A Performance Comparison of Machine Learning Algorithms for Load Forecasting in Smart Grid

With the rapid increase in the world's population, the global electricity demand has increased drastically. Therefore, it is required to adopt efficient energy management mechanisms. Since the energy consumption trends are rather dynamic. Therefore, precise energy demand estimation and short an...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.48419-48433
Hauptverfasser:	Alquthami, Thamer, Zulfiqar, Muhammad, Kamran, Muhammad, Milyani, Ahmad H., Rasheed, Muhammad Babar
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Classification algorithms decision tree Decision trees Economic forecasting electric load forecasting Electric power demand Electrical loads Energy consumption Energy management Error analysis Forecasting Ground penetrating radar logistic regression Machine learning machine learning algorithms Neural networks Optimization Prediction algorithms Predictive models Smart grid Smart grids Stability analysis Support vector machines
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