{"title":"Artificial Neural Network for Single Reservoir Operation","authors":"K. A. Al-Mohseen, A. Towfeeq","doi":"10.33899/RENGJ.2014.87313","DOIUrl":null,"url":null,"abstract":"The current paper aims to explore the capability of Artificial Neural Network models (ANN) to calculate the optimal operating policy of a single reservoir system (Al_Qaim reservoir on the Al_KhosarRiver). The ANN models proposed in this research were making use of the outcomes emerged from two Stochastic Dynamic Programming (SDP) models suggested by previous study on the same reservoir system i.e. Explicit Stochastic Dynamic Programming and Implicit Stochastic Dynamic Programming. The two ANN models have been used to find pattern between inflow and initial storage of the system in one hand, and the release and the final storage of the system on other hand. It is found that the topology of the first model which adopted the attributes of the ESDP is 2-6-2, while that which was implemented the ISDP attributes has a 2-10-2ANN topology. The final results prevail that good agreement have been exist between the output (release) of the proposed ANN models and those obtained by the two (SDP) models with coefficients of determination0.934 and 0.803 respectively. Keywords: Artificial Neural Network , Dynamic Programming, Operation reservoir.","PeriodicalId":339890,"journal":{"name":"AL Rafdain Engineering Journal","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AL Rafdain Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33899/RENGJ.2014.87313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The current paper aims to explore the capability of Artificial Neural Network models (ANN) to calculate the optimal operating policy of a single reservoir system (Al_Qaim reservoir on the Al_KhosarRiver). The ANN models proposed in this research were making use of the outcomes emerged from two Stochastic Dynamic Programming (SDP) models suggested by previous study on the same reservoir system i.e. Explicit Stochastic Dynamic Programming and Implicit Stochastic Dynamic Programming. The two ANN models have been used to find pattern between inflow and initial storage of the system in one hand, and the release and the final storage of the system on other hand. It is found that the topology of the first model which adopted the attributes of the ESDP is 2-6-2, while that which was implemented the ISDP attributes has a 2-10-2ANN topology. The final results prevail that good agreement have been exist between the output (release) of the proposed ANN models and those obtained by the two (SDP) models with coefficients of determination0.934 and 0.803 respectively. Keywords: Artificial Neural Network , Dynamic Programming, Operation reservoir.