Caio Cesar, Oba Ramos, Andre Nunes De Souza, Danilo S. Gastaldello, J. Papa
{"title":"Identification and feature selection of non-technical losses for industrial consumers using the software WEKA","authors":"Caio Cesar, Oba Ramos, Andre Nunes De Souza, Danilo S. Gastaldello, J. Papa","doi":"10.1109/INDUSCON.2012.6451485","DOIUrl":null,"url":null,"abstract":"This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 10th IEEE/IAS International Conference on Industry Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDUSCON.2012.6451485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids.