Machine Learning-based Analysis of correlation between Energy Consumption data of the Company and its Sales

被引:0
|
作者
Lee, Jungi [1 ]
Kim, NacWoo [1 ]
Lee, HyunYong [1 ]
Park, SangJun [1 ]
Lee, ByungTak [1 ]
机构
[1] Elect & Telecommun Res Inst ETRI, Honam Res Ctr HRC, Gwangju, South Korea
来源
11TH INTERNATIONAL CONFERENCE ON ICT CONVERGENCE: DATA, NETWORK, AND AI IN THE AGE OF UNTACT (ICTC 2020) | 2020年
关键词
Regression; Data pre-processing; Predictive-learning; Gradient Boosting; Machine Learning; Energy data;
D O I
10.1109/ictc49870.2020.9289575
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper has researched about the correlation between company data, and its annual sales data. Using the identified correlation, we propose a new method of predicting the company's annual sales data with energy consumption data. For this work, gradient boosting was applied to the predictive learning model for effective and better performance of prediction. To implement this method, district address-based energy consumption data is merged into company survey data with pre-processing. Then to predict the sales of each company, the gradient boosting based machine learning model has applied. Our approach to utilizing the energy consumption data can contribute to a new method of predicting the status of companies.
引用
收藏
页码:1258 / 1260
页数:3
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