Publication:
Intelligent decision support model based on neural network to support reservoir water release decision

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dc.Conferencecode85603
dc.Conferencedate27 June 2011 through 29 June 2011
dc.ConferencelocationKuantan
dc.Conferencename2nd International Conference on Software Engineering and Computer Systems, ICSECS 2011
dc.citedby4
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Utara Malaysia (UUM)
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorWan Ishak W.H.en_US
dc.contributor.authorKu-Mahamud K.R.en_US
dc.contributor.authorMd Norwawi N.en_US
dc.date.accessioned2024-05-29T01:54:51Z
dc.date.available2024-05-29T01:54:51Z
dc.date.issued2011
dc.description.abstractReservoir 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.
dc.description.natureFinalen_US
dc.description.sponsorshipSpringer
dc.identifier.doi10.1007/978-3-642-22170-5_32
dc.identifier.epage379
dc.identifier.isbn9783640000000
dc.identifier.issn18650929
dc.identifier.issuePART 1
dc.identifier.scopus2-s2.0-79960354050
dc.identifier.spage365
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-79960354050&doi=10.1007%2f978-3-642-22170-5_32&partnerID=40&md5=2c3c96d7b6e040c5708578bd7abefbcf
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9564
dc.identifier.volume179 CCIS
dc.languageEnglish
dc.language.isoen_US
dc.relation.ispartofCommunications in Computer and Information Science
dc.sourceScopus
dc.subjectEmergency Managementen_US
dc.subjectForecastingen_US
dc.subjectIntelligent Decision Support Systemen_US
dc.subjectNeural Networken_US
dc.subjectDecision modelsen_US
dc.subjectEmergency managementen_US
dc.subjectFlood risksen_US
dc.subjectForecasting modelsen_US
dc.subjectHeavy rainfallen_US
dc.subjectIntelligent decision supporten_US
dc.subjectIntelligent decision support systemsen_US
dc.subjectReservoir operationen_US
dc.subjectReservoir wateren_US
dc.subjectReservoir water levelen_US
dc.subjectSituation assessmenten_US
dc.subjectTemporal data miningen_US
dc.subjectWater releaseen_US
dc.subjectComputer simulationen_US
dc.subjectData miningen_US
dc.subjectDecision makingen_US
dc.titleIntelligent decision support model based on neural network to support reservoir water release decision
dc.typeConference Paperen_US
dspace.entity.typePublication

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