Multicriteria decision-making (MCDM) problems often involve a complex decision process in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. The existing approaches for solving this problem in a fuzzy environment are complex. Combining the concepts of grey relation and pairwise comparison, a new fuzzy MCDM method is proposed. First, the fuzzy an...

Hormone secretion is an intrinsically discontinuous process characterized by a pul-satile pattern. In this paper we describe a fuzzy deconvolution method for pulsatile hormone secretion signals. The secretion signal is modeled as a Poisson process. The fuzzy deconvolution method is based on fuzzy identiication by using learning signals, mountain clustering and optimal output predefuzziication. ...

This paper presents a layer-structured fuzzy neural network (FNN) for learning rules of fuzzy-logic control systems. Initially, FNN is constructed to contain all the possible fuzzy rules. We propose a two-phase learning procedure for this network. The first phase is a error-backprop (EBP) training, and the second phase is a rule pruning. Since some functions of the nodes in the FNN have the com...

Fuzzy time series techniques are more suitable than traditional time series techniques in forecasting problems with linguistic values. Two shortcomings of existing fuzzy time series forecasting techniques are they lack persuasiveness in dealing with recurrent number of fuzzy relationships and assigning weights to elements of fuzzy rules in the defuzzification process. In this paper, a novel fuz...

ln a fuzzy relational database where a relation is atuzzy sel of tuples and ill-known data are represented by possibility distributions, nested fuzzy queries can be expressed in lhe Fuzzy SQL language, as defined in [25], [23]. Although it provides a very convenient way for users to express complex queries, a nested fuzzy query may be very inefficient to process with the naive evaluation method...

Statistical Quality Control is a valuable strategy that applies to the statistical technique for monitoring manufacturing system under particular situations. On other hand, fuzzy set theory an ideal instrument cope with unclear situation. The existing studies are restricted, and there still mystery behind data. This paper deals technique: namely, control chart based on process capability indice...

In this paper, the computationally intelligent modeling approach for fluidized bed combustion process is considered, as well as intelligent process control based on developed models and soft computing methodologies. Applied genetic optimization and fuzzy modeling approach are combined with proposed intelligent control strategies. Efficient fuzzy nonlinear FBC process modeling by combining sever...

In the present paper Fuzzy process, similar to a stochastic process is carried out for reliability analysis of the network modeling. Classical reliability analysis carries out the probability and binary state assumption which has been found to be inadequate to handle uncertainties of failure data and modeling. In the present paper we have attempted to review the fuzzy tools when dealing with re...

This paper proposes a two-stage fuzzy logarithmic preference programming with multi-criteria decisionmaking, in order to derive the priorities of comparison matrices in the analytic hierarchy pprocess (AHP) and the analytic network process (ANP). The Fuzzy Preference Programming (FPP) proposed by Mikhailov and Singh [L. Mikhailov, M.G. Singh, Fuzzy assessment of priorities with application to c...

In general, high-speed network traffic is a complex, nonlinear, nonstationary process and is significantly affected by immeasurable parameters and variables. Thus, a precise model of this process becomes increasingly difficult as the complexity of the process increases. Recently, fuzzy modeling has been found to be a powerful method to effectively describe a real, complex, and unknown process w...