Presentation | 1997/11/17 A study on general solution to inverse optimization problems by neural network Hong Zhang, Masumi Ishikawa, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, we proposed a novel general approach to inverse optimization problems by neural networks learning. It contains a newly method which be called recursive modification of its principal minors of matrix guaranteeing the positive semidefiniteness of the resulting criterion parameter matrix to solve the inverse optimization problems with nonstandard quadratic criterion functions. In accordance with the method to cancel unstableness for solving the inverse optimization problems. Through some experiments on computer, we take the unity and continuity of nonstandard quadratic criterion function which be satified with inverse optimization problems into consideration, and discuss the constancy of marginal rate of substitution in data analysis. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | inverse optimization problem / semipositive matrix / neural network / quadratic optimization |
Paper # | NC97-54 |
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Committee | NC |
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Conference Date | 1997/11/17(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A study on general solution to inverse optimization problems by neural network |
Sub Title (in English) | |
Keyword(1) | inverse optimization problem |
Keyword(2) | semipositive matrix |
Keyword(3) | neural network |
Keyword(4) | quadratic optimization |
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 | 1997/11/17 |
Paper # | NC97-54 |
Volume (vol) | vol.97 |
Number (no) | 379 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |