JACIII Vol.9 No.6 pp. 607-614
doi: 10.20965/jaciii.2005.p0607


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

February 22, 2005
May 30, 2005
November 20, 2005
decision making, preference assessment, incomplete comparison, neural networks
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 Lp-metric function as underlying decision maker preference show that SONIA-based DNN outperforms conventional DNN for decision maker preference assessment with incomplete comparisons.
Cite this article as:
M. Widyanto, K. Kawamoto, B. Kusumoputro, and K. Hirota, “SONIA-Based Decision Neural Network for Preference Assessment with Incomplete Comparisons,” J. Adv. Comput. Intell. Intell. Inform., Vol.9 No.6, pp. 607-614, 2005.
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Last updated on Jul. 12, 2024