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Non-linear prediction model of river flow by self-organization method

 

作者: SABURO IKEDA,   SATORU FUJISHIGE,   YOSHIKAZU SAWARACl,  

 

期刊: International Journal of Systems Science  (Taylor Available online 1976)
卷期: Volume 7, issue 2  

页码: 165-176

 

ISSN:0020-7721

 

年代: 1976

 

DOI:10.1080/00207727608941909

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

This paper presents two heuristic self-organization methods for construction of a non-linear prediction model of river flows. The self-organization algorithms have multi-layered structures of the perceptron type and provide the optimally complex non-linear equation of the input-output relation. The algorithms are applied to the river-flow prediction of Karasu JRiver and Katsura River in Japan. The performance of the prediction models by the self-organization methods is compared with that of the hydrological models. The numerical comparison shows that without any hydrological and geographical knowledge the prediction models presented here aro superior to the elaborate hydrological models.

 

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