{"title":"神经模糊算法在软件大小估计中的应用研究","authors":"Justin Wong, D. Ho, Luiz Fernando Capretz","doi":"10.1109/WOSQ.2009.5071557","DOIUrl":null,"url":null,"abstract":"Neuro-Fuzzy refers to a hybrid intelligent system using both neural network and fuzzy logic. In this study, neuro-fuzzy is applied to a backfiring and categorical data size estimation model. Evaluation was conducted to determine whether a neuro-fuzzy approach improves software size estimations. It was found that a neuro-fuzzy approach provides minimal improvement over the traditional backfiring sizing technique.","PeriodicalId":158077,"journal":{"name":"2009 ICSE Workshop on Software Quality","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"An investigation of using Neuro-Fuzzy with software size estimation\",\"authors\":\"Justin Wong, D. Ho, Luiz Fernando Capretz\",\"doi\":\"10.1109/WOSQ.2009.5071557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neuro-Fuzzy refers to a hybrid intelligent system using both neural network and fuzzy logic. In this study, neuro-fuzzy is applied to a backfiring and categorical data size estimation model. Evaluation was conducted to determine whether a neuro-fuzzy approach improves software size estimations. It was found that a neuro-fuzzy approach provides minimal improvement over the traditional backfiring sizing technique.\",\"PeriodicalId\":158077,\"journal\":{\"name\":\"2009 ICSE Workshop on Software Quality\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 ICSE Workshop on Software Quality\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSQ.2009.5071557\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 ICSE Workshop on Software Quality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSQ.2009.5071557","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An investigation of using Neuro-Fuzzy with software size estimation
Neuro-Fuzzy refers to a hybrid intelligent system using both neural network and fuzzy logic. In this study, neuro-fuzzy is applied to a backfiring and categorical data size estimation model. Evaluation was conducted to determine whether a neuro-fuzzy approach improves software size estimations. It was found that a neuro-fuzzy approach provides minimal improvement over the traditional backfiring sizing technique.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
