2003-06-192024-05-14https://scholars.lib.ntu.edu.tw/handle/123456789/660058摘要：水庫平日灌溉、給水、發電運轉操作的水量除了水庫集水區日常流量外，最主要是依賴汛期水庫防洪操作所攔蓄的大量洪水流量。如何在安全與減災的前提下，進行有效的水庫颱洪操作以增加發電量，充分利用大自然所帶來的資源，即需要在降低水庫出水量與提高水庫蓄水容量間取得平衡並獲得最大防洪與水資源利用效益，欲達成以上目標，則必須要靠迅速而精確掌握水庫集水區流量站水文狀況及水庫流量推估方能達成。 本研究目的即在運用人工智慧類神經網路方法建立石門水庫集水區各流量站流量演算模式，進而推估水庫流量，達到掌握水庫及集水區水文資訊，以作為水庫管理機關水資源管理及防洪操作決策之參考及依據。<br> Abstract: Reservoirs not only provide water supply, hydroelectric energy and irrigation, but also smooth out extreme inflows to mitigate flood or drought. Therefore, it is very important to determine an optimal reservoir operating schedule for effective water distribution. In order to impermanently make use of available water resources, a method, which integrates many theories from different fields to provide a friendly using environment for user, can be applied by the reservoir management authorities during flood periods. The Shi-man Reservoir will be chosen as the study area. A rainfall-runoff model will be constructed by using artificial neural network to provide high accuracy of flood forecasting. The fuzzy-neural network is constructed by a set of Rule-Base control, a modified self-organizing counterpropagation network and a fuzzy control predictor on the basis of the extracted rules in its predicting part.水庫操作類神經網路流量推估reservoir operationneural networkestimation of flow