文献类型：期刊文献

英文题名：Floor Heating Customer Prediction Model Based on Random Forest

作者：Yao, Zhihuan[1];Xu, Xian[1];Yu, Huiqun[1]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2018

卷号：7

期号：1

起止页码：37

外文期刊名：INTERNATIONAL JOURNAL OF NETWORKED AND DISTRIBUTED COMPUTING

收录：EI(收录号：20184406019737);WOS:【ESCI(收录号:WOS:000459356600005)】；

基金：This work is supported by National Natural Science Foundation of China under grants No. 61173048, 61572318, 61702334, 61772200, 61872142, the Information Development Special Funds of Shanghai Economic and Information Commission under Grant No. 201602008, Shanghai Pujiang Talent Program under Grant No. 17PJ1401900, Natural Science Foundation of Shanghai under Grant No. 17ZR1406900, 17ZR1429700, and Educational Research Fund of ECUST under Grant No. ZH1726108.

语种：英文

外文关键词：Floor heating; customer; prediction random forest

摘要：Nowadays floor heating service is increasingly attracting both residents in cold areas and gas companies for market profits. With the aggravation of market-oriented competition, the gas companies are actively seeking service transformation. It is of great significance to gas companies to be able to forecast those customers willing to use floor heating. In this paper, we establish a floor heating customer prediction model that helps indicate the potential customers using floor heating, based on analyzing existing floor heating customers' behavior. The prediction model uses random forest. We exploit data coming from the actual running of a Shanghai based gas company. Experiments show that the random forest model has better performance than those using k-nearest neighbor (KNN) or logistic regression. (c) 2018 The Authors. Published by Atlantis Press SARL.