processes characterizing uncertainties needs the creating of the proper knowledge base for the controller. In this paper, to solve this problem the integration of fuzzy set theory and wavelet neural network (WNN) is considered. The structure and operation algorithms of fuzzy WNN based controller are presented. Using gradient method the learning of fuzzy WNN is performed to find optimal values o...

The object of this paper is to elaborate an automatic system in order to detect suspect zones or tumors in medical image especially brain ones. The purpose is to define with precision the existence of different kinds of lesions using a hybrid system which combines Fuzzy Neural Networks and Expert System. After getting regions features by regions growing or mathematical morphology, the fuzzy neu...

A fuzzy ARTMAP system is a system for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequence of analog or binary input vectors. The original fuzzy ARTMAP system incorporates two fuzzy ART modules and an inter-ART module. Many different approaches have been proposed to modify fuzzy ARTMAP systems. In this paper, we proposed a new app...

the uv-spectrophotometric method of analysis was proposed for simultaneous determination of fluoxetine (flx) and sertraline (srt). considering the strong spectral overlap between uv-vis spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrophotometric techniques. here, full-spectrum multivariate calibrations adaptive neuro-fuzz...

The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed sys...

the hybrid fuzzy differential equations have a wide range of applications in science and engineering. we consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. here neural network is considered as a part of large eld called neural computing or soft computing. the proposed algorithm is illustrated by numerical examples and the resu...

1 This paper describes DANIELA, a Neuro-Fuzzy system for control applications. The system is based on a custom neural device that can implement either Multi-Layer Perceptrons, Radial Basis Functions or Fuzzy paradigms. The system implements intelligent control algorithms mixing neuro-fuzzy algorithms with nite state automata and is used to control a walking hexapod.

Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural...

a multi objective honey bee mating optimization (hbmo) designed by online learning mechanism is proposed in this paper to optimize the double fuzzy-lead-lag (fll) stabilizer parameters in order to improve low-frequency oscillations in a multi machine power system. the proposed double fll stabilizer consists of a low pass filter and two fuzzy logic controllers whose parameters can be set by the ...

Though traditional neural networks and fuzzy logic are powerful universal approximators, however without some refinements, they may not, in general, be good approximators for adaptive systems. By extending fuzzy sets to qualitative fuzzy sets, fuzzy logic may become universal approximators for adaptive systems. Similar considerations can be extended to neural networks.