Engine fault has a high rate in the car. Considering about the distinguishing feature of the engine, Engine Diagnosis Expert System was investigated based on Diagnosis Tree module, Fuzzy Neural Network module, and commix reasoning module. It was researched including Knowledge base and Reasoning machine, and so on. In Diagnosis Tree module, the origin problem was searched in right method. In whi...

in common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. it is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical...

In order to extend capability of spiking neural P systems (SN P systems) to represent fuzzy knowledge and further to process fuzzy information, we propose an extended spiking neural P system in this paper, called fuzzy spiking neural P system (FSN P system). In the FSN P system, two types of neurons (fuzzy proposition neuron and fuzzy rule neuron), certain factor and new spiking rule are consid...

This paper gives a short introduction into Fuzzy Set Theory, presents an overview on fuzzy controllers, and discusses possible combinations between fuzzy controllers and neural networks. Fuzzy Sets suggested by L.A. Zadeh 32] ooer a possibility to formally describe linguistic expressions like tall, fast, medium, etc., and to operate on them. Fuzzy controllers use fuzzy sets to represent linguis...

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...

A fuzzy logic and neuro-fuzzy system for classification of hydrometeor type based on polarimetric radar measurements is described in this paper. The hydrometeor classification system is implemented by using fuzzy logic and a neural network, where the fuzzy logic is used to infer hydrometeor type, and the neural network learning algorithm is used for automatic adjustment of the parameters of the...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

Neural networks and fuzzy systems have been the subject of much interest in recent years for the control of nonlinear processes. Much research has been directed at indirect control schemes where, basically, the neural network or fuzzy system has been used to identify the process, and a controller has been synthesised from this model. An alternative approach is that of direct control where the n...

Estimation of distribution algorithm for optimization of neural networks for intrusion detection system p. 9 Neural network implementation in reprogrammable FPGA devices-an example for MLP p. 19 A new approach for finding an optimal solution and regularization by learning dynamic momentum p. 29 Domain dynamics in optimization tasks p. 37 Nonlinear function learning by the normalized radial basi...