教師資料查詢 | 類別: 期刊論文 | 教師: 張麗秋 LI-CHIU CHANG (瀏覽個人網頁)

標題:Assessing the effort of meteorological variables for evaporation estimation by self-organizing map neural network
學年
學期
出版(發表)日期2010/04/01
作品名稱Assessing the effort of meteorological variables for evaporation estimation by self-organizing map neural network
作品名稱(其他語言)
著者Chang, Fi-John; Chang, Li-Chiu; Kao, Huey-Shan; Wu, Gwo-Ru
單位淡江大學水資源及環境工程學系
出版者Amsterdam: Elsevier BV
著錄名稱、卷期、頁數Journal of Hydrology 384(1–2), pp.118–129
摘要The phenomenon of evaporation affects the distribution of water in the hydrological cycle and plays a key role in agriculture and water resource management. We propose a self-organizing map neural network (SOMN) to assess the variability of daily evaporation based on meteorological variables. The daily meteorological data sets from a climate gauge were collected as inputs to the SOMN and then were classified into a topology map based on their similarities to investigate their multi-collinear relationships to assess their effort in the evaporation. To accurately estimate the daily evaporation based on the input pattern, the weights that connect the clustered centers in a hidden layer with the output were trained by using the least square regression method. In addition, we compared the results with those of back propagation neural network (BPNN), modified Penman and Penman–Monteith formulas. The results demonstrated that the topological structures of SOMN could give a meaningful map to present the clusters of meteorological variables and the networks could well estimate the daily evaporation. By comparing the performances of these models in estimating daily and long-term (monthly or yearly) cumulative evaporation, the SOMN provides the best performance.
關鍵字Artificial neural network; Evaporation; Meteorological variables; Self-organizing map
語言英文
ISSN0022-1694
期刊性質
收錄於SCI;EI;
產學合作
通訊作者Chang, Fi-John
審稿制度
國別荷蘭
公開徵稿
出版型式紙本;
相關連結
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