Application of Artificial Intelligence on Reservoir Flood Control Operation

• Main Authors: Heng-Yi Liao, 廖珩毅
• Other Authors: An-Pei Wang
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/08303574451209606560

博士 === 中原大學 === 土木工程研究所 === 96 === As a monsoon climate island, the annual average rainfall on Taiwan reaches 2500 mm, which is three times over world’s average. However, water resource in Taiwan count on typhoon rain due to its particular climate and geographic characteristics. It is hard for reservoir to consider both in reserve typhoon rain and flood control. Therefore, how to operate reservoir in a high-effect way is the key of water resource management in Taiwan. To make optimal operation decision, reservoir needs to forecast rainfall and inflow accurately before typhoon coming, and the purpose of this thesis is to build some models to meet reservoir’s demand. The models including four parts: typhoon rainfall forecasting, reservoir inflows forecasting, typhoon flood assessment, and downstream water level forecasting (in Chapter 3~6, respectively). All the proposed models are based on artificial intelligence (AI) technique. AI has been developed rapidly in recent years and applied extensively in many fields since it possesses advantages of self-learning and logical inference. Artificial neuron networks, fuzzy theory, and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are three AI methods applied here. Shihmen reservoir and Danshuei River basin are taken as study area; water level in Sin-Hai Bridge is prediction downstream water level. Some satisfactory results are showed in this thesis, and this thesis provides a well-forecast method for reservoir to refer to while facing operation problems.