Identification of Related Factors of Users' Power Consumption and Prediction Model of Power Consumption Based on Random Forest Algorithm

Given the characteristics of big data associated with power consumption prediction, such as numerous types, vast volume, high dimensionality, and rapid generation speed, we propose a method for subspace clustering analysis of extensive user electricity characteristics after studying the evaluation i...

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Veröffentlicht in:	2023 International Conference on Internet of Things, Robotics and Distributed Computing (ICIRDC) S. 205 - 210
Hauptverfasser:	Zhu, Zheng, Xiao, Shuang, Zhang, Ruijia, An, Bailong
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 29.12.2023
Schlagworte:	Big Data Correlation Electricity Identification of related factors power consumption forecast Power demand Prediction algorithms Predictive models Random forest algorithm Simulation
Online-Zugang:	Volltext
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