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 result...

To design a multi-population adaptive genetic BP algorithm, crossover probability and mutation probability are self-adjusted according to the standard deviation of population fitness in this paper. Then a hybrid model combining Fuzzy Neural Network and multi-population adaptive genetic BP algorithm—Adaptive Genetic Fuzzy Neural Network (AGFNN) is proposed to overcome Neural Network’s drawbacks....

The combination of evolutionary algorithms and ANN has been a recent interest in the field of research. Hopfield model is a type of recurrent neural network which has been widely studied for the purpose of associative memories. In the present work, this Hopfield Model of feedback neural networks has been studied with Monte Carlo adaptation learning rule and one evolutionary searching algorithm ...

suspended particles have deleterious effects on human health and one of the reasons why tehran is effected is its geographically location of air pollution. one of the most important ways to reduce air pollution is to predict the concentration of pollutants. this paper proposed a hybrid method to predict the air pollution in tehran based on particulate matter less than 10 microns (pm10), and the...

in recent years, the existing competitions between investment companies have been increased largely by entering private investors in capital market. large and powerful companies try to achieve the goals predicted to increase the competition capacity. to analyze the efficiency of investment companies, parametric and non-parametric methods are used. in this research, based on the dissociation pow...

This paper investigates the effectiveness of the genetic algorithm evolved neural network classifier and its application to the land cover classification of remotely sensed multispectral imagery. First, the key issues of the algorithm and the general procedures are described in detail. Our methodology adopts a real coded GA strategy and hybrid with a back propagation (BP) algorithm. The genetic...

Abstract In this research paper, the application of Artificial Neural Networks (ANN) for designing antennas is introduced. The primary objective optimization technique to focus on antenna’s parameters achieve a desirable S 11 value, which key metric an performance. To demonstrate effectiveness approach, method design three different using Numerical Analyzer (MATLAB) tool employed. Through study...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...