We can obtain a conservative risk value, a venture risk value and a maximum probability risk value. Under such an level, three risk values can be calculated. As adopts all values throughout the set [0, 1], it is possible to obtain a series of risk values. Therefore, the fuzzy risk can be a multi-valued risk or set-valued risk. Calculation of the fuzzy expected value of landfall typhoon risk in ...

an orthogonal approach to the fuzzification of both multisets and hybridsets is presented. in particular, we introduce $l$-multi-fuzzy and$l$-fuzzy hybrid sets, which are general enough and in spirit with thebasic concepts of fuzzy set theory. in addition, we study the properties ofthese structures. also, the usefulness of these structures is examined inthe framework of mechanical multiset proc...

The solid transportation problem considers the supply, the demand and the conveyance satisfying the transportation requirement in a cost-effective manner. This paper develops a method that is able to derive the fuzzy objective value of the fuzzy solid transportation problem when the cost coefficients, the supply and demand quantities, conveyance capacities are fuzzy numbers and additional const...

This paper expresses the prominent features of the fuzzy expert system by applying the algorithm Fuzzy Assessment Methodology using K ratio. To diagnosis the diabetes Fuzzy Assessment Methodology using k ratio is developed. Fuzzy Expert System consists of following elements such as Fuzzification interface, Fuzzy Assessment Methodology using K ratio and Defuzzification interface. The crisp value...

Fuzzy measures are a generalization of probability measures for which additivity is removed and monotonicity is imposed instead. These measures have become a powerful tool in Decision Theory (see e.g. 12, the work of Schmeidler 21 and 3); moreover, the Choquet Expected Utility model generalizes the Expected Utility one, and this model offers a simple theoretical foundation for explaining phenom...

VHDL high level modelling and implementaiton of fuzzy systems p. 11 Some complexity results on fuzzy description logics p. 19 An evolutionary approach to ontology-based user model acquisition p. 25 Mathematical modeling of passage dynamic function p. 33 Bi-monotonic fuzzy sets lead to optimal fuzzy interfaces p. 39 Conversational agent model in intelligent user interface p. 46 A fuzzy frame-bas...

12 Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from 13 argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-lan14 guage level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot 15 be expressed in the object la...

in this paper the solution of a second order linear dierential equations with intu-itionistic fuzzy boundary value is described. it is discussed for two dierent cases: coecientis positive crisp number and coecient is negative crisp number. here fuzzy numbers aretaken as generalized trapezoidal intutionistic fuzzy numbers (gtrifns). further a numericalexample is illustrated.