{"title":"SELECTION OF AGGREGATION OPERATORS FOR A MULTI-CRITERIA EVALUTION OF SUTABILITY OF TERRITORIES","authors":"S. Kuznichenko, I. Buchynska","doi":"10.28925/2663-4023.2019.6.4656","DOIUrl":null,"url":null,"abstract":"The article discusses the issues of improving the adequacy and validity of the results of the convolution of criteria evaluation into a generalized evaluation when conducting a multi-criteria analysis of the land suitability by choosing the appropriate type of aggregation operator that can be performed in the GIS environment and has the properties that allow the most complete formalization of expert knowledge about the features of this applied area. Based on the analysis of the causes of the fuzziness of information in multicriteria decision-making models, the properties that the aggregation operator must have are formulated. A comparative analysis of various aggregation operators for the construction of complex maps of the suitability of territories is carried out. The features of the execution of aggregation operators are investigated: minimum, maximum, arithmetic mean, weighted sum, OWA Yager operator. It is shown that the most justified choice is to use the OWA Yager operator with fuzzy quantifiers, which allows you to provide expert information on the acceptable form of a compromise between evalutions by individual criteria. The use a family of the RIM quantifiers to formalize the attitude of DM to risk in making decisions is proposed. An example of the use of the OWA Yager operator with fuzzy quantifiers for calculating the convolution of criteria evalutions is given. It is shown that the Yager OWA operator with fuzzy quantifiers is a universal aggregation operator, since it has the ability to implement a wide range of decision-making strategies: from minimum operator to maximum operator.","PeriodicalId":198390,"journal":{"name":"Cybersecurity: Education, Science, Technique","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybersecurity: Education, Science, Technique","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28925/2663-4023.2019.6.4656","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article discusses the issues of improving the adequacy and validity of the results of the convolution of criteria evaluation into a generalized evaluation when conducting a multi-criteria analysis of the land suitability by choosing the appropriate type of aggregation operator that can be performed in the GIS environment and has the properties that allow the most complete formalization of expert knowledge about the features of this applied area. Based on the analysis of the causes of the fuzziness of information in multicriteria decision-making models, the properties that the aggregation operator must have are formulated. A comparative analysis of various aggregation operators for the construction of complex maps of the suitability of territories is carried out. The features of the execution of aggregation operators are investigated: minimum, maximum, arithmetic mean, weighted sum, OWA Yager operator. It is shown that the most justified choice is to use the OWA Yager operator with fuzzy quantifiers, which allows you to provide expert information on the acceptable form of a compromise between evalutions by individual criteria. The use a family of the RIM quantifiers to formalize the attitude of DM to risk in making decisions is proposed. An example of the use of the OWA Yager operator with fuzzy quantifiers for calculating the convolution of criteria evalutions is given. It is shown that the Yager OWA operator with fuzzy quantifiers is a universal aggregation operator, since it has the ability to implement a wide range of decision-making strategies: from minimum operator to maximum operator.