Application of adaptive fuzzy rule-based models for reconstruction of missing precipitation events
作者:
A.J. ABEBE,
D.P. SOLOMATINE,
R.G. W. VENNEKER,
期刊:
Hydrological Sciences Journal
(Taylor Available online 2000)
卷期:
Volume 45,
issue 3
页码: 425-436
ISSN:0262-6667
年代: 2000
DOI:10.1080/02626660009492339
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper describes a fuzzy rule-based approach applied for reconstruction of missing precipitation events. The working rules are formulated from a set of past observations using an adaptive algorithm. A case study is carried out using the data from three precipitation stations in northern Italy. The study evaluates the performance of this approach compared with an artificial neural network and a traditional statistical approach. The results indicate that, within the parameter sub-space where its rules are trained, the fuzzy rule-based model provided solutions with low mean square error between observations and predictions. The problems that have yet to be addressed are overfitting and applicability outside the range of training data.
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