bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review on plasma diagnosis technology of pulsed plasma thruster
Authors: Zhao Yuanzheng , Wu Jianjun 
Published: June 2021

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.
Research on Basic Programming System of Computer Science Mobile APP Software Engineering
Authors: Wang Haoran 
Published: June 2021

Abstract
With the continuous development of computer network technology and the large-scale popularization of smart phones, mobile phone palm technology has also ushered in a golden period of rapid development. The development and use of mobile terminals provide a broad and convenient stage for the development of APP technology applications. Based on Android phones, the development and application of mobile phone APP software can effectively improve development efficiency, promote some development activities not to be restricted by time and space, improve the flexibility of the development system, and meet the development needs of the new era. Based on this, this article deeply analyzes the background of developing Android mobile phone APP software on the computer basis, from the aspects of hardware, software and operation, detailed research on software development and application, promotes the popularization of related mobile phone software technology and product promotion, and develops mobile phones for the construction of computers. The APP mode laid the foundation.
Design of multi-robot system based on target detection
Authors: Wu Zongyuan 
Published: June 2021

Abstract
Traditional target-following robots are not only easy to lose targets, but also unable to solve all kinds of unexpected situations in time. Based on the above problems, this paper designs a multi-robot following system based on target recognition. The system can complete the task of target following through image recognition and processing and PID algorithm control. While completing target following, it can also complete the cooperative control of multi-robots by constructing local networks among robot systems, which makes the system have better processing ability for various situations. After experimental tests, the robot system has higher following robustness and practical value.
Time-varying formation control for unmanned intelligent vehicle (UIV) with mobile reference center
Authors: Zheng Yinan 
Published: June 2021

Abstract
This paper studies a time-varying formation control algorithm based on the unmanned intelligent vehicle (UIV) system. First, modeling the multi-agent system. Reference [4] gives the time-varying formation control algorithm of multi-agent under changing communication topology and necessary and sufficient conditions for the establishment of the algorithm. The simulation verifies the effectiveness of the algorithm. On this foundation, based on the consensus theory, this paper proposes a formation algorithm in the case of a formation reference center movement and realizes multiple time-varying formations of a multi-agent system through simulation. The simulation results show that the algorithm proposed in this paper can quickly realize formation under different formation requirements and the algorithm has better control effect and robustness.
Improved NSGA-II Algorithm for multi-objective flexible job shop scheduling problem
Authors: Dai Yutong 
Published: June 2021

Abstract
In order to solve the problems such as poor diversity and poor convergence ability of the offspring population of the NSGA-II Algorithm in the vehicle production scheduling problem, an improved shop scheduling algorithm based on NSGA-II is proposed. The improved NSGA-ii Algorithm mainly focuses on the crossover and mutation of the traditional NSGA-II Algorithm, and proposes a new improved self-adaptive Crossover and mutation operator. By comparing the individual crowding degree with the average crowding degree of the population, and combining the iterative evolution process of the population, in order to avoid blind orientation and to improve the convergence speed of the population, the genetic probability is correlated with the individuals and the evolution iteration times of the population, and a new uniform evolution strategy is proposed to select the individuals of the population through adaptive hierarchical selection, in order to improve the quality of the solution, the problem of the poor diversity of the offspring population was solved. The improved NSGA-II Algorithm is used to carry out the experimental simulation analysis. The effectiveness of the proposed algorithm is verified by comparing the optimization results before and after the improvement.
An Improved genetic algorithm for solving TSP
Authors: Tao Shuaihan 
Published: June 2021

Abstract
An improved genetic algorithm is proposed to solve the traveling salesman problem. On the basis of traditional genetic algorithm, greedy algorithm is introduced to initialize the population. The genetic parameters are adjusted adaptively from two aspects of genetic evolution algebra and individual fitness function value, which can speed up the optimization speed and prevent the optimization from falling into local optimum. In mutation operation, adaptive algorithm is used to select mutation operator to improve the quality of variation and search effect of the algorithm; after individual evolution, one-way evolutionary reversal operation is introduced to improve the chance of inheriting parent and parent genes, and improve the ability of algorithm to search for optimal solution.