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Cogent Engineering Volume 5, 2018 - Issue 1

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Research Article

Wind energy assessment and mapping using terrain nonlinear autoregressive neural network (TNARX) and wind station data

Salisu Muhammad Lawan Department of Electrical Engineering, Kano University of Science and Technology , Wudil, PMB 3244, Kano, Nigeria; Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS) , 94300, Kota SamarahanSarawak, MalaysiaCorrespondence[email protected]

https://orcid.org/0000-0002-8144-0459 View further author information

Wan Azlan Wan Zainal Abidin Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS) , 94300, Kota SamarahanSarawak, Malaysia

Qingsong Ai Wuhan University of Technology , China

(Reviewing Editor)

Article: 1452594 | Received 28 Dec 2017, Accepted 12 Mar 2018, Published online: 26 Mar 2018

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https://doi.org/10.1080/23311916.2018.1452594
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Citations (3)

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Articles from other publishers (3)

Salisu Muhammad Lawan & Wan Azlan Wan Zainal Abidin. 2020. Wind Solar Hybrid Renewable Energy System. Wind Solar Hybrid Renewable Energy System.

Muhammad Abid Saeed, Zahoor Ahmed, Jian Yang & Weidong Zhang. (2020) An optimal approach of wind power assessment using Chebyshev metric for determining the Weibull distribution parameters. Sustainable Energy Technologies and Assessments 37, pages 100612.
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Jianzhou Wang, Xiaojia Huang, Qiwei Li & Xuejiao Ma. (2018) Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China. Energy 164, pages 432-448.
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