Most of the recent research in the design of fuzzy controllers has been centered on automatic techniques using expert’s input-output data. The majority of these techniques rely on the use of Takagi-Sugeno type controllers and fuzzy-neural-network [3-5,11], fuzzy clustering and fuzzy partition approaches [1,2,6,7]. These controllers, however, are not fully-linguistic and the use of neural-networ...

Three computing models, based on the multilayer perceptron and capable of fuzzy classification of patterns, are presented. The first type of fuzzy neural network uses the membership values of the linguistic properties of the past load and weather parameters and the output of the network is defined as fuzzy-class-membership values of the forecast load. The backpropagation algorithm is used to tr...

This paper consists of a survey of various engineering, computational biology, medicine, etc applications based on the fuzzy neural network model, and also a summary of the recent techniques such as still support vector machine, self-organizing map, principal component analysis. The advantage of the fuzzy neural network is that it is closer to biophysical reality and mathematically more tractab...

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 ...

In order to speed up the defects of the neural network computing and recognition, the essay proposes the information identification method research of sports throwing force based on the fuzzy neural network model. Firstly, I use the information, which is the combination of the wavelet transformation and the fuzzy neural network, to identify the new method combining and make the noise-suppressed...

In this paper, the author research on electrical equipment’s fault diagnosis based on the improved support vector machine and fuzzy clustering. Combining the support vector combined fuzzy sets and neural network to carry on the fault diagnosis is a most prosperous diagnosis method. This article put forward a sample processing method using fuzzy clustering and studied the application of fuzzy co...

Symmetric polygonal fuzzy number is employed to build an improved feedforward fuzzy neural network (FNN). First, a novel fuzzy arithmetic and extension principle for the polygonal fuzzy numbers is derived. Second, the topological architecture of a three layer feedforward FNN is presented, and the input-output law of this network is systematically studied. Third, a fuzzy BP learning algorithm fo...

Fuzzy neural network methods have been successfully used to diagnose many diseases. This paper uses logic-based fuzzy neural networks to diagnose breast cancer. Logic-based fuzzy neural networks can select reduced size of input subspace by selecting useful inputs. For the optimization of the input subspace and the structure of the logic-based fuzzy neural networks, genetic algorithms and gradie...