Development of Artificial Intelligent Techniques for Short-Term Wind Speed Forecasting

Development of Artificial Intelligent Techniques for Short-Term Wind Speed Forecasting
  IJETT-book-cover           
  
© 2021 by IJETT Journal
Volume-69 Issue-7
Year of Publication : 2021
Authors : Amit Verma, K G Upadhyay, M M Tripathi
DOI :  10.14445/22315381/IJETT-V69I7P208

How to Cite?

Amit Verma, K G Upadhyay, M M Tripathi, "Development of Artificial Intelligent Techniques for Short-Term Wind Speed Forecasting," International Journal of Engineering Trends and Technology, vol. 69, no. 7, pp. 56-63, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I7P208

Abstract
The main aim of this research work is to present an assessment of machine learning algorithms for wind speed forecasting. Five machine learning algorithms considered for performance comparisons are such as Multiple Linear Regression, Polynomial Regression, Random Forest, Decision Tree, and Gradient Descent. The prediction is based on the data collected for Brussels in Belgium from open source for the period of 1 Jan 2020 to 30 Jun 2020. The overall best prediction results are obtained by the Gradient Descent algorithm to predict the wind speed for the next 300 minutes. The performance of Polynomial Regression is also found satisfactory.

Keywords
Data Preprocessing, Gradient Descent, Polynomial Regression, Mean Absolute Percentage Error (MAPE), Root mean Square Error (RMSE).

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