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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