{"title":"基于平均压缩熵的疲劳损伤钢桥改造方法选择","authors":"Masaru Minagawa, T. Kamitani","doi":"10.11532/JOURNALAC1992.8.135","DOIUrl":null,"url":null,"abstract":"[ABSTRACT] For the purpose of knowledge discovery, we evaluated average compressed entropies for a case-base virtually constructed through some inferences with the inference system that we proposed for selecting the retrofitting method. It is found from the analyses that the average compressed entropy is an effective measure for the discovery of knowledge that is implicitly buried into dada-bases or case-bases.","PeriodicalId":309334,"journal":{"name":"journal of Civil Engineering Information Processing System","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1999-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Knowledge Discovery using Average Compressed Entropy for selecting retrofitting Method of Steel Bridges Damaged by Fatigue\",\"authors\":\"Masaru Minagawa, T. Kamitani\",\"doi\":\"10.11532/JOURNALAC1992.8.135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"[ABSTRACT] For the purpose of knowledge discovery, we evaluated average compressed entropies for a case-base virtually constructed through some inferences with the inference system that we proposed for selecting the retrofitting method. It is found from the analyses that the average compressed entropy is an effective measure for the discovery of knowledge that is implicitly buried into dada-bases or case-bases.\",\"PeriodicalId\":309334,\"journal\":{\"name\":\"journal of Civil Engineering Information Processing System\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"journal of Civil Engineering Information Processing System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11532/JOURNALAC1992.8.135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"journal of Civil Engineering Information Processing System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11532/JOURNALAC1992.8.135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Knowledge Discovery using Average Compressed Entropy for selecting retrofitting Method of Steel Bridges Damaged by Fatigue
[ABSTRACT] For the purpose of knowledge discovery, we evaluated average compressed entropies for a case-base virtually constructed through some inferences with the inference system that we proposed for selecting the retrofitting method. It is found from the analyses that the average compressed entropy is an effective measure for the discovery of knowledge that is implicitly buried into dada-bases or case-bases.
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