{"title":"基于神经网络的大学体育教学质量评价研究","authors":"B. Hu","doi":"10.1109/ICSGEA.2017.155","DOIUrl":null,"url":null,"abstract":"In the process of establishing evaluation index system of physical education, the traditional methods setting weights for each indicator mainly include analytic hierarchy process, fuzzy comprehensive evaluation method, and Delphi method, etc. These methods mostly rely on experience, which is strongly influenced by artificial factors and cannot be avoided. Because artificial neural network model has the ability of highly nonlinear function mapping, it is applied to the teaching quality evaluation system of physical education. Besides, the weight value of neural network is optimized by genetic algorithm. The experiment results show that the proposed scheme is feasible.","PeriodicalId":326442,"journal":{"name":"2017 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Teaching Quality Evaluation Research Based on Neural Network for University Physical Education\",\"authors\":\"B. Hu\",\"doi\":\"10.1109/ICSGEA.2017.155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the process of establishing evaluation index system of physical education, the traditional methods setting weights for each indicator mainly include analytic hierarchy process, fuzzy comprehensive evaluation method, and Delphi method, etc. These methods mostly rely on experience, which is strongly influenced by artificial factors and cannot be avoided. Because artificial neural network model has the ability of highly nonlinear function mapping, it is applied to the teaching quality evaluation system of physical education. Besides, the weight value of neural network is optimized by genetic algorithm. The experiment results show that the proposed scheme is feasible.\",\"PeriodicalId\":326442,\"journal\":{\"name\":\"2017 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSGEA.2017.155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Smart Grid and Electrical Automation (ICSGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGEA.2017.155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Teaching Quality Evaluation Research Based on Neural Network for University Physical Education
In the process of establishing evaluation index system of physical education, the traditional methods setting weights for each indicator mainly include analytic hierarchy process, fuzzy comprehensive evaluation method, and Delphi method, etc. These methods mostly rely on experience, which is strongly influenced by artificial factors and cannot be avoided. Because artificial neural network model has the ability of highly nonlinear function mapping, it is applied to the teaching quality evaluation system of physical education. Besides, the weight value of neural network is optimized by genetic algorithm. The experiment results show that the proposed scheme is feasible.