{"title":"一种利用模糊认知地图进行葡萄栽培和酿酒的新数学建模方法","authors":"Vasilios P. Groumpos, K. Biniari, P. Groumpos","doi":"10.1109/ELEKTRO.2016.7512035","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to present a new approach in modelling wine quality and quantity using Fuzzy Cognitive Maps trained by non linear Hebbian learning algorithm. The methodology described extracts the knowledge from the experts and exploits their experience on wine production. Two case studies with data from real vineyards were examined. The results of this study show that software tools using Fuzzy Cognitive Maps could be explored further and problems that arise during the wine production could be prevented by an efficient decision support system.","PeriodicalId":369251,"journal":{"name":"2016 ELEKTRO","volume":"235 1-2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A new mathematical modelling approach for viticulture and winemaking using fuzzy cognitive maps\",\"authors\":\"Vasilios P. Groumpos, K. Biniari, P. Groumpos\",\"doi\":\"10.1109/ELEKTRO.2016.7512035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to present a new approach in modelling wine quality and quantity using Fuzzy Cognitive Maps trained by non linear Hebbian learning algorithm. The methodology described extracts the knowledge from the experts and exploits their experience on wine production. Two case studies with data from real vineyards were examined. The results of this study show that software tools using Fuzzy Cognitive Maps could be explored further and problems that arise during the wine production could be prevented by an efficient decision support system.\",\"PeriodicalId\":369251,\"journal\":{\"name\":\"2016 ELEKTRO\",\"volume\":\"235 1-2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 ELEKTRO\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELEKTRO.2016.7512035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 ELEKTRO","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELEKTRO.2016.7512035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new mathematical modelling approach for viticulture and winemaking using fuzzy cognitive maps
The aim of this paper is to present a new approach in modelling wine quality and quantity using Fuzzy Cognitive Maps trained by non linear Hebbian learning algorithm. The methodology described extracts the knowledge from the experts and exploits their experience on wine production. Two case studies with data from real vineyards were examined. The results of this study show that software tools using Fuzzy Cognitive Maps could be explored further and problems that arise during the wine production could be prevented by an efficient decision support system.
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