Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
Identification of Large-Spatial Air Pollution Patterns Using a Neural Network
Tadashi KONDO
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1994 Volume 7 Issue 2 Pages 59-67

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Abstract

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.

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