This paper reviews neuro-fuzzy systems, which combine methods from neural network theory with fuzzy systems. Such combinations have been considered for several years already. However, the term neuro-fuzzy still lacks proper deenition, and still has the avour of a buzzword to it. Surprisingly few neuro-fuzzy approaches do actually employ neural networks, even though they are very often depicted ...

In an earlier companion paper [56] a supervised learning neural network pattern classifier called the fuzzy min-max classification neural network was described. In this sequel, the unsupervised learning pattern clustering sibling called the fuzzy min-max clustering neural network is presented. Pattern clusters are implemented here as fuzzy sets using a membership function with a hyperbox core t...

The QFD method is widely used in the product preliminary design and competitive analysis of different products. The overall customer satisfaction is usually set as the objective and principle of the design planning and evaluation of products. As an MADM problem, in generally, the calculation of the objective value relies on the specification of importance weights to accomplish trade-offs among ...

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...

The defects of BP neural network, such as low convergence speed, falling into local minimum easily, bad generalization ability, can depress the calculation accuracy of BP neural network and damage its practical effect. So the research of improving BP neural network has great theoretical and practical significance. The paper advances a new fuzzy neural network algorithm to overcome the defects o...

In this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. In other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of network. Then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (TFN). This paper com...

Motion control of mobile robots is a typical nonlinear tracking control issue and has been discussed with different control schemes such as PID, GPC, sliding mode, predictive control etc[1]-[3]. Intelligent control techniques, based on neural networks and fuzzy logic, have also been developed for path tracking control of mobile robots[4][5]. While conventional neural networks have good ability ...

Abstract: In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of...