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In this paper, the cloud model is used to first predict drivers\u2019 charging behavior. An optimization model of charging stations is proposed, which is based on waiting time. The target of this optimization model is to minimize the time cost to electric vehicle drivers. We use the SCE-UA algorithm to solve the optimization model. We apply our method to Dalian, China to optimize charging station locations. We also analyze the optimized result with or without behavior prediction, the optimized result of different numbers of electric vehicles, and the optimized result of different cost constraints. The analysis shows the feasibility and advantages of the charging station location optimization method proposed in this paper.<\/jats:p>","DOI":"10.1177\/0037549717743807","type":"journal-article","created":{"date-parts":[[2018,1,8]],"date-time":"2018-01-08T19:20:15Z","timestamp":1515439215000},"page":"625-636","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":55,"title":["The location optimization of electric vehicle charging stations considering charging behavior"],"prefix":"10.1177","volume":"94","author":[{"given":"Zhihui","family":"Tian","sequence":"first","affiliation":[{"name":"Automotive Engineering College, Dalian University of Technology, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbin","family":"Hou","sequence":"additional","affiliation":[{"name":"Automotive Engineering College, Dalian University of Technology, PR 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