The potential of topographical feed forward neural network (T-FFNN) technique in monthly wind speed and direction prediction

Lawan, S.M and Abidin, W.A.W.Z and Lawan, A.M. and Bichi, S.L. and Abba, I. (2018) The potential of topographical feed forward neural network (T-FFNN) technique in monthly wind speed and direction prediction. 2017 6th International Conference on Electrical Engineering and Informatics (ICEEI), 2018. pp. 1-6. ISSN 2155-6830

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Official URL: https://ieeexplore.ieee.org/document/8312407
Item Type: Article
Uncontrolled Keywords: wind, prediction, wind mapping, neural network, research, Universiti Malaysia Sarawak, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Faculties, Institutes, Centres > Faculty of Engineering
Depositing User: Karen Kornalius
Date Deposited: 31 Jul 2019 01:43
Last Modified: 31 Jul 2019 01:43
URI: http://ir.unimas.my/id/eprint/26215

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