Object–Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set

Alcantud, J.C.R. (2016). A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set, Information Fusion29: 142–148.10.1016/j.inffus.2015.08.007Search in Google Scholar

Atanassov, K.T. (1986). Intuitionistic fuzzy sets, Fuzzy Sets and Systems20(1): 87–96.10.1016/S0165-0114(86)80034-3Search in Google Scholar

Deng, T. and Wang, X. (2013). An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets, Applied Mathematical Modelling37(6): 4139–4146.10.1016/j.apm.2012.09.010Search in Google Scholar

Fan, J. (2002). Some new similarity measures, Journal of Xi’an Institute of Posts and Telecommunications3(7): 69–71.Search in Google Scholar

Feng, F., Liu, X., Leoreanu-Fotea, V. and Jun, Y.B. (2011). Soft sets and soft rough sets, Information Sciences181(6): 1125–1137.10.1016/j.ins.2010.11.004Search in Google Scholar

Gau, W.L. and Buehrer, D.J. (1993). Vague sets, IEEE Transactions on Systems, Man, and Cybernetics23(2): 610–614.10.1109/21.229476Search in Google Scholar

Herawan, T. and Deris, M.M. (2011). A soft set approach for association rules mining, Knowledge-Based Systems24(1): 186–195.10.1016/j.knosys.2010.08.005Search in Google Scholar

Jiang, Y., Liu, H., Tang, Y. and Chen, Q. (2011). Semantic decision making using ontology-based soft sets, Mathematical and Computer Modelling53(5): 1140–1149.10.1016/j.mcm.2010.11.080Search in Google Scholar

Jiang, Y., Tang, Y., Chen, Q., Liu, H. and Tang, J. (2010). Interval-valued intuitionistic fuzzy soft sets and their properties, Computers & Mathematics with Applications60(3): 906–918.10.1016/j.camwa.2010.05.036Search in Google Scholar

Jun, Y.B., Lee, K.J. and Park, C.H. (2009). Soft set theory applied to ideals in d-algebras, Computers & Mathematics with Applications57(3): 367–378.10.1016/j.camwa.2008.11.002Search in Google Scholar

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 Mathematics236(6): 1521–1530.10.1016/j.cam.2011.09.016Search in Google Scholar

Li, Y., Qin, K. and He, X. (2014). Some new approaches to constructing similarity measures, Fuzzy Sets and Systems234(1): 46–60.10.1016/j.fss.2013.03.008Search in Google Scholar

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 Medicine64: 161–171.10.1016/j.artmed.2015.05.002Search in Google Scholar

Li, Z., Xie, N. and Wen, G. (2015b). Soft coverings and their parameter reductions, Applied Soft Computing31: 48–60.10.1016/j.asoc.2015.02.027Search in Google Scholar

Li, Z. and Xie, T. (2014). The relationship among soft sets, soft rough sets and topologies, Soft Computing18(4): 717–728.10.1007/s00500-013-1108-5Search in Google Scholar

Maji, P.K., Biswas, R. and Roy, A.R. (2001). Fuzzy soft sets, Journal of Fuzzy Mathematics9(3): 589–602.Search in Google Scholar

Molodtsov, D. (1999). Soft set theory—first results, Computers & Mathematics with Applications37(4): 19–31.10.1016/S0898-1221(99)00056-5Search in Google Scholar

Muthukumar, P. and Krishnan, G.S.S. (2016). A similarity measure of intuitionistic fuzzy soft sets and its application in medical diagnosis, Applied Soft Computing41: 148–156.10.1016/j.asoc.2015.12.002Search in Google Scholar

Nowicki, R. (2010). On classification with missing data using rough-neuro-fuzzy systems, International Journal of Applied Mathematics and Computer Science20(1): 55–67, DOI: 10.2478/v10006-010-0004-8.10.2478/v10006-010-0004-8Search in Google Scholar

Pawlak, Z. (1982). Rough sets, International Journal of Computer & Information Sciences11(5): 341–356.10.1007/BF01001956Search in Google Scholar

Qin, H., Ma, X., Herawan, T. and Zain, J.M. (2012a). DFIS: A novel data filling approach for an incomplete soft set, International Journal of Applied Mathematics and Computer Science22(4): 817–828, DOI: 10.2478/v10006-012-0060-3.10.2478/v10006-012-0060-3Search in Google Scholar

Qin, H., Ma, X., Zain, J.M. and Herawan, T. (2012b). A novel soft set approach in selecting clustering attribute, Knowledge-Based Systems36: 139–145.10.1016/j.knosys.2012.06.001Search in Google Scholar

Roy, A.R. and Maji, P. (2007). A fuzzy soft set theoretic approach to decision making problems, Journal of Computational and Applied Mathematics203(2): 412–418.10.1016/j.cam.2006.04.008Search in Google Scholar

Siwek, K. and Osowski, S. (2016). Data mining methods for prediction of air pollution, International Journal of Applied Mathematics and Computer Science26(2): 467–478, DOI: 10.1515/amcs-2016-0033.10.1515/amcs-2016-0033Search in Google Scholar

Wang, P. (1983). Fuzzy Sets and Its Applications, Shanghai Science and Technology Press, Shanghai.Search in Google Scholar

Xiao, Z., Gong, K. and Zou, Y. (2009). A combined forecasting approach based on fuzzy soft sets, Journal of Computational and Applied Mathematics228(1): 326–333.10.1016/j.cam.2008.09.033Search in Google Scholar

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 Systems8(5): 959–976.10.1080/18756891.2015.1099903Search in Google Scholar

Xu, W., Ma, J., Wang, S. and Hao, G. (2010). Vague soft sets and their properties, Computers & Mathematics with Applications59(2): 787–794.10.1016/j.camwa.2009.10.015Search in Google Scholar