Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Vachtsevanos, G.J. | Kim, S.S. | Echauz, J.R. | Ramani, V.K.
Affiliations: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA. E-mail: [email protected], [email protected] | Electrical and Computer Engineering Department, University of Puerto Rico – Mayagúez Campus, Mayagüez, PR 00681-5000, USA. E-mail: [email protected] | Information Technology Lab., GE CR & D, Bldg. K1, Room 5C5A, One Research Cir., Niskayuna, NY 12309, USA. E-mail: [email protected]
Abstract: This paper describes and compares several nonlinear decision-making systems, including multilayer perceptrons, wavelet neural networks, polynomial neural networks, and fuzzy decision models. The applicability of these systems is illustrated through the problem of check authorization from incomplete data. A benchmark is established in terms of classical linear discriminant analysis and Bayes quadratic classification, in order to assess the need for the neuro-fuzzy strategies. An overall improvement of around 10 percentage points in classification accuracy on an independent test set is demonstrated for each of the neuro-fuzzy models over conventional statistical techniques. In addition to classification accuracy, five performance measures are reported: accuracy in dollar terms, robustness, parametric efficiency, training computational expense, and classification balance. Even though each system performs differently on these measures, any neuro-fuzzy model is recommended over traditional techniques in problems such as check authorization, where the improvement in reliability warrants the added cost of implementation.
Journal: Journal of Intelligent and Fuzzy Systems, vol. 6, no. 2, pp. 259-278, 1998
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]