Modelling reservoir water release decision using temporal data mining and neural network - Wan Ishak, Wan Hussain; Ku-Mahamud, Ku Ruhana; Md Norwawi, Norita (IJETAE Exploring Research and Innovations, 2012)
During emergencies such as flood and drought seasons, reservoir acts as a defence mechanism to reduce the risk of flooding and maintaining water supply. During this period, decision regarding the water release is very crucial. During flood season, early water release decision should be established to prepare the reservoir for incoming in-flow. While during drought season, reservoir water level should be maintained in order to sustain the supply and other usages. Reservoir operation during these two seasons cause conflicting decision as incoming inflow is hardly predicted. Modeling the reservoir water release decision can be one of the solutions to this problem. The modeling is based on reservoir’s operator previous experiences when dealing with such situations. These experiences provide valuable information on the decision when the reservoir water should be released. Temporal data mining technique has been applied to extract temporal pattern from the reservoir operational record and neural network has been applied as the modeling tool. The neural network model was developed to classify the data that in turn can be used to aid the reservoir water release decision. In this study neural network model 8-23-2 has produced the acceptable performance during training, validation and testing.