Soft Methods for Modeling Uncertainty and Imprecision
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".
Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 6251
Special Issue Editors
Interests: dissimilarities; stochastic orders; graph theory; interval-valued fuzzy sets
Interests: information fusion; machine learning; decision making; interval-valued fuzzy set
Special Issue Information
Dear Colleagues,
Fuzzy logic is a widely acknowledged theory that provides a tool to make decisions when imprecision is involved in the procedure. It provides a formal basis that allows machines to approximate human behavior, in the sense that it allows them to mimic the way human beings think and make choices. In classical, or “hard”, computing there is no room for imprecision or uncertainty. Hard computing is therefore not useful in artificial intelligence, where the main objective is to reproduce human reasoning with computers. Soft computing takes advantage of the theoretical ground provided by, among others, fuzzy logic to model decision-making procedures where information or knowledge is incomplete/imprecise. It is therefore a natural alternative to hard computing. A proof of the relevance and reputation of soft computing is the increasing range of application areas of its techniques.
This Special Issue welcomes both theoretical papers and applied contributions, so as to reinforce the necessity of both sides (fuzzy logic and soft computing) of scientific research.
Prof. Dr. Susana Montes
Prof. Dr. Irene Díaz
Dr. Susana Díaz-Vázquez
Guest Editors
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