A Fuzzy Adaptive Neighborhood Search for Function Optimization David A. Pelta Armando Blanco Jose-L. Verdegay Depto. de Ciencias de la Computaci6n e Inteiigencia Artificial. Universidad de Granada, Granada, Spain {dpelta,armando ,verdegay}@ugr . es Neighborhood based search algorithms have been applied with success in the optimization field. In this work, a Fuzzy Adaptive Neighborhood Search al...

in this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.based on the backstepping technique, the adaptive fuzzy controller is constructed. the main contributions of the paper...

This paper describes the design of an adaptive direct control scheme for a class of nonlinear systems. The architecture is based on a fuzzy inference system (FIS) of Takagi Sugeno (TS) type to approximate a feedback linearization control law. The parameters of the consequent part of the fuzzy system are adapted and changed according to a law derived using Lyapunov stability theory. The asymptot...

Regarding the fact that getting a suitable combination of the human resources and service stations is one of the important issues in the most service and manufacturing environments, In this paper, we have studied the two models of planning queuing systems and its effect on the cost of the each system by using two fuzzy queuing models of M/M/1 and M/E2/1. In the first section, we have compar...

We propose an interactive content based image retrieval (CBIR) system using M-band wavelet features with Earth Mover’s Distance (EMD). A fuzzy relevance feedback (FRF) method is proposed to enhance the retrieval in order to retrieve more images. So that retrieve images are semantically close to the query. M ×M sub-bands coefficient are used as primitive features, on which, for each pixel, energ...

in this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. utilizing the generalized characterization theorem. then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. here neural network is considered as a part of large eld called n...

Abstract— This study derives a new interpretation for Fuzzy Kohonen Neural Network in parameter m .Derivation of new algorithm is accomplished by adaptive m. The learning rate in each iteration is effected by updating m ascending or descending .This yields automatic control to distribution of learning rate in the neighborhood of all data nodes at each iteration .This experiment evaluates the mo...