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Sequential 3WD-based local optimal scale selection in dynamic multi-scale decision information systems

Published: 01 January 2023 Publication History
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  • Abstract

    The multi-scale decision information system (MDIS) is a typical granular computing model. In the research of MDIS, uncertainty is an important factor in making decision analysis, and the selection of optimal scale is a core problem. Therefore, the uncertainty of decision is an important factor in the scale selection. With the rapid increase of data size, the amount of feature information will increase greatly, and the uncertainty of the system will become more and more complex, which makes the optimal scale selection more difficult. The purpose of this study is to investigate the updating law of the local optimal scale under the condition of the dynamic increase of objects. The criterion of scale selection is to keep the uncertainty of the system unchanged. Firstly, the updating law of uncertainty for the decision class in a decision information system under the case of object increment is explored. Secondly, the definition of local optimal scale which keeps the uncertainty of decision classes is given by the sequential three-way decision theory, and the updating law of optimal scale is given by using the updating mechanism of the uncertainty of decision classes. Finally, experiments are conducted to verify the correctness and effectiveness of the proposed method in the calculation of local optimal scale by comparing the algorithms for adding multiple objects directly and adding objects one by one.

    References

    [1]
    J.H. Li, C.C. Huang, J.J. Qi, Y.H. Qian, W.Q. Liu, Three way cognitive concept learning via multi-granularity, Inf. Sci. 378 (2017) 244–263,.
    [2]
    Z.H. Huang, J.J. Li, Y.H. Qian, Noise-tolerant fuzzy β covering based multigranulation rough sets and feature subset selection, IEEE Trans. Fuzzy Syst. 30 (7) (2022) 2721–2735,.
    [3]
    X.R. Zhao, B.Q. Hu, Three-way decisions with decision-theoretic rough sets in multiset-valued information tables, Inf. Sci. 507 (2020) 684–699,.
    [4]
    J.J. Niu, D.G. Chen, J.H. Li, H. Wang, A dynamic rule-based classification model via granular computing, Inf. Sci. 584 (2022) 325–341,.
    [5]
    L.A. Zadeh, Fuzzy sets and information granularity, in: Advances in Fuzzy Set Theory and Applications, North-Holland, Amsterdam, 1979, pp. 3–18,.
    [6]
    Z. Pawlak, Rough set, Int. J. Comput. Inf. Sci. 11 (1982) 341–356,.
    [7]
    X.L. Yang, H.M. Chen, T.R. Li, P.F. Zhang, C. Luo, Student-t kernelized fuzzy rough set model with fuzzy divergence for feature selection, Inf. Sci. 610 (2022) 52–72,.
    [8]
    W. Zhang, B.Q. Hu, The distributive laws of convolution operations over meet-convolution and join-convolution on fuzzy truth values, IEEE Trans. Fuzzy Syst. 29 (2) (2021) 415–426,.
    [9]
    C.Z. Wang, Y. Huang, W.P. Ding, Z.H. Cao, Attribute reduction with fuzzy rough self-information measures, Inf. Sci. 549 (2021) 68–86,.
    [10]
    B.H. Long, W.H. Xu, X.Y. Zhang, L. Yang, The dynamic update method of attribute-induced three-way granular concept in formal contexts, Int. J. Approx. Reason. 126 (2020) 228–248,.
    [11]
    Y.Y. Yao, Three-way decisions with probabilistic rough sets, Inf. Sci. 180 (3) (2010) 341–353,.
    [12]
    Y.Y. Yao, The superiority of three-way decisions in probabilistic rough set models, Inf. Sci. 181 (6) (2011) 1080–1096,.
    [13]
    Y.Y. Yao, Three-way decision and granular computing, Int. J. Approx. Reason. 103 (2018) 107–123,.
    [14]
    Y. Xing, D.Y. Li, S.G. Wang, Cost-sensitive sequential three-way decision making method, Comput. Sci. 45 (10) (2018) 107–113,.
    [15]
    W.B. Chen, Q.H. Zhang, Y.Y. Dai, Sequential multi-class three-way decisions based on cost-sensitive learning, Int. J. Approx. Reason. 146 (2022) 47–61,.
    [16]
    J.F. Luo, M.J. Hu, K.Y. Qin, Three-way decision with incomplete information based on similarity and satisfiability, Int. J. Approx. Reason. 120 (2020) 151–183,.
    [17]
    H.L. Yang, S.Y. Xue, Y.H. She, General three-way decision models on incomplete information tables, Inf. Sci. 605 (2022) 136–158,.
    [18]
    Y. Zhang, J.T. Yao, Game theoretic approach to shadowed sets: a three-way tradeoff perspective, Inf. Sci. 507 (2020) 540–552,.
    [19]
    S. Singh, J.T. Yao, Pneumonia detection with game-theoretic rough sets, in: IEEE ICMLA, vol. 507, 2021, pp. 1029–1304,.
    [20]
    X. Yang, T.R. Li, D. Liu, H.M. Chen, C. Luo, A unified framework of dynamic three-way probabilistic rough sets, Inf. Sci. 420 (2017) 126–147,.
    [21]
    Q.H. Zhang, G.X. Lv, Y.H. Chen, G.Y. Wang, Dynamic three-way decision model based on the updating of attribute values, Knowl.-Based Syst. 142 (2018) 71–84,.
    [22]
    X. Yang, D. Liu, X.B. Yang, K.Y. Liu, T.R. Li, Incremental fuzzy probability decision-theoretic approaches to dynamic three-way approximations, Inf. Sci. 550 (2021) 71–90,.
    [23]
    S.F. He, Y.M. Wang, X.H. Pan, K.S. Chin, A novel behavioral three-way decision model with application to the treatment of mild symptoms of COVID-19, Appl. Soft Comput. 25 (2022),.
    [24]
    F. Shen, Z.Y. Yang, X.C. Zhao, D. Lan, Reject inference in credit scoring using a three-way decision and safe semi-supervised support vector machine, Inf. Sci. 606 (2022) 614–627,.
    [25]
    S. Senthil Kumara, H. Hannah Inbarani, Optimistic multi-granulation rough set based classification for medical diagnosis, Proc. Comput. Sci. 47 (2015) 374–382,.
    [26]
    Y.H. Qian, S.Y. Li, J.Y. Liang, Z.Z. Shi, F. Wang, Pessimistic rough set based decisions: a multigranulation fusion strategy, Inf. Sci. 264 (2014) 196–210,.
    [27]
    J. Qian, C.H. Liu, D.Q. Miao, X.D. Yue, Sequential three-way decisions via multi-granularity, Inf. Sci. 507 (2020) 606–629,.
    [28]
    L.B. Zhang, H.X. Li, X.Z. Zhou, B. Huang, Sequential three-way decision based on multi-granular autoencoder features, Inf. Sci. 507 (2020) 630–643,.
    [29]
    Q. Hu, K.Y. Qin, L. Yang, A constructing approach to multi-granularity object-induced three-way concept lattices, Int. J. Approx. Reason. 150 (2022) 229–241,.
    [30]
    T.N. Zhao, Y.J. Zhang, D.Q. Miao, W. Pedrycz, Selective label enhancement for multi-label classification based on three-way decisions, Int. J. Approx. Reason. 150 (2022) 172–187,.
    [31]
    J. Yang, G.Y. Wang, Q.H. Zhang, Y.L. Chen, W.H. Xu, Optimal granularity selection based on cost-sensitive sequential three-way decisions with rough fuzzy sets, Knowl.-Based Syst. 163 (2019) 131–144,.
    [32]
    X.Q. Ye, D. Liu, A cost-sensitive temporal-spatial three-way recommendation with multi-granularity decision, Inf. Sci. 589 (2022) 670–689,.
    [33]
    W.Z. Wu, Y. Leung, Theory and applications of granular labelled partitions in multi-scale decision tables, Inf. Sci. 181 (18) (2011) 3878–3897,.
    [34]
    W.Z. Wu, Y. Leung, A comparison study of optimal scale combination selection in generalized multi-scale decision tables, Int. J. Mach. Learn. Cybern. 11 (2020) 961–972,.
    [35]
    F. Li, B.Q. Hu, A new approach of optimal scale selection to multi-scale decision tables, Inf. Sci. 381 (2017) 193–208,.
    [36]
    F. Li, B.Q. Hu, Stepwise optimal scale selection for multi-scale decision tables via attribute significance, Knowl.-Based Syst. 129 (2017) 4–16,.
    [37]
    J.W. Jiang, W.Z. Wu, H. Bao, A.H. Tan, Evidence theory based optimal scale selection for multi-scale ordered decision systems, Int. J. Mach. Learn. Cybern. 13 (2022) 1115–1129,.
    [38]
    Y.H. She, Z.H. Qian, X.L. He, J.T. Wang, T. Qian, W.L. Zheng, On generalization reducts in multi-scale decision tables, Inf. Sci. 555 (2021) 104–124,.
    [39]
    H. Bao, W.Z. Wu, J.W. Zheng, T.J. Li, Entropy based optimal scale combination selection for generalized multi-scale information tables, Int. J. Mach. Learn. Cybern. 12 (2021) 1427–1437,.
    [40]
    Z.H. Huang, J.J. Li, W.Z. Dai, R.D. Lin, Generalized multi-scale decision tables with multi-scale decision attributes, Int. J. Approx. Reason. 115 (2019) 194–208,.
    [41]
    W.Z. Wu, Y.H. Qian, T.J. Li, S.M. Gu, On rule acquisition in incomplete multi-scale decision tables, Inf. Sci. 378 (2017) 282–302,.
    [42]
    S.M. Gu, J.Y. Gu, W.Z. Wu, T.J. Li, C.J. Chen, Local optimal granularity selections in incomplete multi-granularity decision systems, J. Comput. Res. Dev. 54 (7) (2017) 1500–1509,.
    [43]
    W.K. Li, J.J. Li, J.X. Huang, W.Z. Dai, Matrix representation of optimal scale for generalized multi-scale decision table, J. Ambient Intell. Humaniz. Comput. 12 (2021) 8549–8559,.
    [44]
    Z.H. Huang, J.J. Li, Multi-scale covering rough sets with applications to data classification, Appl. Soft Comput. 110 (2021),.
    [45]
    Y.S. Chen, J.J. Li, R.D. Lin, D.X. Chen, Z.H. Huang, Multi-scale set value decision information system, Control Decis. 37 (2) (2022) 455–463,.
    [46]
    B. Huang, W.Z. Wu, J.J. Yan, H.X. Li, X.Z. Zhou, Inclusion measure-based multi-granulation decision-theoretic rough sets in multi-scale intuitionistic fuzzy information tables, Inf. Sci. 507 (2020) 421–448,.
    [47]
    J.P. Xie, M.H. Yang, J.H. Li, Z. Zheng, Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart city, Future Gener. Comput. Syst. 83 (2018) 564–581,.
    [48]
    Y.L. Cheng, Q.H. Zhang, G.Y. Wang, B.Q. Hu, Optimal scale selection and attribute reduction in multi-scale decision tables based on three-way decision, Inf. Sci. 541 (2020) 36–59,.
    [49]
    J. Deng, J.M. Zhan, W.Z. Wu, A three-way decision methodology to multi-attribute decision-making in multi-scale decision information systems, Inf. Sci. 568 (2021) 175–198,.
    [50]
    B. Huang, H.X. Li, G.F. Feng, C.X. Guo, D.F. Chen, Double-quantitative rough sets, optimal scale selection and reduction in multi-scale dominance IF decision tables, Int. J. Approx. Reason. 130 (2021) 170–191,.
    [51]
    C. Luo, T.R. Li, Y.Y. Huang, G.X. Guo, H. Fujita, Updating three-way decisions in incomplete multi-scale information systems, Inf. Sci. 476 (2019) 274–289,.
    [52]
    X.Q. Zhang, Q.H. Zhang, Y.L. Cheng, G.Y. Wang, Optimal scale selection by integrating uncertainty and cost sensitive learning in multi-scale decision tables, Int. J. Mach. Learn. Cybern. 11 (2020) 1095–1114,.
    [53]
    C. Hao, J.H. Li, M. Fan, W.Q. Liu, E.C.C. Tsang, Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions, Inf. Sci. 415–416 (2017) 213–232,.
    [54]
    Y.S. Chen, J.H. Li, J.J. Li, R.D. Lin, D.X. Chen, A further study on optimal scale selection in dynamic multi scale decision information systems based on sequential three way decisions, Int. J. Mach. Learn. Cybern. 13 (2022) 1505–1515,.

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              Published In

              cover image International Journal of Approximate Reasoning
              International Journal of Approximate Reasoning  Volume 152, Issue C
              Jan 2023
              470 pages

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              Elsevier Science Inc.

              United States

              Publication History

              Published: 01 January 2023

              Author Tags

              1. Sequential three-way decisions
              2. Multi-scale decision information systems
              3. Local optimal scale
              4. Dynamic updating

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