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Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

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  1. Zhang, Jie & Chowdhury, Souma & Messac, Achille & Castillo, Luciano, 2013. "A Multivariate and Multimodal Wind Distribution model," Renewable Energy, Elsevier, vol. 51(C), pages 436-447.
  2. Rehman, Shafiqur & Sahin, Ahmet Z., 2012. "Wind power utilization for water pumping using small wind turbines in Saudi Arabia: A techno-economical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4470-4478.
  3. Rana Muhammad Adnan & Zhongmin Liang & Xiaohui Yuan & Ozgur Kisi & Muhammad Akhlaq & Binquan Li, 2019. "Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation," Energies, MDPI, vol. 12(2), pages 1-22, January.
  4. Song, Dongran & Yang, Jian & Cai, Zili & Dong, Mi & Su, Mei & Wang, Yinghua, 2017. "Wind estimation with a non-standard extended Kalman filter and its application on maximum power extraction for variable speed wind turbines," Applied Energy, Elsevier, vol. 190(C), pages 670-685.
  5. Marwa Hassan & Alsnosy Balbaa & Hanady H. Issa & Noha H. El-Amary, 2018. "Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator," Energies, MDPI, vol. 11(10), pages 1-25, October.
  6. Chen, J.J. & Wu, Q.H. & Zhang, L.L. & Wu, P.Z., 2017. "Multi-objective mean–variance–skewness model for nonconvex and stochastic optimal power flow considering wind power and load uncertainties," European Journal of Operational Research, Elsevier, vol. 263(2), pages 719-732.
  7. Anicic, Obrad & Jovic, Srdjan, 2016. "Adaptive neuro-fuzzy approach for ducted tidal turbine performance estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1111-1116.
  8. Asadi, Shahla & Nilashi, Mehrbakhsh & Iranmanesh, Mohammad & Hyun, Sunghyup Sean & Rezvani, Azadeh, 2022. "Effect of internet of things on manufacturing performance: A hybrid multi-criteria decision-making and neuro-fuzzy approach," Technovation, Elsevier, vol. 118(C).
  9. Rodrigues, Eugénio & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Henggeler Antunes, Carlos, 2018. "Estimation of renewable energy and built environment-related variables using neural networks – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 959-988.
  10. Shamshirband, Shahaboddin & Keivani, Afram & Mohammadi, Kasra & Lee, Malrey & Hamid, Siti Hafizah Abd & Petkovic, Dalibor, 2016. "Assessing the proficiency of adaptive neuro-fuzzy system to estimate wind power density: Case study of Aligoodarz, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 429-435.
  11. Shamshirband, Shahaboddin & Petković, Dalibor & Anuar, Nor Badrul & Gani, Abdullah, 2014. "Adaptive neuro-fuzzy generalization of wind turbine wake added turbulence models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 270-276.
  12. Ahmed G. Abo-Khalil & Saeed Alyami & Khairy Sayed & Ayman Alhejji, 2019. "Dynamic Modeling of Wind Turbines Based on Estimated Wind Speed under Turbulent Conditions," Energies, MDPI, vol. 12(10), pages 1-25, May.
  13. Koo, Junmo & Han, Gwon Deok & Choi, Hyung Jong & Shim, Joon Hyung, 2015. "Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea," Energy, Elsevier, vol. 93(P2), pages 1296-1302.
  14. He, Qingqing & Wang, Jianzhou & Lu, Haiyan, 2018. "A hybrid system for short-term wind speed forecasting," Applied Energy, Elsevier, vol. 226(C), pages 756-771.
  15. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
  16. Liu, Hui & Tian, Hong-qi & Pan, Di-fu & Li, Yan-fei, 2013. "Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks," Applied Energy, Elsevier, vol. 107(C), pages 191-208.
  17. Bertašienė, Agnė & Azzopardi, Brian, 2015. "Synergies of Wind Turbine control techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 336-342.
  18. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
  19. Shafiqur Rehman & Md. Mahbub Alam & Luai M. Alhems & M. Mujahid Rafique, 2018. "Horizontal Axis Wind Turbine Blade Design Methodologies for Efficiency Enhancement—A Review," Energies, MDPI, vol. 11(3), pages 1-34, February.
  20. Zhongrong Zhang & Yiliao Song & Feng Liu & Jinpeng Liu, 2016. "Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis," Sustainability, MDPI, vol. 8(2), pages 1-30, January.
  21. Liu, Hui & Tian, Hong-qi & Li, Yan-fei, 2012. "Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction," Applied Energy, Elsevier, vol. 98(C), pages 415-424.
  22. Burlibaşa, A. & Ceangă, E., 2013. "Rotationally sampled spectrum approach for simulation of wind speed turbulence in large wind turbines," Applied Energy, Elsevier, vol. 111(C), pages 624-635.
  23. Oluseyi O. Ajayi & Richard O. Fagbenle & James Katende & Julius M. Ndambuki & David O. Omole & Adekunle A. Badejo, 2014. "Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria," Energies, MDPI, vol. 7(12), pages 1-27, December.
  24. Asmaa Alazmi & Bader S. Al-Anzi, 2023. "Assessment of Machine Learning Algorithms for Predicting Air Entrainment Rates in a Confined Plunging Liquid Jet Reactor," Sustainability, MDPI, vol. 15(18), pages 1-13, September.
  25. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
  26. Yaïci, Wahiba & Entchev, Evgueniy, 2016. "Adaptive Neuro-Fuzzy Inference System modelling for performance prediction of solar thermal energy system," Renewable Energy, Elsevier, vol. 86(C), pages 302-315.
  27. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2016. "Comprehensive overview of grid interfaced wind energy generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 260-281.
  28. Jena, Debashisha & Rajendran, Saravanakumar, 2015. "A review of estimation of effective wind speed based control of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1046-1062.
  29. Gergo Pinter & Imre Felde & Amir Mosavi & Pedram Ghamisi & Richard Gloaguen, 2020. "COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
  30. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
  31. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
  32. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.
  33. Yang, L. & Entchev, E., 2014. "Performance prediction of a hybrid microgeneration system using Adaptive Neuro-Fuzzy Inference System (ANFIS) technique," Applied Energy, Elsevier, vol. 134(C), pages 197-203.
  34. Douak, Fouzi & Melgani, Farid & Benoudjit, Nabil, 2013. "Kernel ridge regression with active learning for wind speed prediction," Applied Energy, Elsevier, vol. 103(C), pages 328-340.
  35. Kwami Senam A. Sedzro & Adekunlé Akim Salami & Pierre Akuété Agbessi & Mawugno Koffi Kodjo, 2022. "Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)," Energies, MDPI, vol. 15(22), pages 1-28, November.
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