Modeling refers to the establishment of a description of a system in mathematical terms, which characterizes the input-output behavior of the underlying system. The process of developing a model under fuzziness is termed fuzzy modeling. Fuzzy logic can provide a promising alternative to mathematical modeling for many physical systems that are too vague or too complicated to be described by simple and crisp mathematical formulas or equations. When fuzzy logic is employed, the interval of confidence and the fuzzy membership functions are used as approximation measures, leading to the so-called fuzzy systems modeling. The Fuzzy Modeling has been applied in a wide variety of fields such as Engineering and Management Sciences and Social Sciences to solve a number decision making problems which involve impreciseness, uncertainty and vagueness in data. Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge.
Fuzzy modeling and decision making in engineering was the name of the special sessions chaired by me at the 9th International FLINS Conference on Foundations and Applications of Computational Intelligence (FLINS2010) in August 2-4, 2010, Chengdu (EMei), China. The papers presented in these special sessions were extended and submitted after the conference for possible publication in this special issue of Journal of Multiple Valued Logic and Soft Computing. After a peer review using at least two referees for each paper, 11 papers included by this issue have been accepted.