DocumentCode :
381197
Title :
A novel data-mining method based on the IMVFEWNN
Author :
Zheng Jian-guo ; Chun-qing, Li
Author_Institution :
Dept. of Manage., Hubei Automotive Ind. Inst., Shiyan, China
Volume :
3
fYear :
2002
fDate :
2002
Firstpage :
1998
Abstract :
Based on analyzing the immune phenomena in nature and utilizing the performance of the existent artificial neural network, a novel network structure, i.e. IMVFEWNN is proposed which integrates the immune mechanism and the structure of neural information processing. The learning algorithm of MVFEWNN is also given which contains the method of selecting an activation function and the adaptive algorithm of the network. This model makes it easy for a user to directly utilize the characteristic information of a pending problem and to simplify the original structure through adjusting the activation function with the prior knowledge, and then the working efficiency and the searching accuracy are both improved. The analysis in theory and the simulating test for the data mining problem show that, compared with the artificial neural network, IMVFEWNN is not only effective but also feasible.
Keywords :
data mining; learning (artificial intelligence); neural nets; search problems; very large databases; IMVFEWNN; activation function; adaptive algorithm; artificial neural network; data mining method; immune phenomena; large database; learning; nature; neural information processing; searching accuracy; Artificial neural networks; Automotive engineering; Data mining; Electronic mail; Information processing; Performance analysis; Radar signal processing; Signal analysis; Signal processing algorithms; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
Type :
conf
DOI :
10.1109/WCICA.2002.1021435
Filename :
1021435
Link To Document :
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