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Most of the existing characteristics weighting methods always rely heavily on the experts\u2019 a priori knowledge, while rough set weighting method does not rely on experts\u2019 a priori knowledge and can meet the need of objectivity. However, the current rough set weighting methods could not obtain a balanced redundant characteristic set. Too much redundancy might cause inaccuracy, and less redundancy might cause ineffectiveness. In this paper, a new method based on rough set and knowledge granulation theories is proposed to ascertain the characteristics weight. Experimental results on several UCI data sets demonstrate that the weighting method can effectively avoid subjective arbitrariness and avoid taking the nonredundant characteristics as redundant characteristics.<\/jats:p>","DOI":"10.1155\/2018\/1838639","type":"journal-article","created":{"date-parts":[[2018,5,31]],"date-time":"2018-05-31T19:32:57Z","timestamp":1527795177000},"page":"1-9","source":"Crossref","is-referenced-by-count":1,"title":["A New Knowledge Characteristics Weighting Method Based on Rough Set and Knowledge Granulation"],"prefix":"10.1155","volume":"2018","author":[{"given":"Zhenquan","family":"Shi","sequence":"first","affiliation":[{"name":"Business School, University of Shanghai for Science and Technology, Shanghai 200093, China"},{"name":"Nantong University, Nantong, Jiangsu 226017, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9311-483X","authenticated-orcid":true,"given":"Shiping","family":"Chen","sequence":"additional","affiliation":[{"name":"Business School, University of Shanghai for Science and Technology, Shanghai 200093, China"}]}],"member":"311","reference":[{"issue":"9","key":"1","first-page":"1790","volume":"31","year":"2011","journal-title":"Systems Engineering Theory and Practice"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-0255(98)00010-3"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asm094"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1080\/14786451.2014.907292"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-014-1519-y"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2016.12.043"},{"issue":"12","key":"7","first-page":"7177","volume":"2","year":"2010","journal-title":"International Journal of Engineering Science and Technology"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2004.01.011"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2006.06.003"},{"issue":"8","key":"10","first-page":"154","volume":"322","year":"2011","journal-title":"Statistics & Decisions"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.3969\/j.issn.1004-4132.2010.02.013"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(02)00196-4"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2013.03.018"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.07.024"},{"year":"2000","key":"17"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-2217(00)00280-0"},{"issue":"2","key":"20","first-page":"248","volume":"27","year":"2012","journal-title":"Applied Mathematics. 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