Paper:
Language: English:

SONIA-Based Decision Neural Network for Preference Assessment with Incomplete Comparisons

Muhammad R. Widyanto^, Kazuhiko Kawamoto^, Benyamin Kusumoputro^**, and Kaoru Hirota^*

*Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama-city 226-8502, Japan
**Faculty of Computer Science, University of Indonesia, Depok Campus, West Java, Indonesia

Received: February 22, 2005

Accepted: May 30, 2005

Keywords: decision making, preference assessment, incomplete comparison, neural networks

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.9, No.6 pp. 607-614, 2005

Abstract

To deal with the problem of incomplete comparisons in decision maker preference assessment, a SONIA (Self-Organized Network inspired by Immune Algorithm)-based Decision Neural Network (DNN) is proposed. B cell mutation of SONIA creates hidden units having diverse data characteristics that improve generalization capability. This mutation deals with a limited number of training data resulting from incomplete pair-wise comparisons by decision maker. Experiments on linear, Euclidean, and L_p-metric function as underlying decision maker preference show that SONIA-based DNN outperforms conventional DNN for decision maker preference assessment with incomplete comparisons.

[Notice]
* "Preview" is the first 2 pages of the article. You don't need the registration.
* To read the PDF file you will then need to download and install the Adobe Reader.
Adobe Reader is free and available for download here: