Wan Ishak, Wan Hussain and Ku-Mahamud, Ku Ruhana and Md Norwawi, Norita (2011) Reservoir water release decision modelling. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011 , Bandung, Indonesia.

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Abstract

Reservoir water release decision during emergency situations typically, flood and drought is very crucial as early and accurate decision can reduce the negative impact of the events.In practice, decision regarding the water release is made by experience reservoir operator. During emergency such as heavy upstream rainfall that may causes massive inflow into the reservoir, early water release cannot be done without the attendance and knowledge of the operator. Additionally, the operator has to be very certain that the water released will be replaced with the incoming inflow as maintaining the water level at the normal range is very critical for multipurpose reservoir. Having this situation every year the reservoir operation record or the log book has become knowledge or experience rich "repository". Mining this "repository" will give an insight on how and when the decision was made to release the water from the reservoir during the emergency situations.The neural network (NN) model was developed to classify the data that in turn can be used to aid the reservoir water release decision. In this study NN model 8-23-2 has produced the acceptable performance during training (93.94%), validation (100%) and testing (100%).

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	reservoir water release decision, neural network, repository mining
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	College of Arts and Sciences
Depositing User:	Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited:	21 Dec 2011 04:35
Last Modified:	07 Apr 2015 07:04
URI:	https://repo.uum.edu.my/id/eprint/4015

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