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The hidden information between both objects and parameters revealed in our approach is more comprehensive. Furthermore, based on the similarity measures of fuzzy sets, a new adjustable object-parameter approach is proposed to predict unknown data in incomplete fuzzy soft sets. Data predicting converts an incomplete fuzzy soft set into a complete one, which makes the fuzzy soft set applicable not only to decision making but also to other areas. The compared results elaborated through rate exchange data sets illustrate that both our improved approach and the new adjustable object-parameter one outperform the existing method with respect to forecasting accuracy.<\/jats:p>","DOI":"10.1515\/amcs-2017-0011","type":"journal-article","created":{"date-parts":[[2017,4,2]],"date-time":"2017-04-02T10:00:29Z","timestamp":1491127229000},"page":"157-167","source":"Crossref","is-referenced-by-count":15,"title":["Object\u2013Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set"],"prefix":"10.61822","volume":"27","author":[{"given":"Yaya","family":"Liu","sequence":"first","affiliation":[{"name":"College of Mathematics Southwest Jiaotong University , Chengdu 610031, Sichuan, PR China"}]},{"given":"Keyun","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Mathematics Southwest Jiaotong University , Chengdu 610031, Sichuan, PR China"}]},{"given":"Chang","family":"Rao","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology Southwest Jiaotong University , Chengdu 610031, Sichuan, PR China"}]},{"given":"Mahamuda","family":"Alhaji Mahamadu","sequence":"additional","affiliation":[{"name":"Council for Scientific and Industrial Research PO 132 , Accra , Ghana"}]}],"member":"37438","published-online":{"date-parts":[[2017,5,4]]},"reference":[{"key":"2021040703265586184_j_amcs-2017-0011_ref_001_w2aab2b8c21b1b7b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"Alcantud, J.C.R. 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