Application of fuzzy logic to the design of decision support systems for the evaluation of wind energy investments

Skikos, GD; Machias, AV; Kazantzis, C

dc.contributor.author	Skikos, GD	en
dc.contributor.author	Machias, AV	en
dc.contributor.author	Kazantzis, C	en
dc.date.accessioned	2014-03-01T01:43:36Z
dc.date.available	2014-03-01T01:43:36Z
dc.date.issued	1995	en
dc.identifier.issn	0309524X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24164
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0029412829&partnerID=40&md5=b90d442b883e361c96e9a3f17eb9e54a	en
dc.subject.other	Algorithms	en
dc.subject.other	Decision making	en
dc.subject.other	Decision support systems	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Heuristic methods	en
dc.subject.other	Mathematical operators	en
dc.subject.other	Membership functions	en
dc.subject.other	Systems analysis	en
dc.subject.other	Decision criteria	en
dc.subject.other	Fuzzy decision index	en
dc.subject.other	Wind energy investments	en
dc.subject.other	Wind power	en
dc.subject.other	Decision Support Systems	en
dc.subject.other	Fuzzy Reasoning	en
dc.subject.other	Investment Evaluation	en
dc.subject.other	Wind Power	en
dc.title	Application of fuzzy logic to the design of decision support systems for the evaluation of wind energy investments	en
heal.type	journalArticle	en
heal.publicationDate	1995	en
heal.abstract	In this paper, an innovative multiple objective approach to the problem of wind energy investments evaluation is outlined and step by step developed. The proposed methodology is based on the fuzzy set theory, which is a very powerful tool to manipulate quantitative and qualitative concepts and information in a way very similar to human reasoning. The fuzzy algorithm for the evaluation of wind energy investments makes use of a set of economic, environmental and personal decision criteria, fuzzified by means of appropriate, heuristically defined membership functions. The final fuzzy evaluation decision index, which expresses the overall merit of the proposed wind energy investments, can be applied to rank and classify them, in an ascending or descending order. The higher the fuzzy decision index is, the more promising the wind energy investment. This index is computed by aggregating the decision criteria, making use of the Zimmermann-Zysno λ fuzzy aggregation operator. The proposed fuzzy logic methodology can be easily implemented to a computer decision support system, enabling the decision-maker to make faster and more reliable evaluation of investments in wind energy, especially nowadays when the legislation in most European countries encourages and subsidizes private investment projects in this field.	en
heal.publisher	Multi-Science Publishing Co, Ltd, Brentwood, United Kingdom	en
heal.journalName	Wind Engineering	en
dc.identifier.volume	19	en
dc.identifier.issue	6	en
dc.identifier.spage	371	en
dc.identifier.epage	395	en