Abstract—Use the historical data of household energy
consumption to design a valuable information model for
predicting future demand. The cluster analysis of the data set of
the transmission power distribution system shows the
proportion of different consumption behaviors and the level of
power consumption in different periods, and effectively predicts
the power consumption of users. It can help power companies
and users to control the load during peak hours of power
demand transfer to off-peak hours.
Index Terms—Big data, data analytics, RStudio language,
predictive model.
Cuihua Tian is with the School of Computer and Information Engineering,
Xiamen University of Technology, China (Corresponding author: Jianhong
Qian; e-mail: qianjianhong2020@outlook.com, tiancuihua@xmut.edu.cn).
Cite: Cuihua Tian, Mugisha Theophile, Jianhong Qian, Yiping Zhang, and Zhigang Hu, "Prediction of Time Series Analysis of Power Usage Based on Rstudio," International Journal of Machine Learning and Computing vol. 12, no. 2, pp. 68-72, 2022.
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