DocumentCode :
1945579
Title :
Application of New Adaptive Higher Order Neural Networks in Data Mining
Author :
Xu, Shuxiang ; Chen, Ling
Author_Institution :
Sch. of Comput., Univ. of Tasmania, Launceston, TAS
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
115
Lastpage :
118
Abstract :
This paper introduces an adaptive Higher Order Neural Network (HONN) model and applies it in data mining such as simulating and forecasting government taxation revenues. The proposed adaptive HONN model offers significant advantages over conventional Artificial Neural Network (ANN) models such as much reduced network size, faster training, as well as much improved simulation and forecasting errors. The generalization ability of this HONN model is explored and discussed. A new approach for determining the best number of hidden neurons is also proposed.
Keywords :
data mining; neural nets; adaptive higher order neural networks; data mining; hidden neurons; Artificial neural networks; Brain modeling; Computational modeling; Computer networks; Computer science; Data mining; Humans; Neural networks; Neurons; Predictive models; Data Mining; Higher Order Neural Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.897
Filename :
4721705
Link To Document :
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