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Application of new adaptive higher order neural networks in data mining
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. © 2008 IEEE.
History
Publication title
Proceedings International Conference on Computer Science and Software Engineering CSSE 2008Editors
Kawada, SPagination
115-118ISBN
978-0-7695-3336-0Department/School
School of Information and Communication TechnologyPublisher
IEEE Computer SocietyPlace of publication
Los Alamitos, CaliforniaEvent title
International Conference on Computer Science and Software Engineering (CSSE)Event Venue
Wuhan, ChinaDate of Event (Start Date)
2008-12-12Date of Event (End Date)
2008-12-14Repository Status
- Restricted