Particle Swarm Optimization method for estimation of Weibull parameters: A case study for the Brazilian northeast region
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DOI: 10.1016/j.renene.2015.08.060
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References listed on IDEAS
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- Tiam Kapen, Pascalin & Jeutho Gouajio, Marinette & Yemélé, David, 2020. "Analysis and efficient comparison of ten numerical methods in estimating Weibull parameters for wind energy potential: Application to the city of Bafoussam, Cameroon," Renewable Energy, Elsevier, vol. 159(C), pages 1188-1198.
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- Chaurasiya, Prem Kumar & Ahmed, Siraj & Warudkar, Vilas, 2018. "Comparative analysis of Weibull parameters for wind data measured from met-mast and remote sensing techniques," Renewable Energy, Elsevier, vol. 115(C), pages 1153-1165.
- Alrashidi, Musaed & Rahman, Saifur & Pipattanasomporn, Manisa, 2020. "Metaheuristic optimization algorithms to estimate statistical distribution parameters for characterizing wind speeds," Renewable Energy, Elsevier, vol. 149(C), pages 664-681.
- Acitas, Sukru & Aladag, Cagdas Hakan & Senoglu, Birdal, 2019. "A new approach for estimating the parameters of Weibull distribution via particle swarm optimization: An application to the strengths of glass fibre data," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 116-127.
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- dos Santos, Fábio Sandro & do Nascimento, Kerolly Kedma Felix & da Silva Jale, Jader & Xavier, Sílvio Fernando Alves & Ferreira, Tiago A.E., 2024. "Brazilian wind energy generation potential using mixtures of Weibull distributions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
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Keywords
Particle Swarm Optimization (PSO); Weibull distribution; Wind resource; Numerical methods;All these keywords.
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