제어로봇시스템학회:학술대회논문집
- 2004.08a
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- Pages.1078-1083
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- 2004
Neural network analysis of water pollution for a main river, Tamagawa, in Tokyo metropolis
- Yuan, Yan (The Faculty of Engineering, Miyazaki University) ;
- Kambe, Junko (Faculty of Foreign Language, Daito Bunka University) ;
- Aoyama, T. (The Faculty of Engineering, Miyazaki University) ;
- Nagashima, U. (Grid Technology Research Center)
- Published : 2004.08.25
Abstract
We proposed a method to compensate incomplete observations and made a study of environmental problem, water quality of Tama-River in Tokyo.The method is based on interpolations of the multi-layer neural networks. We call the approach as CQSAR method .which can compensate the defect data.The water quality data include defects which will give wrong effect to other normal data. The CQSAR method suppresses the wrong effect .Thus, we believe that the proposed CQSAR method has practical usability for environment examinations.
Keywords
- neural networks;
- inverse optimization problems;
- interpolations;
- environments;
- water quality;
- Tama River