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Energy Consumption Forecasting in Industrial Sector Using Machine Learning Approaches

  • Mouad BahijEmail author
  • Mohamed Cherkaoui
  • Moussa Labbadi
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)

Abstract

This paper proposes an energy consumption forecasting Model by using the Machine Learning Methods (ML). On the one hand, the Linear Regression (LR), Support Vector Machine (SVM), Decision Tree (DT) and Artificial Neural Networks (ANN) are used as predictive tools. In the other hand, by using different attributes as inputs, the LR, SVM and ANN algorithms can predict energy consumption in the industry sector. In order to assess the performances of the proposed approaches, a simulation is carried out with Python software. The comparison between these methods proves the efficiency of LR approach.

Keywords

Electricity consumption Prediction Machine learning LR SVM ANN 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Mouad Bahij
    • 1
    Email author
  • Mohamed Cherkaoui
    • 1
  • Moussa Labbadi
    • 1
  1. 1.Engineering for Smart and Sustainable Systems Research Center, Mohammadia School of Engineers (EMI)Mohammed V UniversityRabatMorocco

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