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A Hybrid Time Series Forecasting Method Based on Supervised Machine Learning Program

  • Ganesh Prasad Khuntia
  • Ritesh DashEmail author
  • Sarat Chandra Swain
  • Prashant Bawaney
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 37)

Abstract

Clean and inexhaustible source of energy is the requirement of the entire world with respect to the present scenario. Among the different types of energy sources, wind energy is the cleanest energy and inexhaustible source of energy. In order to ensure the production of clean energy, it is required to forecast the level of wind energy from a day ahead. Forecasting of wind energy not only forecasts the level of wind but also predicts the type of wind energy, density, and other important variables. This paper describes the short-term forecasting based on Machine Learning algorithm. This paper compares the different Machine Learning Algorithm and its behavior in predicting or forecasting the day-ahead data for the wind energy system. Machine learning based on Python is formulated in this paper.

Keywords

Wind energy Python Forecasting Training set Testing set 

Notes

Acknowledgements

The authors would like to thank the Department of Electrical Engineering, CCCET, Bhilai for providing necessary laboratory facilities during the entire research activities.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ganesh Prasad Khuntia
    • 1
  • Ritesh Dash
    • 2
    Email author
  • Sarat Chandra Swain
    • 1
  • Prashant Bawaney
    • 2
  1. 1.School of Electrical EngineeringKIIT Deemed to be UniversityBhubaneswarIndia
  2. 2.CCETBhilaiIndia

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