Identification of Large-Spatial Air Pollution Patterns Using a Neural Network
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- KONDO Tadashi
- School of Medical Sciences, The University of Tokushima
Bibliographic Information
- Other Title
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- ニューラルネットワークを用いた広域大気汚染濃度パターンの同定
- ニューラル ネットワーク オ モチイタ コウイキ タイキ オセン ノウド パタ
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Description
A new identification system of large-spatial air pollution patterns using a neural network and a source-receptor matrix, is described. The neural network used in this paper can identify a nonlinear system whose structure is very complex. In the previous identification system of a large-spatial air pollution patterns, a GMDH algorithm and a source-receptor matrix are used. The prediction results obtained by using the new identification system are compared with the results obtained by using the previous identification system. It is shown that the new identification system in this paper gives better prediction accuracy as compared with the previous identification system.
Journal
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- Transactions of the Institute of Systems, Control and Information Engineers
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Transactions of the Institute of Systems, Control and Information Engineers 7 (2), 59-67, 1994
THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)
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Keywords
Details 詳細情報について
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- CRID
- 1390001205165538944
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- NII Article ID
- 10007137749
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- NII Book ID
- AN1013280X
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- ISSN
- 2185811X
- 13425668
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- NDL BIB ID
- 3858259
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed