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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/487297
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dc.contributor.advisorAhmed Elshafie, Associate Prof. Dr.
dc.contributor.authorSabah Saadi Fayaed (P52304)
dc.date.accessioned2023-10-11T02:32:15Z-
dc.date.available2023-10-11T02:32:15Z-
dc.date.issued2013-09-06
dc.identifier.otherukmvital:75046
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/487297-
dc.descriptionStochastic Dynamic Programming (SDP) has often been a useful technique for identifying the optimal operating policies for reservoirs. The stochastic nature of in-flows is usually described by an order one Markov process, of which the current inflow is conditioned on the preceding inflow, and represented by a transition probability Pr(Qt+1/Qt). An important controversy in the literature of stochastic reservoir optimizations, as well as that of stream flow modeling, concerns the appropriateness of using order one Markov process to describe the inflow sequence. Theoretically, these previous inflows can be treated as state variables to be included in the SDP formulation. However, this addition of state variables yields a mathematical formulation that is impractical to solve due to the curse of dimensionality" inherent in the SDP formulation. In this study
dc.language.isoeng
dc.publisherUKM, Bangi
dc.relationFaculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina
dc.rightsUKM
dc.subjectOptimal Operation Of Water Supply Reservoir
dc.subjectWater Supply Reservoir Operation
dc.subjectWater Supply Reservoir Through Augmented ANN-MSDP Model
dc.subjectANN-MSDP Model
dc.subjectDynamic programming
dc.titleOptimal Operation Of Water Supply Reservoir Through Augmented ANN-MSDP Model
dc.typeTheses
dc.format.pages160
dc.identifier.callnoT57.83 .F348 2013 3
dc.identifier.barcode000189
Appears in Collections:Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina

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