Presentation 1999/11/26
An Analysis and Interpretation of Real Data by Static Inverse Optimization
Hong Zhang, Masumi Ishikawa,
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Abstract(in English) In this paper, we propose a novel approach to solve inverse static optimization problems using the neural network learning with a quadratic criterion function which includes linear form. In the approach, an algorithm of deciding the pareto solutions with minimum value in attributes is proposed to apply it to a large quatity of data. The pareto solutions in data set and the inequality conditions can be decided by the algorithm in the less calculation times. To evaluate the effectiveness of the proposed method, Some simulation experiments were carried out, and the character of the criterion function decided by network learning was examined. The latent factor in deciding standard of tenants was interpreted to some rental residence data in Tokyo, etc..
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Keyword(in English) static inverse optimization / neural network / structural learning with forgetting.
Paper # NC99-57
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Committee NC
Conference Date 1999/11/26(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Analysis and Interpretation of Real Data by Static Inverse Optimization
Sub Title (in English)
Keyword(1) static inverse optimization
Keyword(2) neural network
Keyword(3) structural learning with forgetting.
1st Author's Name Hong Zhang
1st Author's Affiliation Kyushu Institute of Technology()
2nd Author's Name Masumi Ishikawa
2nd Author's Affiliation Kyushu Institute of Technology
Date 1999/11/26
Paper # NC99-57
Volume (vol) vol.99
Number (no) 473
Page pp.pp.-
#Pages 8
Date of Issue