An offer in a fuzzy negotiation model is rejected or accepted by acceptability based on fuzzy set theory and membership functions. Since different issues have different effect on negotiators, the combined concession in the multi-issue negotiation for negotiators and negotiation agents and genetic learning mechanism are adopted to update their beliefs about incomplete information. The fuzzy nego...

lthough fuzzy set theory and  sheaf theory have been developed and studied independently,  Ulrich Hohle shows that a large part of fuzzy set  theory  is in fact a subfield of sheaf theory. Many authors have studied mathematical structures, in particular, algebraic structures, in both  categories of these generalized (multi)sets. Using Hohle's idea, we show that for a (universal) algebra $A$, th...

the paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. some mathematical vector models were obtained for control system multicriterion quality indices with due ...

the ecological potential assessment of forest sites introduces an index or indices that show the potential of forest site for fulfillment of special different roles of forest. khanikan forest at chalous needs precise investigation for assessment as indicator of lowland forests in forest ecosystems of northern iranwith considering its location position in caspian lowland and different values. th...

this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...

By Fuzzy theory we mean Zadeh’s mathematical theory of generalized sets and their associated logics. At this state of the art, fuzzy theory has provided significant contributions to artificial intelligence via a broader umbrella of soft computing. Like other theories of mathematics, such as number theory and potential theory, fuzzy theory has its own agenda, concepts, and techniques. However, j...

The traditional event tree analysis uses a single probability to represent each top event. However, it is unrealistic to evaluate the occurrence of each event by using a crisp value without considering the inherent uncertainty and imprecision a state has. The fuzzy set theory is universally applied to deal with this kind of phenomena. The main purpose of this study is to construct an easy metho...

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of “If..., then...” statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environm...

A genetic algorithm is a stochastic computational model that seeks the optimal solution to an objective function. A methodology calculation is based on the idea of measuring the increase of fitness and fitness quality evaluation with chaos theory principles applying within genetic algorithm environment. Fuzzy neural networks principles are effectively applied in solved manufacturing problems mo...