bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short-term prediction model of photovoltaic power generation based on rough set-BP neural network
Authors: Ma Xiaoling , Pang Qingle , Xie Qingsong 
Published: April 2021

Abstract
It is very important to predict the photovoltaic power generation because of the great challenges to the safe and stable operation of the power grid. Based on the analysis of traditional forecasting models, a power generation forecasting model based on rough set and neural network is proposed. Firstly, the Hampel filtering algorithm and rough set theory are used to process outliers and redundant data for the collected information. The above algorithms solve the problem of big data processing before forecasting. Finally, the fuzzy C-means clustering was used to divide the data set and combined with the neural network to predict. The key weather feature variables combined with the forecast time were taken as the input and the power was taken as the output variable. The results show that the prediction method proposed in this paper is more accurate and fast in predicting the power generation at each time.
Markov model in home energy management system
Authors: Bai Jiayuan 
Published: April 2021

Abstract
An intelligent home energy management system was proposed. Reinforcement learning and a markov prediction model were used to help the system make decisions. The Markov model predicted the future state of users or the weather, and the intelligent decisionmaking support system sent signals to local controllers to control furniture. This work benefits energy management because if the system knows the user’s next state, it can control a specific appliance to save energy. Meanwhile, if the system can predict the weather, the house can use green energy rationally. The proposed energy management system could be applied in an intelligent house, city energy management systems, and building energy management. The state prediction helped the decision-making system make accurate and rational decisions.
Distribution Network Island Partition and Black Start Based on Distributed Generation
Authors: Li Jian , Xiao Qiang , He Ge , Fu Yameng 
Published: April 2021

AbstractIn order to reduce the power outage loss of the grid after a large area power failure in the regional power system, it is necessary to start the black power grid as soon as possible. For distribution networks with distributed generation (DG), it is of great significance to determine the partition scheme of islands and put forward the black start strategy of DG to continue to supply power to the loads, so as to reduce the power outage loss. Fully considering the importance of loads and their controllability, an island partition scheme of two steps are proposed based on the established mathematical model. The primary island is formed by using the dynamic programming algorithm, and then, the secondary island is formed by modifying primary island according to certain rules, thus obtaining the optimal island. Then the starting sequence of the black start power supply in the island is determined by Analytic Hierarchy Process (AHP) and the black start strategy is obtained. The effectiveness of the proposed island partition and black start strategy is verified by using the example of PG&E69-node system.
Neural Network Quantization Methods For Voice Wake Up Network
Authors: Zhang Shurui , Li Xiangyu , Zhang Chen 
Published: April 2021

Abstract
Quantifying the pre-trained neural network model can reduce its storage size and speed up the forward-inference process. Previous researches for the quantization of voice wake up networks couldn’t reach our anticipation for applying it to applications. The voice wake up network is mainly composed of recurrent neural network and classification function. Recurrent neural network can take preorder words into consideration and it widely used in voice network. In this paper, we propose method to quantize the structure of recurrent neural networ including RNN, GRU and LSTM by optimizing the method of quantifying the activation function. At the same time, using the translation invariance of the classification function to improve classification accuracy on Speech commands dataset version 2. Using the method proposed in this paper, we can make the quantized model achieve a better voice wake up rate.
Research on Intelligent Temperature Control Technology for Spacecraft with Instantaneous High Power Load
Authors: Wang Jin , Gong Mengmeng , Zhu Shanglong , Zhang Qun , Chen Yi , Li Defu , Deng Wan , Qi Feng 
Published: April 2021

Abstract
Thermoelectric modules are widely studied by domestic and foreign experts and scholars because of their light weight, small size, absence of mechanical moving parts, and the ability to switch between cooling and heating and adjust the cooling/heating capacity by current. Based on the advantages of thermoelectric modules, this paper proposes an innovative thermoelectric module-based intelligent temperature control device for instantaneous high-power payloads of spacecrafts, which can realize the rapid heat dissipation of high power payloads and adjust the current of thermoelectric modules through intelligent temperature control strategies to precisely regulate the payload temperature. The results show that the thermal control device can efficiently control the heat of the instantaneous high power load during the orbit, and the precision temperature control of the thermoelectric cooling work during the load operation is achieved with the temperature control accuracy of ±0.5°C.
Feature Point Matching Based on Local Relative Velocity Consensus
Authors: Shao Feng , Liu ZhaoXia , Jubai  
Published: April 2021

Abstract
Feature matching is still a crucial and challenging problem in image processing. In this paper, a novel feature matching algorithm based on local relative velocity consensus (LRVC) is proposed to find two accurate matched feature points. To remove the outliers accurately and robustly, the relative velocity between the putative matches and their corresponding neighbors are exploited. Based on the consensus of relative velocity and the consensus of neighborhood elements, the similarity of each putative matches is evaluated. With a two iteration outlier removal strategy, the feature points are matched accurately and robustly. In the experiment, VGG dataset are used to verify the accuracy and robustness of the proposed method LRVC. The matching results indicate that our method is superior to three other classic feature matching methods.
A Terahertz 3dB Waveguide Power Divider with 90° Phase Shifter Integrated
Authors: Jin Liang , Li Xiaojun , Zhu Zhongbo 
Published: April 2021

Abstract
A 3dB power divider is designed based on E-plane waveguide directional coupler and self-compensating waveguide phase shifter. This power divider was implemented with a center frequency at 110GHz. Simulation results show that amplitude balance within ±0.3dB and phase balance within +0.5/-1.2 degrees, and isolation is better than -15 dB from 100 to 120 GHz. It has good performance in-band flatness and bandwidth is 18%. It can be used in terahertz communication system.
Identifying 3D Models by Matching Rendered Image and Depth Image with Using a New Combined Descriptor
Authors: Jiang Dayou 
Published: April 2021

Abstract
This paper presented a 3D model identification method by matching pairs of rendered images and depth images. Firstly, the technique uses the HARRIS detector and PIIFD detector (partial intensity invariant feature descriptor) to detect feature points of rendered-depth image pair of shape and then uses LGHD (Log-Gabor Histogram Descriptor) to descript these feature points. Secondly, the shape identification processing is conducted, including normalizing shape pose, capturing multi-view pairs of rendered images and depth images, and image matching. Finally, 100 pairs of 3D models are used for the experiment. The experiment results show that the proposed method has an efficient performance on rendered-depth image matching and can be used for 3D model identification.
An Improved Compensation Current Detection Method of Static Synchronous Compensator
Authors: Tongsheng Wei , xiaochen Zhang , Xueying Qiu , Kangheng Qiao , Jianchao Xu 
Published: April 2021

Abstract
When the load current check point and compensation injection point of the Static Synchronous Compensator (STATCOM) are at different positions and there are differences in phase and amplitude, there will be a detection difference. To solve this problem, this paper proposes an improved STATCOM compensation command current detection method based on the ip-iq algorithm. This method can eliminate errors and improve detection accuracy by setting the preset phase angle and proportional integral (PI) controller according to the voltage phase and amplitude difference between the check point and the compensation point, thus breaking through the traditional ip-iq. The algorithm is only applicable to the situation where the detection point and the compensation point are at the same position, which improves the accuracy of detection. Theoretical analysis and simulation results show the effectiveness of the method. S
Research on radar main lobe false target jamming feature extraction based on time-frequency domain and fluctuation characteristics
Authors: Wu Ke , Cha Hao 
Published: April 2021

Abstract
Aiming at radar main lobe false target jamming, the forms of target echo and jamming signal are analyzed, and its modeling and simulation are carried out. By extracting the 11 dimensional features of time domain, frequency domain and amplitude fluctuation characteristics, it is proved that it is distinguishable for real target echo and false target jamming signal through simulation experiment, and a feature model is established; aiming at the shortcomings of traditional classification model, bagging algorithm is applied to deal with the over fitting phenomenon. Simulation results show that the feature model established in this paper has good performance in bagging algorithm.
Small Face Detection Based On Feature Fusion
Authors: Hao Zili , Shi Hangqi 
Published: April 2021

Abstract
While great progress has been made in face detection, one of the remaining challenges is to detect the faces of small targets in images. The small target face we define, mainly includes the absolute size of the face is not greater than 32×32 pixels and the relative proportion of the face size is not greater than one tenth of the image size. To meet this challenge, we propose an effective face detector, called SmallFaceBoxes, which has a better performance in both speed and accuracy. Specifically, our method has a lightweight but powerful network structure consisting of small target face detection layers and multi-scale convolution layers. The design of small target face detection layers enables detector to increase the representation ability of small and medium-sized faces in the image and improve the detection accuracy of small faces. The multi-scale convolution layers aim at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales. In addition, according to the size of receptive field, we propose a strategy of setting Anchor in multiple feature layers, thus improving the recall rate of small face. As a consequence, our algorithm performs well on the wideface dataset.
Adaptive droop control of DC distribution network considering photovoltaic output power margin
Authors: Qing Liu , Tongyu Zhang 
Published: April 2021

Abstract
When multiple photovoltaic power sources are connected in parallel in the DC distribution network, photovoltaic with different output have differences in the regulation capacity of unbalanced power of the system. In order to make full use of the power margin of photovoltaic to adjust the DC bus voltage, this paper proposes an adaptive droop control of DC distribution network considering the photovoltaic output power margin. The voltage signals of the input and output terminals of the PV side converter are used to judge the system load change and the output of the photovoltaic power supply. On the basis of traditional droop control, the droop coefficient is modified based on the input voltage deviation of PV side converter to realize the reasonable distribution of the unbalanced power between photovoltaic power sources with different power margin. The output impedance characteristic model of PV side converter is established, and the adaptive droop control proposed in this paper can effectively improve the stability of multi PV parallel connected DC distribution system. Finally, the effectiveness of the proposed control method is verified by MATLAB/simulink platform simulation.
An Inexact Double Primal-Dual Algorithm for Saddle Point Problems
Authors: Fang Changjie , Chen Jingyu 
Published: April 2021

Abstract
In this paper, we study a saddle point problem and propose an inexact double primal-dual algorithm for solving the saddle point problem. The sequence generated by the proposed algorithm is proved to globally converge to the saddle point of the saddle point problem in the ergodic sense, and the convergence rate of the algorithm is also obtained. For the model of total variation image processing, the performance of the algorithm is demonstrated. Simulation results show that our method is more efficient in image denoising compared with existing methods.
A Formal Verification Method for Security Protocol Implementations Based on Model Learning and Tamarin
Authors: Zhang Xieli , Zhu Yuefei , Gu Chunxiang , Miao Xuyang 
Published: April 2021

Abstract
The verification of security protocol implementations is notoriously difficult and important. In this paper, combining with the model learning using Tamarin, a formal verification tool of protocol specification, a formal verification method for security protocol implementations is proposed. We extract state machine information from protocol implementations by model learning, and determine suspicious paths in the finite-state machines by cross-validation between different implementations of the same protocol; and then verify whether the suspicious paths violate the security properties of the protocol using Tamarin. It can be used to detect logical errors in protocol implementations and avoid relying on expert experience to make compliance rules from protocol documents when using model checking tools. The effectiveness of this method is demonstrated by the vulnerability detection of the typical ChangeCipherSpec in the TLS protocol implementation. The method proposed can help developers to develop more robust implementations of security protocols.
Research on solid-state fermentation process in a closed environment with multiple interferences
Authors: Tan HuiDan , Zhang Peng 
Published: April 2021

Abstract
A closed battery detection system consists of a semiconductor alcohol sensor, a temperature sensor, a STM32F103 microcontroller, and a Windows 10 operating system computer. The ZigBee communication and RS485 communication technology are used to detect the temperature and alcohol concentration of the Dianchi Lake online, which solves the problem of manual sampling and damage to the sealing of the Dianchi Lake. Field tests have shown that the acquisition system data meets the manual physical and chemical test data.
Research and design of an intelligent ventilation system
Authors: Shuang Luo , Ming Wei 
Published: April 2021

Abstract
A kind of intelligent ventilation system is studied in this paper, which includes host system and slave system. The design scheme and schematic diagram of the hardware circuit are given. A variety of sensors are integrated, which can measure temperature, humidity, formaldehyde, PM2.5 dust, smoke and other parameters. According to the measured data, the host sends out control commands such as “open window” ” purify air” and “draught fan speed”, and realizes intelligent ventilation. The system has dust prevention, damp proofing and other work mode. The power drive circuit designed by SCR designs to realize no spark control. Host monitors multiple slave stations using ZigBee wireless networks, through the WIFI broadband access network and realize the application of “Internet +”. Therefore, users can view and monitor the home environment status through the mobile phone APP software. The system can be used in the newly decorated houses without ventilation, and can also be used in various mines, subway stations, working room of chemical plant and other workplaces
Research on Optimal Strategy of Peak-shaving of Photovoltaic Grid-connected System Based on Simulated Annealing-Q Learning Algorithm
Authors: Jun Xu , Jinhui Chen , Zhe Zhang 
Published: April 2021

Abstract
In order to alleviate the problem of large-scale grid-connected photovoltaics and increase the pressure of grid peak regulation, this paper proposes a dynamic economic dispatch method considering the system peak regulation margin. The system peak shaving margin is proposed to deal with the flexibility problem in economic dispatch and improve the enthusiasm of thermal power unit peak shaving. The economic dispatch model is transformed into a dynamic programming model and solved by the simulated annealing-Q learning algorithm. The analysis of the results shows that the proposed dynamic programming strategy can effectively improve the operating economy of the system and increase the flexibility of peak shaving of thermal power units.
Application of XGBoost in P2P Default Prediction
Authors: Li Zhiqiang , Li Shouyan , Li Zhilong , Hu Yixiang , Gao Hanlin 
Published: April 2021

Abstract
P2P network lending is a “ peer-to-peer ” loan through a third-party Internet platform built by P2P companies. The application of machine learning algorithms to the field of P2P loan default prediction will improve the operating capabilities of the platform, and also effectively regulate the lending market. In this paper, we use Lending Club’s loan data and feature engineering technology to apply the XGBoost algorithm to construct a P2P loan default prediction model, and we choose five performances: accuracy, AUC value, error rate, model robustness, and model run time to compare it with Logistic Regression and Decision Trees. The result shows that the prediction accuracy rate of the XGBoost algorithm is 97.705%, which fits the actual results better, and can effectively control the loss cost caused by model errors. In addition, we also select 10 features that have the greatest impact on loan default rates based on the XGBoost algorithm, and provide a reference for P2P lending platforms.
Research on Product Design Technology of Computer Aided Innovation
Authors: Xue Xiaoguang 
Published: April 2021

Abstract
This article mainly briefly introduces the related content of computer-aided innovation technology. This article discusses the effective application of computer-aided innovation product design technology by analyzing the necessity of knowledge utilization in the process of product innovation design. This article takes full advantage of computer technology, constantly innovates product design, develops products that meet people’s actual needs based on market demand, and optimizes product design. This can guarantee the quality of product design and enhance the company’s market competitiveness. The effective use of key knowledge can not only solve the technical difficulties in product design innovation, but also improve the technical level of computer-aided innovation product design.
Research on mass monitoring data Retrieval Technology based on HBase
Authors: Xu Haojie 
Published: April 2021

Abstract
With the arrival of the era of big data, the data generated by the monitoring system grows rapidly, the storage and quick retrieval of massive monitoring data pose a challenge to the database. HBase is an open-source version of Bigtable, built on top of HDFS, based design and query on rowkey is quick, but with the development of database application, when retrieving non-rowkey fields, HBase can only query by scanning the full table, which obviously cannot meet the actual requirements, and the query of the monitoring data is mostly based on the most recent data, so for this problem, this article presents a secondary indexing approach based on coprocessor and Redis. This method realizes the rapid creation and automatic update of secondary indexes in HBase and Redis through the coprocessor. It gets the corresponding rowkey quickly during retrieval, and query the corresponding data in the data table according to the rowkey. The former stores the index of the data table, while the latter stores the index of the latest data in the data table, to improve the real-time performance of data retrieval.
Self-selection Protocol Algorithm for Wireless Networks based on DDQN
Authors: Wang Chongyang , Yan Hairong , Li Fan 
Published: April 2021

Abstract
Given the current complex heterogeneous network environment, choosing different networks in different user scenarios limits the effectiveness of network access. To solve this problem, an algorithm based on DDQN is proposed to optimize the network configuration. The reward value is determined by service type, throughput, delay, and signal strength. DDQN can avoid the ping-pong effect that can be generated by network selection and stabilize the network environment by splitting action selection and action evaluation to prevent overestimation. The experimental results show that the algorithm can autonomously select and assign network protocols and can more accurately find network access methods suitable for user scenarios than the current network switching method represented by a single network parameter based on RSSI and CCA.
Research on Optimal Path Selection Based on WebGIS
Authors: Tan Yafang 
Published: April 2021

Abstract
With the continuous development of geographic information system technology, the ability to analyze and process various spatial information has been greatly enriched and strengthened. The optimal path analysis is the current research hotspot in spatial analysis. In this paper, Changsha City in Hunan Province was taken as an example to build an optimal path selection platform based on WebGIS. With the help of ArcGIS network analysis tool, network analysis data set was established for vector road data, and road length was selected as impedance factor to realize optimal path search.
Research on economic dispatch based on improved firefly ag-orithm
Authors: Wang Xingang , Kai Saijiang , Zhang Feng , Sun Licheng , Huang Ping 
Published: April 2021

Abstract
An improved firefly algorithm for solving the economic dispatch problem of power system is proposed. The algorithm considers the climbing rate, the dead zone and other constraints, and calculates the network loss. This algorithm is based on the firefly algorithm, a new repair strategy for active correction of the violation of the constraint condition of all kinds of fireflies, and combined with the penalty function technique, the fireflies in the feasible region or as close as possible to the feasible solution search in the area. The accuracy and speed of the algorithm can be effectively improved by greatly reducing the probability of finding the optimal location of the firefly in the infeasible solution region. The simulation results show that the algorithm has the characteristics of high speed, high accuracy and good convergence.