OPAC Home  

Long term annual electricity demand forecasting by artificial neural networks including socio-economic indicators and climatic conditions

By: Hapuarachchi, Diyasha ChenaliContributor(s): Dr. K.T.M.U. Hemapala [supervisor] | A.G.B.P.Jayasekara [supervisor]Language: English Publisher: Moratuwa Department of Electrical Engineering, University of Moratuwa 2018Description: CD-ROM included xi,45p. : ill. (some col.), charts, tablesSubject(s): ELECTRICAL ENGINEERING-Dissertation | ELECTRICAL INSTALLATIONS-Dissertation | ELECTRICITY DEMAND FORECASTING | ARTIFICIAL NEURAL NETWORKS | MSc in Electrical InstallationsOnline resources: Click here to access online Dissertation note: University of Moratuwa 2018 Department of Electrical Engineering Faculty of Engineering
    Average rating: 0.0 (0 votes)
Item type Current location Call number Shelving info Copy number Status Notes Date due Barcode Item holds Course reserves
Thesis Thesis Library, University of Moratuwa
The University of Moratuwa Library (UML) is one of the most prominent technology libraries in the country. Its main subject specializations are Engineering, Architecture and Information Technology. However, the library caters to the requirements of the membership by housing books and other materials of general interest as well.
Thesis Collection
696.6(043) (Browse shelf) DEE 07/56 LB//DON/66/2017 Not For Loan (Restricted Access) TH3539 TH3539

M.Sc. in Electrical Installations

Total holds: 0

TH3539

University of Moratuwa 2018 Department of Electrical Engineering Faculty of Engineering

There are no comments on this title.

to post a comment.

Copyright @ 2015-2021 Library, University of Moratuwa, Katubedda, Moratuwa (10400), Sri Lanka