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2017 | 27 | 1 | 157-167

Tytuł artykułu

Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set

Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
The research on incomplete fuzzy soft sets is an integral part of the research on fuzzy soft sets and has been initiated recently. In this work, we first point out that an existing approach to predicting unknown data in an incomplete fuzzy soft set suffers from some limitations and then we propose an improved method. 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.

Rocznik

Tom

27

Numer

1

Strony

157-167

Opis fizyczny

Daty

wydano
2017
otrzymano
2016-04-22
poprawiono
2016-09-05
zaakceptowano
2016-10-15

Twórcy

autor
  • College of Mathematics, Southwest Jiaotong University, Chengdu 610031, Sichuan, PR China
autor
  • College of Mathematics, Southwest Jiaotong University, Chengdu 610031, Sichuan, PR China
autor
  • College of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, Sichuan, PR China
  • Council for Scientific and Industrial Research, PO 132, Accra, Ghana

Bibliografia

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  • Deng, T. and Wang, X. (2013). An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets, Applied Mathematical Modelling 37(6): 4139-4146.
  • Fan, J. (2002). Some new similarity measures, Journal of Xi'an Institute of Posts and Telecommunications 3(7): 69-71.
  • Feng, F., Liu, X., Leoreanu-Fotea, V. and Jun, Y.B. (2011). Soft sets and soft rough sets, Information Sciences 181(6): 1125-1137.
  • Gau, W.L. and Buehrer, D.J. (1993). Vague sets, IEEE Transactions on Systems, Man, and Cybernetics 23(2): 610-614.
  • Herawan, T. and Deris, M.M. (2011). A soft set approach for association rules mining, Knowledge-Based Systems 24(1): 186-195.
  • Jiang, Y., Liu, H., Tang, Y. and Chen, Q. (2011). Semantic decision making using ontology-based soft sets, Mathematical and Computer Modelling 53(5): 1140-1149.
  • Jiang, Y., Tang, Y., Chen, Q., Liu, H. and Tang, J. (2010). Interval-valued intuitionistic fuzzy soft sets and their properties, Computers & Mathematics with Applications 60(3): 906-918.
  • Jun, Y.B., Lee, K.J. and Park, C.H. (2009). Soft set theory applied to ideals in d-algebras, Computers & Mathematics with Applications 57(3): 367-378.
  • Kong, Z., Wang, L. and Wu, Z. (2011). Application of fuzzy soft set in decision making problems based on grey theory, Journal of Computational and Applied Mathematics 236(6): 1521-1530.
  • Li, Y., Qin, K. and He, X. (2014). Some new approaches to constructing similarity measures, Fuzzy Sets and Systems 234(1): 46-60.
  • Li, Z., Wen, G. and Xie, N. (2015a). An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster-Shafer theory of evidence: An application in medical diagnosis, Artificial Intelligence in Medicine 64: 161-171.
  • Li, Z., Xie, N. and Wen, G. (2015b). Soft coverings and their parameter reductions, Applied Soft Computing 31: 48-60.
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  • Xie, N., Han, Y. and Li, Z. (2015). A novel approach to fuzzy soft sets in decision making based on grey relational analysis and mycin certainty factor, International Journal of Computational Intelligence Systems 8(5): 959-976.
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Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.bwnjournal-article-amcv27i1p157bwm
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