The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

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 ...

The objective of this paper is to investigate and find a solution by designing the intelligent controllers for controlling water level system, such as fuzzy logic and neural network. The controllers also can be specifically run under the circumstance of system disturbances. To achieve these objectives, a prototype of water level control system has been built and implementations of both fuzzy lo...

Nonlinear dynamic ball balancing beam has been successfully controlled by applying conventional methods, neural networks, and fuzzy logic respectively. Conventional methods necessitate strong mathematical and control background to derive equations. Neural networks learn to balance a ball, but the ball never settles down due to the fact that \discrete resolution of the boxes representation" was ...

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...

This paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of articial neural networks, can get a real input vector and calculates its corresponding fuzzy o...

The conformational energy values of 3-amino-4-nitraminofurazan (C2N4O3H2) molecule changing with two torsion angles were firstly calculated using density functional theory (DFT) with Lee-Young-Parr correlation functional and 6-31 G(d) basis set on Gaussian Program. And then, these obtained discrete data were made continuous by using Fuzzy Logic Modelling (FLM) and Artificial Neural Network (ANN...

security term in mobile ad hoc networks has several aspects because of the special specification of these networks. in this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy ratiocination of fuzzy system as...

In this paper, a new architecture combining dynamic neural units and fuzzy logic approaches is proposed for a complex chemical process modeling. Such processes need a particular care where the designer constructs the neural network, the fuzzy and the fuzzy neural network models which are very useful in black box modeling. The proposed architecture is specified to the pH chemical reactor due to ...

the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...