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