query stringlengths 5 348 | positive stringlengths 12 10.2k | negative stringlengths 0 10.2k | scores listlengths 2 2 |
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what is gappso? | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | Job-shop Scheduling Problem (JSP) is one of extremely hard problems because it requires very large combinatorial search space and the precedence constraint between machines. The traditional algorithm used to solve the problem is the branch-andbound method, which takes considerable computing time when the size of proble... | [
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what is gappso? | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | Leaky wave antenna integrated into gap waveguide technology: A novel leaky wave antenna, based on the gap waveguide technology, is here proposed. A groove gap-waveguide is used as feeding and it also acts as antenna at the same time. The proposed antenna provides an excellent performance while maintaining a simple desi... | [
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what is gappso? | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | PAMS: A new position-aware multi-sensor dataset for human activity recognition using smartphones: Nowadays smartphones are ubiquitous in various aspects of our lives. The processing power, communication bandwidth, and the memory capacity of these devices have surged considerably in recent years. Besides, the variety of... | [
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what is gappso? | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | A photovoltaic (PV) generation system (PGS) is becoming increasingly important as renewable energy sources due to its advantages such as absence of fuel cost, low maintenance requirement, and environmental friendliness. For large PGS, the probability for partially shaded condition (PSC) to occur is also high. Under PSC... | [
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what is gappso? | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | In the analysis of sequence-based data matrices, the use of different methods of treating gaps has been demonstrated to influence the resulting phylogenetic hypotheses (e.g., Eernisse and Kluge, 1993; Vogler and DeSalle, 1994; Simons and May den, 1997). Despite this influence, a well-justified, uniformly applied method... | [
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what is hgapso | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | Sego is a hypervisor-based system that gives strong privacy and integrity guarantees to trusted applications, even when the guest operating system is compromised or hostile. Sego verifies operating system services, like the file system, instead of replacing them. By associating trusted metadata with user data across al... | [
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what is hgapso | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems: Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a soci... | [
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what is hgapso | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems: In the Bacteria Foraging Optimization Algorithm (BFAO), the chemotactic process is randomly set, imposing that the bacteria swarm together and keep a safe distance from each other. In hybrid bacteria foragin... | [
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what is hgapso | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | In the Bacteria Foraging Optimization Algorithm (BFAO), the chemotactic process is randomly set, imposing that the bacteria swarm together and keep a safe distance from each other. In hybrid bacteria foraging optimization algorithm and particle swarm optimization (hBFOA-PSO) algorithm the principle of swarming is intro... | [
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what is hgapso | A hybrid of genetic algorithm and particle swarm optimization for recurrent network design: An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid... | High performance work systems: the gap between policy and practice in health care reform.: PURPOSE
Studies of high-performing organisations have consistently reported a positive relationship between high performance work systems (HPWS) and performance outcomes. Although many of these studies have been conducted in manu... | [
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what is the ep used for | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Overview of the EVS codec architecture: The recently standardized 3GPP codec for Enhanced Voice Services (EVS) offers new features and improvements for low-delay real-time communication systems. Based on a novel, switched low-delay speech/audio codec, the EVS codec contains various tools for better compression efficien... | [
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what is the ep used for | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | SKEE: A lightweight Secure Kernel-level Execution Environment for ARM: Previous research on kernel monitoring and protection widely relies on higher privileged system components, such as hardware virtualization extensions, to isolate security tools from potential kernel attacks. These approaches increase both the maint... | [
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what is the ep used for | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | An extension of the Doherty amplifier architecture which maintains high efficiency over a wide range of output power (>6 dB) is presented. This extended Doherty amplifier is demonstrated experimentally with InGaP-GaAs HBTs at a frequency of 950 MHz. P/sub 1 dB/ is measured at 27.5 dBm with PAE of 46%. PAE of at least 3... | [
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what is the ep used for | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Most content providers are interested in providing good video delivery QoE for all users, not just on average. State-of-the-art ABR algorithms like BOLA and MPC rely on parameters that are sensitive to network conditions, so may perform poorly for some users and/or videos. In this paper, we propose a technique called O... | [
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what is the ep used for | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Electric power steering (EPS) system plays an important role in assisting the driver to achieve better handling, steering feel and response in securing vehicle stability. In EPS control system, controlling the torque of the EPS motor is crucial where tracking of the robust command of motor angle to generate desired ass... | [
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what is dynamic economic dispatch | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Distributed Event-Triggered Scheme for Economic Dispatch in Smart Grids: To reduce information exchange requirements in smart grids, an event-triggered communication-based distributed optimization is proposed for economic dispatch. In this work, the θ-logarithmic barrier-based method is employed to reformulate the econ... | [
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what is dynamic economic dispatch | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | To reduce information exchange requirements in smart grids, an event-triggered communication-based distributed optimization is proposed for economic dispatch. In this work, the θ-logarithmic barrier-based method is employed to reformulate the economic dispatch problem, and the consensus-based approach is considered for... | [
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what is dynamic economic dispatch | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Economic dispatch for a microgrid considering renewable energy cost functions: Microgrids are operated by a customer or a group of customers for having a reliable, clean and economic mode of power supply to meet their demand. Understanding the economics of system is a prime factor which really depends on the cost/kWh o... | [
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what is dynamic economic dispatch | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Dynamic simultaneous fare proration for large-scale network revenue management: Network revenue management is concerned with managing demand for products that require inventory from one or several resources by controlling product availability and/or prices in order to maximize expected revenues subject to the available... | [
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what is dynamic economic dispatch | A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function: Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to... | Dynamic TXOP HCCA reclaiming scheduler with transmission time estimation for IEEE 802.11e real-time networks: IEEE 802.11e HCCA reference scheduler guarantees Quality of Service only for Constant Bit Rate traffic streams, whereas its assignment of scheduling parameters (transmission time TXOP and polling period) is too... | [
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which type of systems is genetic fuzzy | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. The QGA is adopted because of their capabilities of directed random search for global optimiz... | [
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which type of systems is genetic fuzzy | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Most fuzzy controllers and fuzzy expert systems must predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy ... | [
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which type of systems is genetic fuzzy | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Fuzzy logic controller for an inverted pendulum system using quantum genetic optimization: In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. Th... | [
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which type of systems is genetic fuzzy | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | The present article is a novel attempt in providing an exhaustive survey of neuro-fuzzy rule generation algorithms. Rule generation from artificial neural networks is gaining in popularity in recent times due to its capability of providing some insight to the user about the symbolic knowledge embedded within the networ... | [
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which type of systems is genetic fuzzy | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Introduction: Hybrid intelligent adaptive systems: This issue of International Journal of Intelligent Systems includes extended versions of selected papers from the 4th International Conference on Soft Computing, held in Iizuka, Japan, September 30]October 5, 1996. The topic of the special issue is ‘‘Hybrid Intelligent... | [
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what are genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Most fuzzy controllers and fuzzy expert systems must predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy ... | [
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what are genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. The QGA is adopted because of their capabilities of directed random search for global optimiz... | [
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what are genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Fuzzy logic controller for an inverted pendulum system using quantum genetic optimization: In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. Th... | [
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what are genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | The present article is a novel attempt in providing an exhaustive survey of neuro-fuzzy rule generation algorithms. Rule generation from artificial neural networks is gaining in popularity in recent times due to its capability of providing some insight to the user about the symbolic knowledge embedded within the networ... | [
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what are genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Introduction: Hybrid intelligent adaptive systems: This issue of International Journal of Intelligent Systems includes extended versions of selected papers from the 4th International Conference on Soft Computing, held in Iizuka, Japan, September 30]October 5, 1996. The topic of the special issue is ‘‘Hybrid Intelligent... | [
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genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Most fuzzy controllers and fuzzy expert systems must predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy ... | [
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genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. The QGA is adopted because of their capabilities of directed random search for global optimiz... | [
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genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Fuzzy logic controller for an inverted pendulum system using quantum genetic optimization: In this paper, we propose a new generalized design methodology of intelligent robust fuzzy control systems based on quantum genetic algorithm (QGA) called quantum fuzzy model that enhance robustness of fuzzy logic controllers. Th... | [
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genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | The present article is a novel attempt in providing an exhaustive survey of neuro-fuzzy rule generation algorithms. Rule generation from artificial neural networks is gaining in popularity in recent times due to its capability of providing some insight to the user about the symbolic knowledge embedded within the networ... | [
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genetic fuzzy systems | Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases: It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in th... | Introduction: Hybrid intelligent adaptive systems: This issue of International Journal of Intelligent Systems includes extended versions of selected papers from the 4th International Conference on Soft Computing, held in Iizuka, Japan, September 30]October 5, 1996. The topic of the special issue is ‘‘Hybrid Intelligent... | [
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what is the parameter of inertia | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | The fusion of inertial and visual data is widely used to improve an object’s pose estimation. However, this type of fusion is rarely used to estimate further unknowns in the visual framework. In this paper we present and compare two different approaches to estimate the unknown scale parameter in a monocular SLAM framew... | [
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what is the parameter of inertia | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | This paper focuses on motion estimation using inertial measurements and observations of naturally occurring point features. To date, this task has primarily been addressed using filtering methods, which track the system state starting from known initial conditions. However, when no prior knowledge of the initial system... | [
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what is the parameter of inertia | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | A redundant inertial measurement unit (IMU) is an inertial sensing device composed by more than three accelerometers and three gyroscopes. This paper analyses the performance of redundant IMUs and their potential benefits and applications in airborne remote sensing and photogrammetry. The theory of redundant IMUs is pr... | [
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what is the parameter of inertia | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | Visual-Inertial-Semantic Scene Representation for 3D Object Detection: We describe a system to detect objects in three-dimensional space using video and inertial sensors (accelerometer and gyrometer), ubiquitous in modern mobile platforms from phones to drones. Inertials afford the ability to impose class-specific scal... | [
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what is the parameter of inertia | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | A Kalman Filter-Based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation: Vision-aided inertial navigation systems (V-INSs) can provide precise state estimates for the 3-D motion of a vehicle when no external references (e.g., GPS) are available. This is achieved by combining inerti... | [
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when is the inertia weight introduced | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | We describe a system to detect objects in three-dimensional space using video and inertial sensors (accelerometer and gyrometer), ubiquitous in modern mobile platforms from phones to drones. Inertials afford the ability to impose class-specific scale priors for objects, and provide a global orientation reference. A min... | [
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when is the inertia weight introduced | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | This paper introduces a novel human activity monitoring system combining Inertial Measurement Units (IMU) and Mechanomyographic (MMG) muscle sensing technology. While other work has recognised and implemented systems for combined muscle activity and motion recording, they have focused on muscle activity through EMG sen... | [
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when is the inertia weight introduced | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | This paper presents a tracking system for ego-motion estimation which fuses vision and inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters), where a comparison of their performance has been done. It also considers the multi-rate nature of the sensors: inertial sensing is sampled at a fast sam... | [
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when is the inertia weight introduced | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | Fast Ego-motion Estimation with Multi-rate Fusion of Inertial and Vision: This paper presents a tracking system for ego-motion estimation which fuses vision and inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters), where a comparison of their performance has been done. It also considers the m... | [
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when is the inertia weight introduced | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | With the increasing rise of professionalism in sport, athletes, teams, and coaches are looking to technology to monitor performance in both games and training in order to find a competitive advantage. The use of inertial sensors has been proposed as a cost effective and adaptable measurement device for monitoring wheel... | [
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what is the particle swarm optimizer called | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | This paper introduces a novel parameter automation strategy for the particle swarm algorithm and two further extensions to improve its performance after a predefined number of generations. Initially, to efficiently control the local search and convergence to the global optimum solution, time-varying acceleration coeffi... | [
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what is the particle swarm optimizer called | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications: Particle swarmoptimization (PSO) is a heuristic global optimizationmethod, proposed originally byKennedy and Eberhart in 1995. It is now one of themost commonly used optimization techniques.This survey presented a comprehensive invest... | [
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what is the particle swarm optimizer called | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | A New Discrete Particle Swarm Optimization Algorithm: Particle Swarm Optimization (PSO) has been shown to perform very well on a wide range of optimization problems. One of the drawbacks to PSO is that the base algorithm assumes continuous variables. In this paper, we present a version of PSO that is able to optimize o... | [
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what is the particle swarm optimizer called | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | [
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what is the particle swarm optimizer called | A modified particle swarm optimizer: In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer. | Hybrid Particle Swarm Optimiser with breeding and subpopulations: In this paper we present two hybrid Particle Swarm Optimisers combining the idea of the particle swarm with concepts from Evolutionary Algorithms. The hybrid PSOs combine the traditional velocity and position update rules with the ideas of breeding and s... | [
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what is the rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Recurrent Neural Networks (RNN) are a type of statistical model designed to handle sequential data. The model reads a sequence one symbol at a time. Each symbol is processed based on information collected from the previous symbols. With existing RNN architectures, each symbol is processed using only information from th... | [
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what is the rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In this article, we detail updates and improvements ... | [
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what is the rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | We introduce the Residual Memory Network (RMN) architecture to language modeling. RMN is an architecture of feedforward neural networks that incorporates residual connections and time-delay connections that allow us to naturally incorporate information from a substantial time context. As this is the first time RMNs are... | [
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what is the rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Machine learning on sequential data using a recurrent weighted average: Recurrent Neural Networks (RNN) are a type of statistical model designed to handle sequential data. The model reads a sequence one symbol at a time. Each symbol is processed based on information collected from the previous symbols. With existing RN... | [
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what is the rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Rfam 12.0: updates to the RNA families database: The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In ... | [
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what is rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Recurrent Neural Networks (RNN) are a type of statistical model designed to handle sequential data. The model reads a sequence one symbol at a time. Each symbol is processed based on information collected from the previous symbols. With existing RNN architectures, each symbol is processed using only information from th... | [
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what is rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In this article, we detail updates and improvements ... | [
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what is rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Machine learning on sequential data using a recurrent weighted average: Recurrent Neural Networks (RNN) are a type of statistical model designed to handle sequential data. The model reads a sequence one symbol at a time. Each symbol is processed based on information collected from the previous symbols. With existing RN... | [
0.5852667093276978,
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] |
what is rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | We introduce the Residual Memory Network (RMN) architecture to language modeling. RMN is an architecture of feedforward neural networks that incorporates residual connections and time-delay connections that allow us to naturally incorporate information from a substantial time context. As this is the first time RMNs are... | [
0.5852667093276978,
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what is rfnn | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Rfam 12.0: updates to the RNA families database: The Rfam database (available at http://rfam.xfam.org) is a collection of non-coding RNA families represented by manually curated sequence alignments, consensus secondary structures and annotation gathered from corresponding Wikipedia, taxonomy and ontology resources. In ... | [
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what is fuzzy neural network | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems: This paper studies an adaptive tracking control for a class of nonlinear stochastic systems with unknown functions. The considered systems are in the nonaffine pure-feedback form, and it is the first to control this class... | [
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what is fuzzy neural network | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | A DYNAMIC FUZZY-COGNITIVE-MAP APPROACH BASED ON RANDOM NEURAL NETWORKS: A fuzzy cognitive map is a graphical means of representing arbitrarily complex models of interrelations between concepts. The purpose of this paper is to describe a dynamic fuzzy cognitive map based on the random neural network model. Previously, w... | [
0.6705715656280518,
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what is fuzzy neural network | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | A fuzzy cognitive map is a graphical means of representing arbitrarily complex models of interrelations between concepts. The purpose of this paper is to describe a dynamic fuzzy cognitive map based on the random neural network model. Previously, we have developed a random fuzzy cognitive map and illustrated its applic... | [
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what is fuzzy neural network | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | A Fuzzy-Neural Intelligent Trading Model for Stock Price Prediction: In this paper, Fuzzy logic and Neural Network approaches for predicting financial stock price are investigated. A study of a knowledge based system for stock price prediction is carried out. We explore Trapezoidal membership function method and Sugeno... | [
0.6705715656280518,
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what is fuzzy neural network | Identification and control of dynamic systems using recurrent fuzzy neural networks: This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using ... | The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. The following paper introduces such operators on hand of computer vision application. In this paper a novel method based on fuzzy logic reasoning s... | [
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what is the body area in the fusiform gyrus | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.125 x 3.125 x 4.0 mm) and high resolution (1.4 x 1.4 x 2.0 mm... | [
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what is the body area in the fusiform gyrus | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Recent functional imaging studies have referred to a posterior region of the left midfusiform gyrus as the "visual word form area" (VWFA). We review the evidence for this claim and argue that neither the neuropsychological nor neuroimaging data are consistent with a cortical region specialized for visual word form repr... | [
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what is the body area in the fusiform gyrus | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Using in-vivo magnetic resonance morphometry it was investigated whether the midsagittal area of the corpus callosum (CC) would differ between 30 professional musicians and 30 age-, sex- and handedness-matched controls. Our analyses revealed that the anterior half of the CC was significantly larger in musicians. This d... | [
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what is the body area in the fusiform gyrus | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | The anatomy and functional role of the inferior fronto-occipital fascicle (IFOF) remain poorly known. We accurately analyze its course and the anatomical distribution of its frontal terminations. We propose a classification of the IFOF in different subcomponents. Ten hemispheres (5 left, 5 right) were dissected with Kl... | [
0.6354947090148926,
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what is the body area in the fusiform gyrus | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | The myth of the visual word form area: Recent functional imaging studies have referred to a posterior region of the left midfusiform gyrus as the "visual word form area" (VWFA). We review the evidence for this claim and argue that neither the neuropsychological nor neuroimaging data are consistent with a cortical regio... | [
0.6354947090148926,
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] |
where is the fusiform gyrus located | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.125 x 3.125 x 4.0 mm) and high resolution (1.4 x 1.4 x 2.0 mm... | [
0.5724499225616455,
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where is the fusiform gyrus located | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Frontal terminations for the inferior fronto-occipital fascicle: anatomical dissection, DTI study and functional considerations on a multi-component bundle: The anatomy and functional role of the inferior fronto-occipital fascicle (IFOF) remain poorly known. We accurately analyze its course and the anatomical distribut... | [
0.5724499225616455,
0.49582070112228394
] |
where is the fusiform gyrus located | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Recent functional imaging studies have referred to a posterior region of the left midfusiform gyrus as the "visual word form area" (VWFA). We review the evidence for this claim and argue that neither the neuropsychological nor neuroimaging data are consistent with a cortical region specialized for visual word form repr... | [
0.5724499225616455,
0.4929455816745758
] |
where is the fusiform gyrus located | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | The anatomy and functional role of the inferior fronto-occipital fascicle (IFOF) remain poorly known. We accurately analyze its course and the anatomical distribution of its frontal terminations. We propose a classification of the IFOF in different subcomponents. Ten hemispheres (5 left, 5 right) were dissected with Kl... | [
0.5724499225616455,
0.4920103847980499
] |
where is the fusiform gyrus located | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | The Neural Architecture of the Language Comprehension Network: Converging Evidence from Lesion and Connectivity Analyses: While traditional models of language comprehension have focused on the left posterior temporal cortex as the neurological basis for language comprehension, lesion and functional imaging studies indi... | [
0.5724499225616455,
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what is ffa in brain | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Dissecting Contributions of Prefrontal Cortex and Fusiform Face Area to Face Working Memory: Interactions between prefrontal cortex (PFC) and stimulusspecific visual cortical association areas are hypothesized to mediate visual working memory in behaving monkeys. To clarify the roles for homologous regions in humans, e... | [
0.562577486038208,
0.5329060554504395
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what is ffa in brain | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Interactions between prefrontal cortex (PFC) and stimulusspecific visual cortical association areas are hypothesized to mediate visual working memory in behaving monkeys. To clarify the roles for homologous regions in humans, event-related fMRI was used to assess neural activity in PFC and fusiform face area (FFA) of s... | [
0.562577486038208,
0.5239884853363037
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what is ffa in brain | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Recent functional imaging studies have referred to a posterior region of the left midfusiform gyrus as the "visual word form area" (VWFA). We review the evidence for this claim and argue that neither the neuropsychological nor neuroimaging data are consistent with a cortical region specialized for visual word form repr... | [
0.562577486038208,
0.487504243850708
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what is ffa in brain | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | BACKGROUND
Frontal fibrosing alopecia (FFA) is a primary lymphocytic cicatricial alopecia with a distinctive clinical pattern of progressive frontotemporal hairline recession. Currently, there are no evidence-based studies to guide treatment for patients with FFA; thus, treatment options vary among clinicians.
OBJECT... | [
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what is ffa in brain | Separate face and body selectivity on the fusiform gyrus.: Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.12... | Frontal fibrosing alopecia: a clinical review of 36 patients.: BACKGROUND
Frontal fibrosing alopecia (FFA) is a primary lymphocytic cicatricial alopecia with a distinctive clinical pattern of progressive frontotemporal hairline recession. Currently, there are no evidence-based studies to guide treatment for patients wi... | [
0.562577486038208,
0.4608234763145447
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what reduces cpu energy | Scheduling for Reduced CPU Energy: The energy usage of computer systems is becoming more important, especially for battery operated systems. Displays, disks, and cpus, in that order, use the most energy. Reducing the energy used by displays and disks has been studied elsewhere; this paper considers a new method for red... | Conservation cores: reducing the energy of mature computations: Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. In this regime, specialized, energy-effi... | [
0.695137083530426,
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what reduces cpu energy | Scheduling for Reduced CPU Energy: The energy usage of computer systems is becoming more important, especially for battery operated systems. Displays, disks, and cpus, in that order, use the most energy. Reducing the energy used by displays and disks has been studied elsewhere; this paper considers a new method for red... | Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. In this regime, specialized, energy-efficient processors can increase parallelism by reducing the per-co... | [
0.695137083530426,
0.5888280272483826
] |
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