Pub Date : 1900-01-01DOI: 10.1109/ICISCAE55891.2022.9927597
Yanxia Wang
In recent years, the school enrollment scale has expanded explosively, and massive student information data sets have brought a lot of troubles to student information management decision-making. Data mining, especially the continuous optimization of decision tree classification algorithms, can effectively manage student data. Therefore, the study of student information management decision system based on decision tree classification algorithm has practical significance. This paper calculates the decision support degree for attributes that are not easily distinguished, and optimizes the decision tree classification algorithm. This article will introduce the modules of student registration management, student status management, examination management and so on in the optimized decision tree classification algorithm application system. In order to verify the feasibility of the system, this article tested and used the basic functions of the system. The test results show that when the number of concurrent users is 100, the actual response time of the system is 0.43s; when the number of concurrent users is 600, the actual response time of the system is 1.56s, which is less than 2s, which verifies that the system functions have reached the expected use effect.
{"title":"Student Information Management Decision System Based on Decision Tree Classification Algorithm","authors":"Yanxia Wang","doi":"10.1109/ICISCAE55891.2022.9927597","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927597","url":null,"abstract":"In recent years, the school enrollment scale has expanded explosively, and massive student information data sets have brought a lot of troubles to student information management decision-making. Data mining, especially the continuous optimization of decision tree classification algorithms, can effectively manage student data. Therefore, the study of student information management decision system based on decision tree classification algorithm has practical significance. This paper calculates the decision support degree for attributes that are not easily distinguished, and optimizes the decision tree classification algorithm. This article will introduce the modules of student registration management, student status management, examination management and so on in the optimized decision tree classification algorithm application system. In order to verify the feasibility of the system, this article tested and used the basic functions of the system. The test results show that when the number of concurrent users is 100, the actual response time of the system is 0.43s; when the number of concurrent users is 600, the actual response time of the system is 1.56s, which is less than 2s, which verifies that the system functions have reached the expected use effect.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126263300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE55891.2022.9927575
Yabin Liu
With the continuous development of economy and society and changes in external factors such as science and technology, human resource management practices are not only strengthening the management of cooperative and coordinated relationships, but also gradually analyzing the influence of personality traits on job performance. Therefore, based on machine learning technology, this paper designs a human resource matching system based on trust propensity, which can effectively improve the operational efficiency of enterprises, reduce the cost of employment and employee selection, and reduce the cost of communication between individuals and organizations, and provide a software tool and practical suggestions for human resource management of enterprises. software tools and practical suggestions for HRM.
{"title":"Research on human resource matching system based on collaborative filtering algorithm and trust propensity matching","authors":"Yabin Liu","doi":"10.1109/ICISCAE55891.2022.9927575","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927575","url":null,"abstract":"With the continuous development of economy and society and changes in external factors such as science and technology, human resource management practices are not only strengthening the management of cooperative and coordinated relationships, but also gradually analyzing the influence of personality traits on job performance. Therefore, based on machine learning technology, this paper designs a human resource matching system based on trust propensity, which can effectively improve the operational efficiency of enterprises, reduce the cost of employment and employee selection, and reduce the cost of communication between individuals and organizations, and provide a software tool and practical suggestions for human resource management of enterprises. software tools and practical suggestions for HRM.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121751729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE55891.2022.9927683
Hong Qu, Xiaolong Wei, Chuhan Sun, Xinze Li
Aiming at the autonomous maneuver decision-making problem of UAV air combat, a lateral maneuver decision-making algorithm is designed. By adding heuristic factors and double Q-table alternating learning mechanism, the defects of slow learning speed and more ineffective learning in traditional Q-learning algorithm are improved. Through the comparison of path planning simulation and data, it is verified that the improved Q-learning algorithm has better stability and solving ability. it is verified that the improved Q-learning algorithm can play a significant role in improving the winning / losing ratio of UAV air combat through the exchange of weapon platforms.
{"title":"Research on UAV Air Combat Maneuver Decision-making Based on Improved Q-learning Algorithm","authors":"Hong Qu, Xiaolong Wei, Chuhan Sun, Xinze Li","doi":"10.1109/ICISCAE55891.2022.9927683","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927683","url":null,"abstract":"Aiming at the autonomous maneuver decision-making problem of UAV air combat, a lateral maneuver decision-making algorithm is designed. By adding heuristic factors and double Q-table alternating learning mechanism, the defects of slow learning speed and more ineffective learning in traditional Q-learning algorithm are improved. Through the comparison of path planning simulation and data, it is verified that the improved Q-learning algorithm has better stability and solving ability. it is verified that the improved Q-learning algorithm can play a significant role in improving the winning / losing ratio of UAV air combat through the exchange of weapon platforms.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590730
Hong Zhang, Wentao Mao, Ying Tang, Guorong Wang
The power system is more reliable and safe, improve the quality of power supply. In order to promote the integration of massive information and energy security in the environment of energy Internet, the core technology of large data smart grid based on grid operation simulation is proposed. In the era of power large data, with the increasing demand for information collection and screening, information communication system has become an important application system of smart grid. The application of large data core technology can help. The development of various fields provides key information to meet the needs of current social development, and promotes the development of power grid planning and construction and service industry.
{"title":"Research on Key Technologies of Large Data Smart Grid Based on Power Grid Operation Simulation","authors":"Hong Zhang, Wentao Mao, Ying Tang, Guorong Wang","doi":"10.1109/ICISCAE52414.2021.9590730","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590730","url":null,"abstract":"The power system is more reliable and safe, improve the quality of power supply. In order to promote the integration of massive information and energy security in the environment of energy Internet, the core technology of large data smart grid based on grid operation simulation is proposed. In the era of power large data, with the increasing demand for information collection and screening, information communication system has become an important application system of smart grid. The application of large data core technology can help. The development of various fields provides key information to meet the needs of current social development, and promotes the development of power grid planning and construction and service industry.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127032488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590723
Jin Huang, Yamin Fang
CNC machine tool is the basic equipment for the development of high-tech industry and high-tech industry. Feed servo system is an important part of CNC system. The matching of drive control parameters is related to the performance of NC system. Servo drive system is an important part of CNC system. Under the same mechanical properties, the matching degree of servo parameters and mechanical properties determines the machining accuracy and quality of the machine tool. Therefore, how to match parameters quickly and effectively has always been the focus of research. A fuzzy adaptive PID controller combining fuzzy control and PID control is designed and applied to the control of NC servo system. The controller has good control performance. The simulation data show that the fuzzy adaptive PID controller has good accuracy and strong robustness.
{"title":"Design of CNC Feed Servo System Based on Fuzzy PID","authors":"Jin Huang, Yamin Fang","doi":"10.1109/ICISCAE52414.2021.9590723","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590723","url":null,"abstract":"CNC machine tool is the basic equipment for the development of high-tech industry and high-tech industry. Feed servo system is an important part of CNC system. The matching of drive control parameters is related to the performance of NC system. Servo drive system is an important part of CNC system. Under the same mechanical properties, the matching degree of servo parameters and mechanical properties determines the machining accuracy and quality of the machine tool. Therefore, how to match parameters quickly and effectively has always been the focus of research. A fuzzy adaptive PID controller combining fuzzy control and PID control is designed and applied to the control of NC servo system. The controller has good control performance. The simulation data show that the fuzzy adaptive PID controller has good accuracy and strong robustness.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126943464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590644
Ronghua Chen, Beibei Yang
With the comprehensive development of Internet technology, web data mining technology has achieved rapid development and is widely used in various industries. Cloud computing is a new method of sharing infrastructure, which is based on open standards and services and centered on the Internet, providing safe, fast and convenient data storage and network computing services. Cloud computing has strong information storage capacity, high security and high level of data processing and analysis. As an indispensable part of storage technology, the application level of cloud computing technology has been improved, effectively ensuring the quality and efficiency of data preservation. By analyzing the characteristics of Web data mining technology in cloud computing environment, we can realize the breakthrough of cloud computing in data storage and improve the storage capacity and security. This paper analyzes the Web data mining algorithm in the cloud computing environment, improves the accuracy and effectiveness of data mining, and uses the cloud computing environment to improve the Web data mining strategy, thus laying the foundation for the healthy development of China's Internet.
{"title":"Research on Web Data Mining Strategy Based on Cloud Computing","authors":"Ronghua Chen, Beibei Yang","doi":"10.1109/ICISCAE52414.2021.9590644","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590644","url":null,"abstract":"With the comprehensive development of Internet technology, web data mining technology has achieved rapid development and is widely used in various industries. Cloud computing is a new method of sharing infrastructure, which is based on open standards and services and centered on the Internet, providing safe, fast and convenient data storage and network computing services. Cloud computing has strong information storage capacity, high security and high level of data processing and analysis. As an indispensable part of storage technology, the application level of cloud computing technology has been improved, effectively ensuring the quality and efficiency of data preservation. By analyzing the characteristics of Web data mining technology in cloud computing environment, we can realize the breakthrough of cloud computing in data storage and improve the storage capacity and security. This paper analyzes the Web data mining algorithm in the cloud computing environment, improves the accuracy and effectiveness of data mining, and uses the cloud computing environment to improve the Web data mining strategy, thus laying the foundation for the healthy development of China's Internet.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"6 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114110103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the low accuracy of traditional anti-stealing prediction methods, this paper proposes an anti-stealing prediction method based on power big data. The method constructs electricity stealing data samples according to abnormal rules, and introduces the constraint condition of line loss rate growth rate. This paper classifies the user's load data, proposes four indicators to measure the load curve, and obtains the characteristic variables. On the basis of classification, the extracted feature variables are dimensionally reduced, and local outlier factors are used to screen out users with abnormal electricity consumption. The method uses the maximum mutual information coefficient to measure the correlation between the management line loss and the specific behavior of users, and uses CFSFDP to locate abnormal electricity users, which has strong applicability and can detect many different types of electricity stealing behaviors. Finally, the algorithm is verified using the smart meter dataset, and the results demonstrate the good performance of the method.
{"title":"Application Research of Computer Machine Learning Algorithm in Anti-theft Analysis under Smart Grid","authors":"Runnian Wang, Zhishang Duan, Xiangyi Ge, Jianwen Zhang","doi":"10.1109/ICISCAE55891.2022.9927579","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927579","url":null,"abstract":"Aiming at the low accuracy of traditional anti-stealing prediction methods, this paper proposes an anti-stealing prediction method based on power big data. The method constructs electricity stealing data samples according to abnormal rules, and introduces the constraint condition of line loss rate growth rate. This paper classifies the user's load data, proposes four indicators to measure the load curve, and obtains the characteristic variables. On the basis of classification, the extracted feature variables are dimensionally reduced, and local outlier factors are used to screen out users with abnormal electricity consumption. The method uses the maximum mutual information coefficient to measure the correlation between the management line loss and the specific behavior of users, and uses CFSFDP to locate abnormal electricity users, which has strong applicability and can detect many different types of electricity stealing behaviors. Finally, the algorithm is verified using the smart meter dataset, and the results demonstrate the good performance of the method.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117142047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590796
Jizhou Lu, J. Rao, Ran Hu, Wen Yu, Xuncan Zhu
In recent years, the rapid development of industrialization and urbanization has led to the continuous growth of energy consumption. Economic and social development is facing severe dual constraints of resources and environment. Energy conservation and emission reduction has become an extremely urgent task at present. As a large energy consumer, the energy-saving effect of the power industry plays an important role in achieving the overall consumption reduction goal. In order to improve the reliability of power supply and ensure users' power consumption experience, uninterrupted operation technology is increasingly introduced into the operation and maintenance of distribution network. According to the actual demand of energy saving and loss reduction, this paper puts forward the research based on low voltage does not power cut operation refined collection of line loss data in distribution network. Combined with the network topology of the line, the measurement data collected by the line is extracted from the measurement automation system to calculate the line loss. The proposed method comprehensively considers the real-time comprehensiveness of data acquisition, and the calculated output results are fine and rich, which can reflect the actual loss of the line more truly.
{"title":"Research on Low Voltage Does not Power Cut Operation Refined Collection of Line Loss Data in Distribution Network","authors":"Jizhou Lu, J. Rao, Ran Hu, Wen Yu, Xuncan Zhu","doi":"10.1109/ICISCAE52414.2021.9590796","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590796","url":null,"abstract":"In recent years, the rapid development of industrialization and urbanization has led to the continuous growth of energy consumption. Economic and social development is facing severe dual constraints of resources and environment. Energy conservation and emission reduction has become an extremely urgent task at present. As a large energy consumer, the energy-saving effect of the power industry plays an important role in achieving the overall consumption reduction goal. In order to improve the reliability of power supply and ensure users' power consumption experience, uninterrupted operation technology is increasingly introduced into the operation and maintenance of distribution network. According to the actual demand of energy saving and loss reduction, this paper puts forward the research based on low voltage does not power cut operation refined collection of line loss data in distribution network. Combined with the network topology of the line, the measurement data collected by the line is extracted from the measurement automation system to calculate the line loss. The proposed method comprehensively considers the real-time comprehensiveness of data acquisition, and the calculated output results are fine and rich, which can reflect the actual loss of the line more truly.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123632632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590782
Rui Gu, Wei Li
Based on the grey prediction GM(1,1) model, the monthly mean temperature in Shenzhen China in 2020 is predicted by selecting 7 years' meteorological data. The monthly mean temperature in 2020 is verified by known temperature data in the first 11 months from data open platform. Then the prediction model was verified by residual test, correlation test and posteriori test. The results showed that the model has higher accuracy and can accurately reflect the actual situation.
{"title":"Temperature Prediction Using Gray Model Based on Data Open Platform","authors":"Rui Gu, Wei Li","doi":"10.1109/ICISCAE52414.2021.9590782","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590782","url":null,"abstract":"Based on the grey prediction GM(1,1) model, the monthly mean temperature in Shenzhen China in 2020 is predicted by selecting 7 years' meteorological data. The monthly mean temperature in 2020 is verified by known temperature data in the first 11 months from data open platform. Then the prediction model was verified by residual test, correlation test and posteriori test. The results showed that the model has higher accuracy and can accurately reflect the actual situation.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129364774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590803
Z. Tang
through the characteristic analysis of electronically controlled diesel engine and electronically controlled pump, the control strategy to reasonably match the power of the whole power system is explored. Based on the typical working conditions of the electronically controlled diesel engine, the power matching method under different working conditions is adopted, and the power mode is divided into five gears. Under various modes, the working conditions are refined and the corresponding speed gears are set, so that the electronically controlled diesel engine can adapt to the load change within the whole speed range, facilitate the operation of the engine and maintain the best power utilization.
{"title":"Research on Power Matching of Excavator's Electronically Controlled Diesel Engine and Electronically Controlled Hydraulic Pump under Different Working Conditions","authors":"Z. Tang","doi":"10.1109/ICISCAE52414.2021.9590803","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590803","url":null,"abstract":"through the characteristic analysis of electronically controlled diesel engine and electronically controlled pump, the control strategy to reasonably match the power of the whole power system is explored. Based on the typical working conditions of the electronically controlled diesel engine, the power matching method under different working conditions is adopted, and the power mode is divided into five gears. Under various modes, the working conditions are refined and the corresponding speed gears are set, so that the electronically controlled diesel engine can adapt to the load change within the whole speed range, facilitate the operation of the engine and maintain the best power utilization.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124521886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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