Using XGBoost Model with Feature Selection Techniques for Wind Speed Forecasting

SHORT COMMUNICATION

Authors

  • Hamza Hanif Department of Physics, Simon Fraser University, Canada
  • Ahmer Shaheem Tahir Department of Physics, University of Karachi
  • Rimsha Shaikh Department of Applied Physics, NED University
  • Dania Anjum Department of Physics, University of Karachi

DOI:

https://doi.org/10.46660/ijeeg.v12i4.78

Abstract

Renewable Energy Sources have a lot of importance in today’s world to produce an electrical output which explains the main reasons that every government and policy maker now a days prefer Renewable Energy in the wake of global warming and limited availability of fossil fuels (Twidell and Weir, 2021). The Renewable Energy Sources are hazardless, pollution free, eco-friendly, freely available in nature in vast quantities and most importantly, they give a chance to create a carbon-free environment.

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Published

2023-03-11

How to Cite

Hanif, H., Tahir, A. S., Shaikh, R., & Anjum, D. (2023). Using XGBoost Model with Feature Selection Techniques for Wind Speed Forecasting: SHORT COMMUNICATION. International Journal of Economic and Environmental Geology, 12(4), 69–72. https://doi.org/10.46660/ijeeg.v12i4.78

Issue

Vol. 12 No. 4 (2021): October-December

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 

Publisher: Society of Economic Geologists and Mineral Technologists (SEGMITE)

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