Abstract
In this paper, we extend the basic distance measure in picture fuzzy sets to the new measures called generalized picture distance measures and picture association measures. Some properties of these measures are examined. An application to clustering problem is given to illustrate applicability of the proposed works.
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Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87–96.
Chen, T. Y. (2013). An interactive method for multiple criteria group decision analysis based on interval type-2 fuzzy sets and its application to medical decision making. Fuzzy Optimization and Decision Making, 12(3), 323–356.
Cornelis, C., De Cock, M., & Kerre, E. E. (2003). Intuitionistic fuzzy rough sets: At the crossroads of imperfect knowledge. Expert systems, 20(5), 260–270.
Cuong, B. C. (2014). Picture fuzzy sets. Journal of Computer Science and Cybernetics, 30(4), 409–420.
Dey, V., Pratihar, D. K., & Datta, G. L. (2011). Genetic algorithm-tuned entropy-based fuzzy C-means algorithm for obtaining distinct and compact clusters. Fuzzy Optimization and Decision Making, 10(2), 153–166.
Ester, M., Kriegel, H. P., Sander, J., & Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. Kdd, 96, 226–231.
Javed, K., Babri, H. A., & Saeed, M. (2014). Impact of a metric of association between two variables on performance of filters for binary data. Neurocomputing, 143, 248–260.
Krawczyk, B., & Woźniak, M. (2014). Diversity measures for one-class classifier ensembles. Neurocomputing, 126, 36–44.
Liu, H. C., Qin, J. T., Mao, L. X., & Zhang, Z. Y. (2015). Personnel selection using interval 2-tuple linguistic VIKOR method. Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3), 370–384.
Meng, F., & Chen, X. (2016). Entropy and similarity measure for Atannasov’s interval-valued intuitionistic fuzzy sets and their application. Fuzzy Optimization and Decision Making, 15(1), 75–101.
Oussalah, M., & Nefti, S. (2008). On the use of divergence distance in fuzzy clustering. Fuzzy Optimization and Decision Making, 7(2), 147–167.
Smarandache, F. (2002). Neutrosophic set—A generalization of the intuitionistic fuzzy set. In Proceeding of 2006 IEEE international conference on granular computing, pp. 38–42.
Son, L. H. (2015). DPFCM: A novel distributed picture fuzzy clustering method on picture fuzzy sets. Expert Systems with Applications, 42(1), 51–66.
Thong, N. T., & Son, L. H. (2015). HIFCF: An effective hybrid model between picture fuzzy clustering and intuitionistic fuzzy recommender systems for medical diagnosis. Expert Systems with Applications, 42(7), 3682–3701.
Thong, P. H., & Son, L. H. (2014). A new approach to multi-variables fuzzy forecasting using picture fuzzy clustering and picture fuzzy rules interpolation method. In Proceeding of 6th international conference on knowledge and systems engineering, pp. 679–690.
UCI Machine Learning Repository. (2013). Heart disease. https://archive.ics.uci.edu/ml/datasets/Heart+Disease. Accessed May 20, 2015.
Vendramin, L., Campello, R. J., & Hruschka, E. R. (2010). Relative clustering validity criteria: A comparative overview. Statistical Analysis and Data Mining, 3(4), 209–235.
VnExpress. (2014). Confidence voting for Vietnam National Assembly. http://vnexpress.net/tin-tuc/thoi-su/ket-qua-lay-phieu-tin-nhiem-3107632.html. Accessed May 20, 2015.
Xu, Z. (2012). Fuzzy ordered distance measures. Fuzzy Optimization and Decision Making, 11(1), 73–97.
Xu, Z. (2012). Intuitionistic fuzzy clustering algorithms. In Intuitionistic fuzzy aggregation and clustering (pp. 159–267). Springer, Berlin.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
Zhang, H. M., Xu, Z. S., & Chen, Q. (2007). On clustering approach to intuitionistic fuzzy sets. Control and Decision, 22, 882–888.
Acknowledgments
The authors wish to thank the Editor-in-chief and anonymous reviewers for their valuable comments and suggestions. We acknowledge the Center for High Performance Computing, VNU University of Science for executing the program on the IBM 1350 cluster server.
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The authors declare that they have no conflict of interest.
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This work is dedicated to Prof. Bui Cong Cuong (Institute of Mathematics, VAST) for 3-year presence of the picture fuzzy set.
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Son, L.H. Measuring analogousness in picture fuzzy sets: from picture distance measures to picture association measures. Fuzzy Optim Decis Making 16, 359–378 (2017). https://doi.org/10.1007/s10700-016-9249-5
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DOI: https://doi.org/10.1007/s10700-016-9249-5