{"title":"使用模糊多属性决策方法(F-MADM)建模流行病前因之间的相互依赖关系","authors":"Dharyll Prince M. Abellana","doi":"10.1515/comp-2020-0213","DOIUrl":null,"url":null,"abstract":"Abstract With the high incidence of the dengue epidemic in developing countries, it is crucial to understand its dynamics from a holistic perspective. This paper analyzes different types of antecedents from a cybernetics perspective using a structural modelling approach. The novelty of this paper is twofold. First, it analyzes antecedents that may be social, institutional, environmental, or economic in nature. Since this type of study has not been done in the context of the dengue epidemic modelling, this paper offers a fresh perspective on this topic. Second, the paper pioneers the use of fuzzy multiple attribute decision making (F-MADM) approaches for the modelling of epidemic antecedents. As such, the paper has provided an avenue for the cross-fertilization of knowledge between scholars working in soft computing and epidemiological modelling domains.","PeriodicalId":43014,"journal":{"name":"Open Computer Science","volume":"11 1","pages":"305 - 329"},"PeriodicalIF":1.1000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/comp-2020-0213","citationCount":"3","resultStr":"{\"title\":\"Modelling the interdependent relationships among epidemic antecedents using fuzzy multiple attribute decision making (F-MADM) approaches\",\"authors\":\"Dharyll Prince M. Abellana\",\"doi\":\"10.1515/comp-2020-0213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract With the high incidence of the dengue epidemic in developing countries, it is crucial to understand its dynamics from a holistic perspective. This paper analyzes different types of antecedents from a cybernetics perspective using a structural modelling approach. The novelty of this paper is twofold. First, it analyzes antecedents that may be social, institutional, environmental, or economic in nature. Since this type of study has not been done in the context of the dengue epidemic modelling, this paper offers a fresh perspective on this topic. Second, the paper pioneers the use of fuzzy multiple attribute decision making (F-MADM) approaches for the modelling of epidemic antecedents. As such, the paper has provided an avenue for the cross-fertilization of knowledge between scholars working in soft computing and epidemiological modelling domains.\",\"PeriodicalId\":43014,\"journal\":{\"name\":\"Open Computer Science\",\"volume\":\"11 1\",\"pages\":\"305 - 329\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/comp-2020-0213\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/comp-2020-0213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/comp-2020-0213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Modelling the interdependent relationships among epidemic antecedents using fuzzy multiple attribute decision making (F-MADM) approaches
Abstract With the high incidence of the dengue epidemic in developing countries, it is crucial to understand its dynamics from a holistic perspective. This paper analyzes different types of antecedents from a cybernetics perspective using a structural modelling approach. The novelty of this paper is twofold. First, it analyzes antecedents that may be social, institutional, environmental, or economic in nature. Since this type of study has not been done in the context of the dengue epidemic modelling, this paper offers a fresh perspective on this topic. Second, the paper pioneers the use of fuzzy multiple attribute decision making (F-MADM) approaches for the modelling of epidemic antecedents. As such, the paper has provided an avenue for the cross-fertilization of knowledge between scholars working in soft computing and epidemiological modelling domains.