Presentation | 2003/1/28 Meteorological data classification and submodels estimation by competitive modular networks Mitsutoshi SAITO, Tetsuo FURUKAWA, Syozo YASUI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The meteorological data classification method using competitive modular networks is proposed. The method is used in conjunction with a set of multilayer-perceptron models. A large number of monthly meteorological data collected from various areas of Japan are processed to obtain meteorological types. The results give some insight into region-season coupled changes. A study was also made by replacing the perceptron models by a simple recurrent network, in order to deal with the time series data more directly for better understanding of the underlying dynamcal aspects. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | competitive modular networks / time series models / meteorological classification |
Paper # | NC2002-131 |
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Committee | NC |
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Conference Date | 2003/1/28(1days) |
Place (in Japanese) | (See Japanese page) |
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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) | Meteorological data classification and submodels estimation by competitive modular networks |
Sub Title (in English) | |
Keyword(1) | competitive modular networks |
Keyword(2) | time series models |
Keyword(3) | meteorological classification |
1st Author's Name | Mitsutoshi SAITO |
1st Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology() |
2nd Author's Name | Tetsuo FURUKAWA |
2nd Author's Affiliation | Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology |
3rd Author's Name | Syozo YASUI |
3rd Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology |
Date | 2003/1/28 |
Paper # | NC2002-131 |
Volume (vol) | vol.102 |
Number (no) | 628 |
Page | pp.pp.- |
#Pages | 5 |
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