Publication: Intelligent decision support model based on neural network to support reservoir water release decision
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Date
2011
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Abstract
Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. The proposed model consists of situation assessment, forecasting and decision models. Situation assessment utilized temporal data mining technique to extract relevant data and attribute from the reservoir operation record. The forecasting model utilize NN to perform forecasting of the reservoir water level, while in the decision model, NN is applied to perform classification of the current and changes of reservoir water level. The simulations have shown that the performances of NN for both forecasting and decision models are acceptably good. � 2011 Springer-Verlag.
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Keywords
Emergency Management, Forecasting, Intelligent Decision Support System, Neural Network, Decision models, Emergency management, Flood risks, Forecasting models, Heavy rainfall, Intelligent decision support, Intelligent decision support systems, Reservoir operation, Reservoir water, Reservoir water level, Situation assessment, Temporal data mining, Water release, Computer simulation, Data mining, Decision making, Decision support systems, Forecasting, Heavy water, Models, Neural networks, Rain, Reservoir management, Risk management, Software engineering, Water levels, Reservoirs (water)