Although the equivalence between fuzzy and neural systems is considered in various aspects depending on the context, the real implication however, of this equivalence is not explicitly addressed. As result of this, unless one is expert on both the fuzzy logic and neural network fields, there is no clear indication what circumstances prevail to implement any of them. The aim of this paper is to ...

In real applications, information is often imprecise and vague. Exact information has become an essential part of modern database applications for making next generation information systems more human friendly. Fuzzy techniques have been widely used to represent such vague information in various database models and theories. Because of the efficiency of object oriented databases in handling com...

Fuzzy cognitive map is a powerful modeling tool. It has several desirable properties on control. In this paper, we utilize the feature and the inference mechanism of fuzzy cognitive map, and present a control method, which study combines control theory with fuzzy cognitive map theory. The causal relationship of variables is constructed by online learning or offline learning, the values of contr...

Fuzzy modeling has become very popular because of its main feature being the ability to assign meaningful linguistic labels to the fuzzy sets in the rule base. This paper examines Sugeno and Yasukawa’s qualitative modeling approach, and addresses one of the remarks in the original paper. We propose a cluster search algorithm that can be used to provide a better projection of the output space to...

the oxidative coupling of methane (ocm) performance over na-w-mn/sio2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (anfis) using reaction data gathered in an isothermal fixed bed microreactor. in the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (ghsv), and reaction temperature were conside...

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...

Fuzzy linear programming problem occur in many elds such as mathematical modeling, Control theory and Management sciences, etc. In this paper we focus on a kind of Linear Programming with fuzzy numbers and variables namely Fully Fuzzy Linear Programming (FFLP) problem, in which the constraints are in inequality forms. Then a new method is proposed to ne the fuzzy solution for solving (FFLP). Nu...

Representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. Fo-cusing on discounted cash flow analysis numerical results are presented, comparisons are made between alter-native modeling methods, and characteristics of the methods are discussed.

The paper presents a study upon the possibility to use adaptive-network-based fuzzy inference method (ANFIS) in the identification of distributed parameter systems, implementing a distributed sensor network in the system. Some main properties of different identification methods are presented with possible application. The fuzzy systems, implemented using rule bases, fuzzy values, membership fun...