TY - JOUR
T1 - Typhoon event-based evolutionary fuzzy inference model for flood stage forecasting
AU - Chen, Chang Shian
AU - Jhong, You Da
AU - Wu, Ting Ying
AU - Chen, Shien Tsung
PY - 2013/5/20
Y1 - 2013/5/20
N2 - This study proposes an evolutionary fuzzy inference model that combines a fuzzy inference model, genetic programming (GP), and a genetic algorithm (GA) to forecast flood stages during typhoons. The number of fuzzy inference rules in the proposed approach is based on the number of typhoon flood events. The consequent part of the rule was formed by constructing GP models that depict the rainfall-stage relationship of a specific flood event, whereas the GA was used to search the parameters of the fuzzy membership functions in the premise part of the rule. This study uses the proposed event-based evolutionary fuzzy inference model to forecast the typhoon flood stages of Wu River in Taiwan. Forecasting results based on stage hydrographs and performance indices verify the forecasting ability of the proposed model. This study also identifies the weights of triggered fuzzy rules during the fuzzy inference process, showing that a fuzzy rule is triggered according to the characteristics of the flood event that forms the rule. Moreover, physical explanation of the proposed evolutionary fuzzy inference model was discussed.
AB - This study proposes an evolutionary fuzzy inference model that combines a fuzzy inference model, genetic programming (GP), and a genetic algorithm (GA) to forecast flood stages during typhoons. The number of fuzzy inference rules in the proposed approach is based on the number of typhoon flood events. The consequent part of the rule was formed by constructing GP models that depict the rainfall-stage relationship of a specific flood event, whereas the GA was used to search the parameters of the fuzzy membership functions in the premise part of the rule. This study uses the proposed event-based evolutionary fuzzy inference model to forecast the typhoon flood stages of Wu River in Taiwan. Forecasting results based on stage hydrographs and performance indices verify the forecasting ability of the proposed model. This study also identifies the weights of triggered fuzzy rules during the fuzzy inference process, showing that a fuzzy rule is triggered according to the characteristics of the flood event that forms the rule. Moreover, physical explanation of the proposed evolutionary fuzzy inference model was discussed.
UR - http://www.scopus.com/inward/record.url?scp=84876858632&partnerID=8YFLogxK
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U2 - 10.1016/j.jhydrol.2013.03.033
DO - 10.1016/j.jhydrol.2013.03.033
M3 - Article
AN - SCOPUS:84876858632
SN - 0022-1694
VL - 490
SP - 134
EP - 143
JO - Journal of Hydrology
JF - Journal of Hydrology
ER -