基于相近关系的粗糙因子神经网络的模式识别方法

Journal of Applied Sciences ›› 2005, Vol. 23 ›› Issue (5): 513-516.

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Model Identification in Rough Factor Neural Network Based on Nearness Relationship

XIAO Di, HU Shou-song

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received:2004-05-28 Revised:2004-08-27 Online:2005-09-30 Published:2005-09-30

Abstract

Abstract: In this paper, relation of nearness is proposed to replace that of indiscernibility for increased robustness of a decision system against noise.Preliminaries of nearness relationship rough sets are defined and the properties of nearness rough membership function are studied.An architecture of neural network based on nearness relationship rough sets and nearness rough membership functions is described.Neurons in such a network consist of conventional neurons and rough neurons, each neuron having a rough factor.Influence of noise on the network is reduced, and convergence is speeded.An example based on fault identification of an aircraft actuator is presented.Simulation results indicate effectiveness of the proposed method.

Key words: model identification, rough factor, rough sets, nearness relationship, neural network

CLC Number:

TP18

XIAO Di, HU Shou-song. Model Identification in Rough Factor Neural Network Based on Nearness Relationship[J]. Journal of Applied Sciences, 2005, 23(5): 513-516.

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Model Identification in Rough Factor Neural Network Based on Nearness Relationship

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