Shiwei Zhu, Yanqing Zhao, Junfeng Yu, Lei Wang, Moji Wei, Aiping Wang
{"title":"基于模糊神经网络的数字资源服务绩效评价","authors":"Shiwei Zhu, Yanqing Zhao, Junfeng Yu, Lei Wang, Moji Wei, Aiping Wang","doi":"10.1109/GrC.2012.6468638","DOIUrl":null,"url":null,"abstract":"This paper is innovatively to develop a new hybrid performance evaluation method in the literature of assessing the digital resources serving performances. The proposed method employs the hierarchical evaluation method based on fuzzy rules and artificial neural networks. The proposed method integrates the fuzzy logic and the artificial neural networks, which overcomes the shortcomings of redundant fuzzy rules. The evaluation index system is determined based on the universal principle and the research fruits of the former scholars home and abroad. We build a fuzzy neural network evaluation model to achieve the final evaluation goal of the digital resources. In addition, to evaluate the performance of the proposed approach, we compare its results with GRA-BPN model. The experimental results demonstrated that the proposed approach has higher accuracy and execution efficiency.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital resources serving performance assessing based on fuzzy neural networks\",\"authors\":\"Shiwei Zhu, Yanqing Zhao, Junfeng Yu, Lei Wang, Moji Wei, Aiping Wang\",\"doi\":\"10.1109/GrC.2012.6468638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is innovatively to develop a new hybrid performance evaluation method in the literature of assessing the digital resources serving performances. The proposed method employs the hierarchical evaluation method based on fuzzy rules and artificial neural networks. The proposed method integrates the fuzzy logic and the artificial neural networks, which overcomes the shortcomings of redundant fuzzy rules. The evaluation index system is determined based on the universal principle and the research fruits of the former scholars home and abroad. We build a fuzzy neural network evaluation model to achieve the final evaluation goal of the digital resources. In addition, to evaluate the performance of the proposed approach, we compare its results with GRA-BPN model. The experimental results demonstrated that the proposed approach has higher accuracy and execution efficiency.\",\"PeriodicalId\":126161,\"journal\":{\"name\":\"IEEE International Conference on Granular Computing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Granular Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GrC.2012.6468638\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Granular Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GrC.2012.6468638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital resources serving performance assessing based on fuzzy neural networks
This paper is innovatively to develop a new hybrid performance evaluation method in the literature of assessing the digital resources serving performances. The proposed method employs the hierarchical evaluation method based on fuzzy rules and artificial neural networks. The proposed method integrates the fuzzy logic and the artificial neural networks, which overcomes the shortcomings of redundant fuzzy rules. The evaluation index system is determined based on the universal principle and the research fruits of the former scholars home and abroad. We build a fuzzy neural network evaluation model to achieve the final evaluation goal of the digital resources. In addition, to evaluate the performance of the proposed approach, we compare its results with GRA-BPN model. The experimental results demonstrated that the proposed approach has higher accuracy and execution efficiency.