Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant
Hydroelectric power; Hydroelectric power plants; Neural networks; Bat algorithms; Bio-inspired algorithms; Electricity production; Forecasting electricity; Hybrid Meta-heuristic; Hydropower; Renewable energies; Water consumption; Electric power generation
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-231822023-05-29T14:38:14Z Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant Hussin S.N.H.S. Malek M.A. Jaddi N.S. Hamid Z.A. 57194948280 55636320055 36716354300 52663349600 Hydroelectric power; Hydroelectric power plants; Neural networks; Bat algorithms; Bio-inspired algorithms; Electricity production; Forecasting electricity; Hybrid Meta-heuristic; Hydropower; Renewable energies; Water consumption; Electric power generation Hydropower is one of the technologies in renewable energy that is commercially viable on a large scale. A hybrid of metaheuristic Artificial Neural Network (ANN) technique with Bat Algorithm (BA), a bio-inspired algorithm is proposed to forecast future electricity production and water consumption at Sultan Azlan Shah Hydropower Dam located upstream of Perak river. In this study, both the ANN and Hybrid ANN-Bat Algorithm coding was designed and written explicitly to tailor the time series input data and assumptions used in this study. Comparison on results obtained from ANN and the proposed hybrid ANN - BA was conducted. Simulations conducted in this study exhibited that the proposed hybrid algorithm is much superior then the conventional ANN. � 2016 IEEE. Final 2023-05-29T06:38:14Z 2023-05-29T06:38:14Z 2017 Conference Paper 10.1109/PECON.2016.7951467 2-s2.0-85024392000 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024392000&doi=10.1109%2fPECON.2016.7951467&partnerID=40&md5=3d5b121abf688f88105a76326c32de1e https://irepository.uniten.edu.my/handle/123456789/23182 7951467 28 31 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Hydroelectric power; Hydroelectric power plants; Neural networks; Bat algorithms; Bio-inspired algorithms; Electricity production; Forecasting electricity; Hybrid Meta-heuristic; Hydropower; Renewable energies; Water consumption; Electric power generation |
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57194948280 |
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57194948280 Hussin S.N.H.S. Malek M.A. Jaddi N.S. Hamid Z.A. |
| format |
Conference Paper |
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Hussin S.N.H.S. Malek M.A. Jaddi N.S. Hamid Z.A. |
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Hussin S.N.H.S. Malek M.A. Jaddi N.S. Hamid Z.A. Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| author_sort |
Hussin S.N.H.S. |
| title |
Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| title_short |
Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| title_full |
Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| title_fullStr |
Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| title_full_unstemmed |
Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant |
| title_sort |
hybrid metaheuristic of artificial neural network - bat algorithm in forecasting electricity production and water consumption at sultan azlan shah hydropower plant |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806428429830062080 |