bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Information extraction algorithm of Agricultural text based on Machine Learning method
Authors: Wang Zihao , Cheng Zilong , Guan Chenzheng , Han Haoxiang
Published: June 2021

The Internet agricultural technology question and answer platform now only relies on manual to provide answer service, the response speed is slow, and the answer quality is difficult to be guaranteed. In order to realize the intelligent question and answer of agricultural technology and construct the knowledge base of agricultural technology, it is necessary to extract the named entity triple of “crop-pest-pesticide” from the existing question and answer data. There are few researches on agricultural Chinese named entity recognition, and the accuracy is low. According to the characteristics of named entities of crops, diseases and insect pests and pesticides, and according to the question and answer data of agricultural technology, a method of identifying named entities of crops, diseases and pests and pesticides based on conditional random field was proposed. The data set is formatted and segmented automatically, and the corpus after word segmentation is automatically tagged according to whether it contains a specific definition word, whether it contains a specific partial radical, whether it is a quantifier, whether it is a specific left and right definition word and part of speech. Using the tagged data to train the CRF model, we can classify the corpus, including judging whether the corpus belongs to crop, pest and pesticide named entities and identifying the position of the corpus in the compound named entity, thus realizing the recognition of the three kinds of named entities and automatically constructing the associated triple. Through the experiment to select the feature combination and adjust the context window size, the recognition accuracy of this method is improved, the model training time is reduced, and the accuracy of crop, pest and pesticide named entity recognition is 97.72%, 87.63% and 98.05%, respectively, which is significantly higher than the existing methods.
Multi-target Tracking Based on Deep Sort in Traffic Scene
Authors: Duan Chao , Li Xingxing
Published: June 2021

In this paper, we use the deep sort multi-target tracking algorithm to achieve multi-target tracking of pedestrians and vehicles in traffic scenes. In this paper, firstly, yolov4 is used to train the pedestrian and vehicle detection model in traffic scenes. Then, according to the detection frame predicted by yolov4, multi-target tracking is carried out for specific targets. The multi-target tracking algorithm uses deep Sort, which can be combined with yolov4, can achieve less ID switching in real-time reasoning and deal with the loss of occlusion, so as to achieve more stable tracking effect.
Computing Algorithm of Robot Distributed 3D Graphic Simulation System
Authors: Cao Junkai , Gao Zhijun , Han Zhonghua
Published: June 2021

In view of the shortcomings of current multi-robot path planning strategies, such as high path coupling, long total path, and long waiting time for collision avoidance, as well as the resulting problems of low system robustness and low robot utilization, the paper proposes Multi-robot path planning particle swarm algorithm based on distributed three-dimensional space-time graphics and motion decomposition. We first generate a dynamic temporary obstacle in the time dimension according to the existing path set and the current robot position, and expand it together with the static obstacle into a three-dimensional search graphics space. Secondly, in the three-dimensional image space, the total path movement time is divided into three parameters: movement time, turning time and staying time in place, and using the conditional depth-first search strategy to calculate all the matching parameters from the starting node to the target node the required path collection. The experimental results show that the path of distributed 3D graphics planning by our proposed particle swarm algorithm has the advantages of total length, less running time, system collision-free, and high robustness, which solves the problem of multi-robot systems completing continuous random tasks.
Kinematics Analysis of the 6-DOF Test-bed for the Sliding Bearing of Marine Gas Turbine
Authors: Li Xu , Zhang Gang , Yang Yumin
Published: June 2021

In order to solve the problem of simulating complex sea conditions on the sliding bearing test bed of marine gas turbines, a six-degree-of-freedom platform based on the Stewart platform is used to build the test bed. By reasonably arranging the positions of the hinge points on the upper and lower platforms, the inverse kinematics solution is used to calculate the length change of the six driving rods, finally, the simulation was verified by Matlab, which proved that the design is reasonable and feasible, and it can accurately simulate the complicated sea conditions encountered by marine gas turbines during sea navigation. Furthermore, it lays the foundation for further sliding bearing of marine gas turbines test and research.
Genetic Algorithm Based LQR Control for AGV Path Tracking Problem
Authors: Gu Jingming , Fang Dianjun
Published: June 2021

In order to study path tracking of AGV, the lateral dynamic model of AGV is established, and the state equation of the system is obtained. In order to make the state equation better adapt to the LQR controller, a lateral error integral is added to the controller. Then an improved state equation is obtained. The energy function is constructed and the LQR controller is designed. In order to find the optimal value of the weight Q and R in the LQR controller, Genetic Algorithm (GA) is introduced so as to realize the optimization of the LQR controller. The simulation results show that compared with the empirical method to determine the Q and R of LQR control, the LQR control method optimized by GA can effectively reduce the overshoot of the system, improve the convergence speed and stability of the system, and obtain a better path tracking effect.
Fuzzy nonsingular terminal sliding mode control for rigid flexible manipulator
Authors: Xu Lisha , Qian Xiaoshan , Lin Chong
Published: June 2021

In order to solve the precise position control problem of a rigid and flexible manipulator with underactuated variables, the controller of the rigid and flexible manipulator was designed based on the fuzzy nonsingular terminal slip control strategy combined with state feedback. The simulation results show that, compared with the existing basic sliding mode position control methods, the proposed control method has less overshoot, less adjustment time, less input torque jitter, less maximum amplitude of end vibration and less error of end position, which can effectively improve the control quality of the rigid flexible manipulator in the working process.
Electrical Life Test of Small Shell Type Special Contactor and Analysis of Change Trend of Key Characteristics
Authors: Su Jinzhou , Kang Junsheng , Lin Caiping
Published: June 2021

In dealing with electrical fire cases, it is necessary to trace the quality of various electrical products running on the line. It is a very effective and direct way to test the electrical life of the samples of the same specifications and models. The research of electrical life test characteristics can reflect the structural problems, movement performance and other characteristics of the product, which provides a basis for understanding the working state of the product and analyzing the failure reasons. In this paper, a kind of small shell type special contactor commonly used in low-voltage distribution system is taken as the research object, and the variation trend of characteristic parameters such as arcing time, arcing energy and opening phase angle with the operation times of electrical life test is analyzed. Through the establishment of key characteristic quantity database of electrical life, we can better analyze the product performance and grasp the operation status, and provide strong data support for the traceability work caused by its quality problems in electrical fire cases.
An Empirical Study of Evaluation of Library WeChat Micro Service by Mobile Information Network Technology
Authors: Ren Jiasi
Published: June 2021

This research established an assessment mechanism for university library’s micro services from the perspectives of user, information and technology. First, it proposed a Group AHP method based on clustering technique to construct a judgment matrix to evaluate the target system. Second, it conducted an empirical analysis of 8 representative university library WeChat accounts with the fuzzy membership degree function. This paper provides new research perspectives for the WeChat account micro-services, as well as methods to improve their quality and efficiency.
Study on Optimal Operation of AC-DC Hybrid Distribution Network
Authors: Luo Simin , Luan Le , Cui Yiping , Xu Shuo , Guo Qianwen , Liu Tian
Published: June 2021

With the increase of power load and the access of distributed generation, AC/DC hybrid distribution network will become the development trend of urban distribution network in the future. The core of AC/DC distribution and distributed generation are voltage source converters based on full control switches. This paper simply analyzes the operation principle and control mode of voltage source converters, a power flow calculation method of AC/DC hybrid distribution system is proposed, and the optimization model of AC/DC hybrid distribution network with minimum network loss and minimum voltage deviation of DC network is established. The particle swarm swarm (PSO) algorithm is used to solve the calculation. Considering the load disturbance, the droop control is set for each VSC, at the same time this paper compares the advantages and disadvantages of the whole time optimal power calculation and droop control combined with the optimal power calculation method. Then the control mode of the distribution network is proposed. Finally, an example of PG&E 69-node distribution network in the United States is given to verify the correctness of the proposed model and algorithm.
Research and Application of Aptitude Information System and Management Software in Environmental Protection Mechanism
Authors: Wu Xiayun
Published: June 2021

Environmental protection is an important measure to maintain sustainable economic and social development. In response to the increasingly complex external environment and the improvement of lean management requirements of enterprises, the financial management of environmentally-friendly enterprises are an effective way to develop blueprints and strategic goals, and it has an important role to improve corporate efficiency. As an important part of the allergy economy, environmental protection enterprises must innovate their financial management models, improve their budget management systems, actively respond to environmental conditions, and strive to maximize their financial value. Based on this background, this paper takes environmental protection enterprises as an example, analyses the innovative methods of lean management of financial affairs within the enterprise, and hopes to provide new ideas for the financial management of the industry.
A crowdsourcing method for 3D furniture based on parameterized template
Authors: Qiao Biyun , Sun Qun , He Hongyuan
Published: June 2021

With the rapid development of indoor positioning and intelligent robotics technologies, fine-grained location services are approaching. The existing 3D indoor information acquisition and expression methods of furniture are complex and inefficient and cannot meet the needs of high-precision indoor location services. Therefore, this paper proposed a parameterized crowdsourcing method for indoor 3D furniture data based on a model library. This method used a set of classifications and codes of indoor furniture facilities, constructed multilevel feature expression parameters for indoor objects, established an indoor 3D furniture facility model library, and obtained 3D indoor furniture data using the “template + parameters” crowdsourcing method. An indoor furniture data organization model based on 3D parameters was established to manage, store and update indoor furniture facility data. In order to verify the effectiveness of the method, a 3D crowdsourcing system was developed. In the system, the building model was used as the basis for labeling, and the indoor room was the basic unit. The system realizes the functions of indoor scene browsing, 3D furniture data labeling and fast updating. The experimental results prove the feasibility of the crowdsourcing method and provide a new idea for using crowdsourcing for existing indoor 3D data.
Rotary double-layer small high efficiency parking device
Authors: Wang Yuyue , Li Zhenhua , He Kang , Gao Feng
Published: June 2021

In order to solve the problem of urban parking, a rotary double-layer small parking device is designed. By using the rotating double-layer structure, the structure of rotation, frame, lifting and so on is mainly designed, and the device model works are designed and made, and the program design and system debugging of the device model are carried out by using Huiyu ROBO PRO programming software, which verifies the feasibility of the design scheme technology of the device. The rotary double-layer small parking device has a small area and high parking efficiency, which properly solves the problem of parking difficulties in residential areas.
Research on electrical life Trace prediction of contact based on SG-BP algorithm
Authors: Su Jinzhou
Published: June 2021

In order to prevent electrical fire in low-voltage distribution system, it is a very effective measure to predict the electrical life of various low-voltage electrical appliances running on the line. At present, it is difficult to predict the residual electrical life of AC contactors. How to establish a reasonable and reliable prediction model for the residual electrical life of AC contactors is the key to the electrical life test and characteristic research of AC contactors. In this paper, Savitzky-Golay convolution smoothing algorithm is combined with BP neural network algorithm, and the remaining electrical life prediction model of contact is established by taking the arcing time, arcing energy and contact opening phase angle as the input parameters of the prediction model. The test results show that the average relative error of BP residual electrical life prediction model is less than 4%, and the maximum relative error is less than 10%. Combined with Savitzky-Golay convolution smoothing algorithm, SG-BP residual electrical life prediction model has average relative error less than 3% and maximum relative error less than 8%, which improves the prediction accuracy of residual electrical life, and lays a good foundation for making safe and reliable judgment by making better use of electrical life trace data..
Fitness app Application Research Based on big data and algorithm
Authors: Meng Xiangkun
Published: June 2021

This paper analyzes the application of fitness app based on big data and algorithm, and uses literature review and big data analysis technology, Through the analysis of fitness app, it is found that all kinds of fitness app network content is lack of shaping the correct values of practitioners. Through the analysis of the advantages and limitations of moral education in the current fitness app, in order to play the biggest role of moral education in fitness app, and make suggestions for the construction of multi-dimensional moral education.
Dual Mode High Speed Uncooled Short Wave Infrared Camera Based on FPGA
Authors: Liu Qing , Wang Huawei , Bian He , Wang Hua
Published: June 2021

This paper introduces a short-wave infrared camera logic design based on FPGA. The hardware design adopts the architecture of Sofradir Tecless SWIR detector SW640+Xilinx FPGA xc4vsx55, which has a dual working mode of 640×512 at 25 FPS and 64×48 at 4000 FPS. The function of high precision target tracking can be realized by high frequency capture of laser signal. In this design, the non-uniform correction coefficient table in SDRAM cache Flash is controlled by FPGA to correct the image of full resolution mode, and the table of 64×48 is cached by Bram in FPGA to achieve fast image correction and processing. The exposure time is controlled by the external synchronous signal, and the 14 bit precision image data are collected by four ADCs for restoration. The output data is processed by image bad point correction, non-uniform correction, median filtering, histogram equalization, and then the image is packaged and sent by the specified protocol.
Research on Test Method and Sensor of Engine Mount Transmission Force
Authors: Wang Kaiyan , Wang Lingxi , Ren Xiaoxue
Published: June 2021

The engine mount transmission force can be used as an important basis to evaluate the vibration isolation performance of the engine mounting system. However, there is a lack of testing equipment and methods for the transmission force. The force sensor and the test method of the transmission force is studied. The finite element model of the mounting element is established to analyze the arrangement position of the sensor. The force sensor is developed based on the resistance strain gauge. The sensor is arranged in the middle of the intermediate bolt. The test system of mount transmission force is established at the same time. The driving force of driving wheel is obtained through the chassis dynamometer test. The force sensor is calibrated base on the test data. The results of mounting transmission force are obtained through the vehicle road test.
Research on Automatic Braking and Traction Control of High-speed Train Based on Neural Network
Authors: Luo Mingyu , Ke Qian , Li June
Published: June 2021

With the rapid development of economy and technology, people’s quality of life has been continuously improved, which also makes people put forward higher requirements for the quality of transportation. As far as railway transportation is concerned, the running speed and route of trains in the past gradually failed to meet people’s travel needs. Automatic train operation system (ATO), under the protection of automatic train protection system, realizes automatic train driving according to the instructions of automatic train supervision system, and can automatically control the starting, traction, cruising, idling and braking of trains. Traction drive system is the core part of high-speed train, and traction drive converter technology is one of the key technologies of high-speed train. In this paper, according to the different working mechanism of traction and braking, the dynamic model of train under traction and resistance braking is established by combining neural network algorithm, and the corresponding controller is designed by using nonlinear backstepping design method to realize automatic tracking of train speed and position.
Estimation Algorithm of Ionospheric Delay Correction Parameters Based on Neural Network
Authors: Feng Weichen
Published: June 2021

Aiming at the difficulty of separating the ionospheric delay error in the user pseudoring observations of a single-frequency receiver, this paper proposes an error separation method based on BP neural network. The receiver’s observation data for a continuous week is used as a training sample, and the time in the sample is the satellite altitude, azimuth and pseudoring observations are used as the input unit of the BP neural network. The high-precision GIM provided by CODE is used to calculate the corresponding ionospheric delay error, and it is used as the output unit to train the BP neural network. At the end of the thesis, the single-frequency PPP model that uses parameter estimation in the ionosphere is discussed. Finally, the positioning accuracy that this model can achieve is verified through actual calculation examples.
A Classifier of Railway Power Supply Equipment Concern Importance Based on Ensemble Learning
Authors: Zhang Lei , Wang Tianbing , Yu Shengcan , Yu Tao
Published: June 2021

It is of great significance to evaluate the condition of equipment and identify the degree of important concern of equipment for formulating reasonable condition maintenance strategy and ensuring the safe and stable operation of railway power grid. In view of the characteristics that the overload operation state and maintenance interval of equipment are closely related to the equipment state level, the evaluation feature vector composed of five indexes, including overload time of heavy overload equipment, whether the central power supply equipment is in the city center, unrepaired time of equipment, whether it is the power supply equipment and the voltage level of equipment is maintained, is constructed in this subject. In addition, based on the Stacking ensemble learning framework, a hybrid ensemble learning framework algorithm is proposed, which combines the single Bagging and Boosting framework algorithms, and realizes the mapping between feature vectors and importance levels. The data of actual railway power grid equipment are substituted into the model for analysis, and the model is compared with the random forest model based on single ensemble learning algorithm. The simulation results show that compared with other ensemble learning algorithms, the accuracy of equipment state evaluation is significantly improved by using the combination model of stacking ensemble learning method.
Research on transformer fault diagnosis based on GWO-RF algorithm
Authors: Wang Tianbing , Zhang Lei , Wu Yufeng
Published: June 2021

Efficient fault diagnosis of power transformer can effectively ensure the safe and stable operation of power system. Considering that the effect of traditional Random Forest (RF) is seriously affected by the initial parameters, this paper proposes a RF algorithm based on Grey Wolf Optimization (GWO-RF) to improve the accuracy of transformer fault identification. The algorithm uses GWO to optimize the total number of decision trees and the depth of the maximum decision tree, effectively balancing the accuracy of the RF model with the ability to generalize. In this paper, the Dissolved Gas in oil is taken as the fault characteristic quantity, and 335 sets of data are used to form the fault set. Three different data sets are verified by GWO-RF, traditional RF and IEC three ratio method. The experimental results show the effectiveness of GWO-RF method.
Research on Redo Log Record Locating Mechanism in SQL Server Instance Recovery
Authors: Li Aiwu
Published: June 2021

This paper discusses the mechanism of locating log records by LSN in the process of SQL Server instance recovery; and explains the detailed process of forward and rollback operations, as well as the main contents of log records and the functions of checkpoint in the instance recovery process.
Research and Design of Small Semi-Automated Beach-Lawn Cleaning Vehicle by Optimizing the Vibrating Screen Module
Authors: Chen Yujiang , Sun Shuyuan
Published: June 2021

Aiming at the problems of garbage pollution on beaches and lawns, and delays in cleaning up, a small beach was designed. The lawn cleaning vehicle can fill the gap of small sanitation machinery, improve work efficiency and reduce labor intensity. The cleaning vehicle has two working modes: human work and automatic cleaning, which can adapt to different terrains and meet a variety of cleaning needs; it can achieve process-based cleaning through the cleaning module, vibrating screen module and collection module, and it is easy to operate; it can be applied to beaches and lawns, etc. Recreation sites, reducing garbage pollution to the ocean and soil, are inevitable choices for protecting natural resources and developing urban economy, and have good energy-saving, emission-reduction and social benefits.
Optimized Design of Aluminium Bumper by Impact Test and Computer Simulation Analysis
Authors: Su Jintao , Lou Jianping , Jiang Xiaolu
Published: June 2021

Aiming at target steel car bumper new lightweight design, with a target vehicle steel bumper static crushing, three static pressure and impact test and simulation analysis based on the performance parameters, design targets bumper car aluminum alloy box, the section size of anticollision beam and the energy absorption and the materials they need to determine the aluminum bumper performance. The three-point static pressure method is used to optimize the design of the anti-collision beam. Because the loading condition is relatively simple, the optimization function of optistruct is used to optimize it to determine the cross-section shape and size of the anti-collision beam.
Crashworthiness Optimization Design of Minibus Structure
Authors: Ling Tianli , Yu Zheng
Published: June 2021

This paper built the 100% frontal crash model of the minibus, 8 thickness of the components which have obvious effect on vehicle crash performance were selected as design variables, and choose the appropriate evaluation index as the responses. Use DOE experimental design method to get 70 set training data and built Kriging approximate model based on the training data. The approximate model is optimized by PSO algorithm, in the optimized scheme, the a
max and m has decreased by 7.6% and 0.87%, D1, D2 and D3 has decreased by 7.7%, 3.1% and 5.3%.
Design and research of central air conditioning air purifier
Authors: Zhang Qingqing , Wan Zhiqiang
Published: June 2021

Central air conditioning type ultraviolet light air purifier, its sterilization and disinfection is mainly through ultraviolet sterilization. Ultraviolet rays penetrate the cell membranes of various microorganisms, and destroy their DNA structure, resulting in the destruction of their nucleic acid molecular bonds, so as to achieve a variety of bacteria or immediately die or reproduce the purpose of the offspring.
Design and dynamics analysis of intelligent modular cabinet parking device
Authors: Song Mengmeng , Xiong Zicheng , Xiao Shungen
Published: June 2021

With the development of economy and the rapid increase of car ownership, as well as the shortage of land resources in the city, it brings an upgrading opportunity to the traditional parking industry, that is, to develop towards the three-dimensional garage direction. Based on this, this paper puts forward a set of intelligent modular cabinet parking device, which is mainly used in urban community. The device adopts a 3×3 modular cabinet type frame structure, which can not only be controlled by wireless connection of mobile phone, but also be controlled by observing dynamic display film keyboard. The control system of the garage can automatically dispatch the vehicles that are about to be stored in the garage, according to the current storage situation of the vehicles in the garage. It can also make free manual selection through the Arduino system.
Design and Research of Automatic Test Control System for Electric Energy Metering Equipment
Authors: Zhou Yuanfeng , Ding Haili , Hu Tingting , Liu Pengyuan
Published: June 2021

Design an automatic test control system for electric energy metering equipment to realize automatic detection of smart electric energy meters and collection terminals. Use data processing technology, data storage technology, data transmission network technology, and automated instrument analysis technology to realize information management and quality control. The test detection system realizes information collection, processing, storage, transmission, analysis and summarization of various detection businesses, and provides quick and efficient query services, forming the multi-level business processing capabilities of the metrology and testing center, and establishing an efficient, true, and accurate modern detection system.
Research on Status Monitoring and Fault Alarm Device of Drop-out Fuse
Authors: Ju Zeli , Xing Wei , Duan Wei , Sun Haofei , Sun Xin , Liu Shulin
Published: June 2021

Drop-out fuse is a common circuit protection device. When a short fault occurs in the circuit, the fusion pipe will drop and the fuse will be disconnected, so as to isolate the fault line. However, in practical application, there is no reliable means and device for remote monitoring, resulting in the failure information can not be found in time. Although the traditional drop-out fuse alarm device can play the role of fault alarm. It has the disadvantages of large time difference and high cost. Based on this, a set of status monitoring and alarm device according to the drop characteristics of drop-out fuse after failure has been developed. The inclination and temperature of the fusion pipe are monitored by sensors in real time, and the data is sent to the master station through wireless communication. When a fault occurs, the operation and maintenance staff can be notified in time to repair the fault point. Through experimental demonstration, it can be concluded that the fuse status monitoring and fault alarm device has stable performance, convenient control and high cost performance. If it is applied to the distribution network, it can shorten the outage time, reduce economic losses and increase user satisfaction.
Deduction of Artificial Intelligence Calculation Theory in Electrical Engineering Automation
Authors: Meng Bin , Ji Xinyang , Hu Gaoshan
Published: June 2021

In order to overcome the shortcomings of manual on-site confirmation of switch position status in smart substations, realize automatic identification of circuit breaker and isolating switch positions, and improve the remote monitoring capability of switchgear in substations, the paper designs and studies a set of remote substations based on bilateral filtering dissipation algorithm Switch equipment state image recognition system. The system takes SIFT, image gravy method, binary method, Hough transform and other theoretical algorithms as the core, and uses high-speed DSP chip as the platform to divide and combine the switch images collected by the CCD camera. Status identification, and then upload the monitoring picture to the remote monitoring room via Ethernet. Invested in experimental research and found that the identification system is accurate and fast to distinguish the switch status, which can greatly improve the safety and efficiency of switchgear monitoring, and has a high promotion value.
A review on plasma diagnosis technology of pulsed plasma thruster
Authors: Zhao Yuanzheng , Wu Jianjun
Published: June 2021

The plasma diagnosis technology is an essential tool to investigate the plasma characteristics in the pulsed plasma thruster, which can understand the fundamental mechanisms behind pulsed plasma thruster. This review introduces the application of plasma diagnostic technology in pulsed plasma thrusters, investigates the research status of plasma diagnostic technology applied to pulsed plasma thrusters, and discusses usual plasma diagnostics methods. In the contact diagnosis method, the application of Langmuir three probes in the plasma diagnosis of the pulsed plasma thruster is mainly introduced. In the non-contact diagnosis method, the application of optical emission spectroscopy in plasma diagnosis in pulsed plasma thruster is mainly introduced. The advantages and disadvantages of Langmuir three probes and optical emission spectroscopy in plasma diagnosis are analysed.
Handwritten Digit Recognition Scheme Based on Noise Reduction and Trestle Self-Coding
Authors: Wang Jingchen , Yan Tong
Published: June 2021

In this paper, in order to improve the accuracy of handwritten number recognition, a convolutional neural network based on noise reduction and stack auto coding is formed by combining the denoising auto coding algorithm with stack auto coding algorithm. In this paper, the MNIST dataset is preprocessed first, then the noise reduction and stack auto coding network layer are constructed, and finally the stack auto coding algorithm based on the improved denoising auto coding is used to train and test the dataset. Experimental data show that the proposed method achieves low loss value and effectively improves the recognition accuracy in the MNIST test set.
Construction and Application of Urban Intelligent Traffic Control System Based on Cloud Computing
Authors: Zhou Xiangming
Published: June 2021

In today’s society, severe traffic congestion is one of the main reasons hindering social development. However, China’s existing urban transportation system has been basically completed, and it is impossible to make major adjustments. By combining the current fast-developing cloud computing and intelligent algorithms, the original traffic control system is optimized and improved. This system will start from two aspects to optimize the city’s traffic system. On the one hand, it establishes an intelligent signal light device to sort out the city’s traffic situation, thereby greatly improved the congestion at various intersections; on the other hand, it uses cloud data as the basis of vehicle-mounted mobile terminal users. Real-time traffic routed formulation, reasonable allocation of urban traffic resources.
Research on SLAM of indoor mobile robot assisted by AR code landmark
Authors: Gu Cong , Zhao Hongjian , Yuan Junfeng , Teng Bowen , Tian Chenghua
Published: June 2021

When mobile robots use odometer method to locate and map simultaneously in large-scale indoor scenes, there are some problems, such as large accumulated error of odometer, low positioning accuracy due to unreliable information, and large difference between the mapping results and the real environment. In view of the above problems, this paper proposes a method to correct the accumulated error of odometer with the aid of AR code artificial landmark, so as to meet the requirements of high-precision positioning and mapping of mobile robots. Using the particle filter algorithm based on Rao-Blackwellized to perform SLAM in indoor corridors, the comparison of experimental results proves that the method based on AR code landmarks can obtain high-precision positioning when the robot is running at a long distance, and the mapping results are similar to the real environment, the trajectory accuracy of the mobile robot is improved by about 8%.
Application of English Score Management System Based on Spark-Decision Tree Algorithm
Authors: Zhang Yisha
Published: June 2021

This paper is based on the classification decision tree algorithm, based on the Spark cloud platform, through the construction of the decision tree algorithm, and setting AUC parameters, comprehensive comparison of the support vector machine algorithm, and Logistic regression. The results show that the Spark cloud platform has the best robustness, Better realize data forecasting.
Sentiment Analysis of News Comments Based on Improved Intuitionistic Fuzzy Reasoning
Authors: Yang Guangyao , Huo Hua
Published: June 2021

With the development of the Internet, public opinion monitoring emphasizes the need to obtain a more accurate mood prediction model, so as to grasp the public opinion tendency and thinking process more accurately. In addition, the need to process real-world datasets of sentiment analysis without using sampling techniques can introduce noise into the data being used. In this paper, we propose an extraction method based on compact interval valued intuitionistic fuzzy rules for the classification of news comment pages based on IVFS, for modeling and predicting real-world Sentiment Analysis applications. The web pages are partitioned based on DOM tree, and the emotional tendency of news comments is classified by the improved intuitionistic fuzzy reasoning algorithm. Finally, this method is used to extract news comment web pages. To test the quality of our recommendations, we will present an experimental study that includes a dataset of 9 news pages with comments. We will demonstrate that this method is superior to the original C4.5 decision tree, Type 1 and Region 1, which are preprocessed.5. Decision tree. Type 1 corresponds to the interval value fuzzy and approximates the original fuzzy classifier. Our approach avoids a lot of unnecessary trouble and provides interpretable models that allow for more accurate results.
Research on Slope Patrolling of Intelligent Car Based on Memory Algorithm
Authors: Zhang Yuzhen , Dai Xun
Published: June 2021

There are many problems in the intelligent car driving on the slope, such as pause, tire slip and so on. This system takes msp432p401r single chip microcomputer as the control core, combines with motor differential, photoelectric cell array, and controls through memory algorithm and PID speed control algorithm, designs an intelligent electric car, and realizes the function of ramp driving and accurate stop. At the same time, in the process of experimental analysis, it can memorize the track, extract effective information from various working conditions, and then complete the accurate control System. After the final debugging, the system has realized the effect of non-stop and non-skid driving on the 0-35° slope surface, and can accurately arrive at the parking point and stop at the set time.
Design of An IoT based Smart Parking Lock
Authors: Huang Hongyang , Song Chai , Ting Jin , Tian Taoling , Hong Chen , Di Zhang , Gao Danni
Published: June 2021

In recent years, the rapid growth of vehicles has led to a great increase in the demand for parking spaces, unmanaged car parks makes it difficult to efficiently utilize the limited parking resources. To solve this problem, an intelligent parking lock system based on the Internet of things (IoT) is designed and implemented in this paper. Our design incorporates the IoT technology, such as LORA wireless network, to carry out real-time monitoring of the parking space and offer remote control ability of the parking lock. The application of our smart parking lock includes time sharing rental of parking space. Our design can improve utilization of the parking space and help to ease the problem of parking space shortage.
The Application of Internet Big Data and Support Vector Machine in Risk Warning
Authors: Li Jiang , Tan Yaochen , Zhang Ao
Published: June 2021

With the strengthening of macro-control of the real estate industry and the intensification of market competition, it is of great significance for the steady development of the industry to establish an accurate and effective early-warning mechanism for enterprise financing risk. Taking the A-share real estate listed companies in China in 2019 as target, this paper collects financial information of the relevant companies from 2010 to 2019, supplemented the risk sample data from 2005 to 2010, and reduced classification imbalance by removing discrete points and using SMOTE. When the financing risk evaluation system of listed real estate companies is constructed with capital as the entry point, the stochastic forest algorithm is used to finally select five important characteristic dimensions, namely, current ratio, equity financing ratio, operating income, current liability ratio and receivable turnover ratio. This paper establishes SVM early warning model, PSO-GA-BP optimization model and KNN early warning model to predict financing risks of real estate companies. It is concluded that, by comparing their applicability and advantages and disadvantages, SVM after feature screening and sample processing has better performance in the real estate financing risk early warning, which can provide some references for enterprise decision makers, investors and regulatory authorities.
Research on trusted virtual machine migration based on dynamic exponential smoothing prediction
Authors: Zhuang Xin’an , Yu Xuejun
Published: June 2021

Cloud service centers have the problems such as untrusted virtual machines and frequent untrusted migration caused by instantaneous peak. In this paper, the trusted virtual machine is measured and the dynamic exponential smoothing prediction algorithm is used to filter the migration requests, to ensure that a trusted virtual machine will migrate at the trusted migration time. The trustworthiness of the service level agreement (SLA) for cloud services is maintained, and the efficiency of the utilization of cloud service center resources is improved.
Research on food redistribution model based on principal component analysis and factor analysis
Authors: Zhu Yuhan , Huang Yihuan , Yan Yuhang
Published: June 2021

We have divided rebuilding food systems into two phases, one of which is to maximize productivity in a way that maximizes sustainability and economic benefits. Another is to minimize hunger and food insecurity, with regard to equity. Firstly, we use Euclidean Metri and Complete Connection Method for cluster analysis according to the production efficiency and production structure of various foods. Then the countries are classified into countries with different production structures and productivity. Secondly, we quantified sustainability indicators to make standard deviations and risks to food production. Using models, principal component analysis, and factor analysis, we figure out how to distribute food among countries to maximize food productivity worldwide. Thirdly, the model is used to analyze the coefficient of food insecurity and the degree of hunger in each country, so as to obtain the utility level of food distribution in each country. The level of food utility in developed countries is relatively flat, while that in underdeveloped countries is steeper. So, the utility of food distribution in less developed countries is higher than that in developed countries. Therefore, when we measure the total utility of food, we multiply the utility difference of the insecurity factor by the quantity of food mixture and add the original food utility level to maximize the food utility level.
Intelligent Recognition System for the Curves Trajectory and Track Capture Using Artificial Intelligence Technology
Authors: Yan Li
Published: June 2021

Aiming at the problem of large deviation of the recognition results of the traditional recognition system, this article carried out the design and research of the intelligent recognition system of the football curve ball movement trajectory. The hardware structure design includes the acceleration sensor selection, the angular motion detection device selection and the power supply circuit design, and the software structure design includes the motion trajectory data filtering processing and the football curve ball motion speed displacement recognition. Experiments show that, compared with the traditional system, the design system has a smaller deviation of the recognition results, significantly fewer recognition errors, and higher accuracy.
Study of attitude adjustment and positioning methods for navigational vehicles
Authors: Luo Weichen
Published: June 2021

In recent years, with the development and progress of science and technology, all kinds of water and underwater vehicles have been gradually integrated into all kinds of commercial and civil marine operations, which are self-energy, autonomous control, flexible and convenient, and can be widely used in fish monitoring, population migration, environmental protection, early warning, underwater survey, etc., while better attitude adjustment and positioning methods can effectively promote the promotion of all kinds of submersible vehicles.
Research on the Optimal Calculation Model of Team Cooperative Attack Strategy Based on Intermediate Speed Confrontation Statistics
Authors: Yu Tianbo , Dai Donghui , Zhao Zhenwen , Sun Rui , Hu Wenxin , Li Yan , Cheng Peng , Man Xiaoni
Published: June 2021

With the rapid advancement of the theory of teamwork offensive tactics, this article uses computer mathematical statistics and derives from mathematical computer mathematics. In the combination of tactical characteristics, the penalty area scoring optimization model research, through the use of teamwork is the offense The main form of organization before scoring improved performance, using the mid-speed confrontation empirical formula, and finally through calculation and statistical comparison and analysis, it proved that the middle-speed statistical algorithm has a significant effect, and it explained the calculation of the team cooperation attack tactics to organize the middle-speed confrontation. Statistics play a positive role.
Design of introspective cultural tourism project service platform based on big data
Authors: Feng Fang , Chen Tianxing
Published: June 2021

This paper designs a self-examination platform based on big data, which consists of three layers, introduces the functions of each part of the top-level visual interface, and expounds the dimensions and the realization of the contents of each function module. The Support Algorithm of face recognition and the flow of video clip are introduced. The Support Algorithm and data mining algorithm of face recognition have been verified in practice, and the effect achieves the expected goal. After further improvement, it will be applied to the Chengdu Smart Travel Project, which will play a positive role in promoting the wisdom of Chengdu smart travel.
Research and Application of the Network Learning Platform in Based on Big Data Analysis and Mobile Communication
Authors: Mi Wang , Min Qian
Published: June 2021

With the development of computer information technology, the learning methods of college students have gradually changed, and the Internet-based online learning methods are becoming more and more prosperous. This article uses big data analysis to explore the reasons for the application of the economic management network learning platform in colleges and universities and the impact of these reasons on the learning effect. Finally, some suggestions are put forward for the construction of the network learning platform. The research results not only provide new ideas for the continuous development of online learning platforms, but also have practical guiding significance for the improvement of teaching quality in colleges and universities.
Analysis of the Operating Model on the Existing South Section of Xinyi-Changxing Railway
Authors: Li Mengtian , Yang Rui
Published: June 2021

Operating suburban trains on existing railways has been highly valued in China due to the advantages of activating railway resources, reducing construction costs and improving the overall transportation efficiency. As a result, it is proposed that ‘operating suburban trains on existing railways’ is the key task of improving urban rail transit network. Recently, south section of existing Xinyi-Changxing Railway has experienced low passenger and freight volume, idle capacity and underutilized corridor resources. To take fully advantages of existing railway corridor resource, the study provides 5 schemes to operate suburban trains on the existing south section of Xinyi-Changxing Railway: Scheme A. Operating DMU trains on existing railway; Scheme B. Open reserved stations + operating DMU trains; Scheme C. Open reserved stations + electrification + operating EMU trains; Scheme D. Open reserved stations + electrification + operating EMU trains + increasing designed speed to 160km/h; Scheme E. Electrification + constructing a double track. The study could provide reference for the further research on operating suburban trains on the existing railways.
Research on the Information Entropy Using Processing Square Matrix Method Based on Similarities Evaluation Model
Authors: Cui Chupeng , Jia Zhendong , Gu Ke
Published: June 2021

In the music history, there are plenty of splendid music artists. musicians in a certain genre may bring some varieties other genres, or influenced by them. this paper constructs a complex network model based on directional weighted graph. Specifically, we calculate the edge of the graph by referring the ideology of information entropy to describe the direct influence on two certain artists. Then, we take the 100 most influential artists and analyze their influence to get a direct influence square matrix. After that, we utilize the DEMATEL method to process this square matrix, and calculate the scale of the comprehensive influence square matrix about these musicians. This article uses Euclidean distance as the similarity metric, and measures the similarity between artists through 11 indicators. In order to facilitate the calculation, this paper uses the principal component analysis method to reduce the dimensionality of these indicators. In order to determine the influence relationship between genres, this paper uses the k-means algorithm to compare and analyze the clusters of artists with more than 10 followers.