Multiple multidimensional linguistic reasoning algorithm based on property-oriented linguistic concept lattice
暂无分享,去创建一个
Hui Cui | Li Zou | Guanli Yue | Ansheng Deng | Xin Liu | Xin Liu | L. Zou | Ansheng Deng | Guanli Yue | Hui Cui
[1] Huifang Deng,et al. Using Fuzzy Concept Lattice for Intelligent Disease Diagnosis , 2017, IEEE Access.
[2] A. Tye,et al. Bayesian population correlation: A probabilistic approach to inferring and comparing population distributions for detrital zircon ages , 2019, Chemical Geology.
[3] L. A. ZADEH,et al. The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..
[4] Andrzej Skowron,et al. Rudiments of rough sets , 2007, Inf. Sci..
[5] Ming-Wen Shao,et al. The construction of attribute (object)-oriented multi-granularity concept lattices , 2020, Int. J. Mach. Learn. Cybern..
[6] Philipp Slusallek,et al. Introduction to real-time ray tracing , 2005, SIGGRAPH Courses.
[7] Bernhard Ganter,et al. Formal Concept Analysis: Mathematical Foundations , 1998 .
[8] Francisco Herrera,et al. Hesitant Fuzzy Linguistic Term Sets for Decision Making , 2012, IEEE Transactions on Fuzzy Systems.
[9] Zaili Yang,et al. Use of Fuzzy Risk Assessment in FMEA of Offshore Engineering Systems , 2015 .
[10] Bo Li,et al. Attribute reduction and rule acquisition of formal decision context based on object (property) oriented concept lattices , 2019, Int. J. Mach. Learn. Cybern..
[11] Junzo Watada,et al. Gaussian-PSO with fuzzy reasoning based on structural learning for training a Neural Network , 2016, Neurocomputing.
[12] Yee Leung,et al. Knowledge acquisition in incomplete information systems: A rough set approach , 2006, Eur. J. Oper. Res..
[13] Keyun Qin,et al. Three-way decision with incomplete information based on similarity and satisfiability , 2020, Int. J. Approx. Reason..
[14] Lotfi A. Zadeh,et al. Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..
[15] C. Guedes Soares,et al. Incorporating evidential reasoning and TOPSIS into group decision-making under uncertainty for handling ship without command , 2018, Ocean Engineering.
[16] Prem Kumar Singh,et al. Object and attribute oriented m-polar fuzzy concept lattice using the projection operator , 2018, Granular Computing.
[17] E. H. Mamdani,et al. Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis , 1976, IEEE Transactions on Computers.
[18] Huilai Zhi,et al. Three-way dual concept analysis , 2019, Int. J. Approx. Reason..
[19] Branko Ristic,et al. A tutorial on uncertainty modeling for machine reasoning , 2020, Inf. Fusion.
[20] Rafael Peñaloza,et al. Algorithms for reasoning in very expressive description logics under infinitely valued Gödel semantics , 2017, Int. J. Approx. Reason..
[21] Jian-Min Ma,et al. Concept acquisition approach of object-oriented concept lattices , 2017, Int. J. Mach. Learn. Cybern..
[22] Xin Wen,et al. Linguistic truth-valued intuitionistic fuzzy reasoning with applications in human factors engineering , 2016, Inf. Sci..
[23] Xizhao Wang,et al. Comparison of reduction in formal decision contexts , 2017, Int. J. Approx. Reason..
[24] Zhiwei Zhao,et al. Multiple multidimensional fuzzy reasoning algorithm based on neural network , 2018, J. Intell. Fuzzy Syst..
[25] Juan Carlos Augusto,et al. A group decision making model for partially ordered preference under uncertainty , 2015, Inf. Fusion.
[26] Jinhai Li,et al. Granule description based knowledge discovery from incomplete formal contexts via necessary attribute analysis , 2019, Inf. Sci..
[27] Jinhai Li,et al. Incomplete decision contexts: Approximate concept construction, rule acquisition and knowledge reduction , 2013, Int. J. Approx. Reason..
[28] Huawen Liu,et al. Unified forms of fully implicational restriction methods for fuzzy reasoning , 2007, Inf. Sci..
[29] Prem Kumar Singh,et al. M-polar Fuzzy Graph Representation of Concept Lattice , 2018, Eng. Appl. Artif. Intell..
[30] Ming-Wen Shao,et al. Attribute reduction in generalized one-sided formal contexts , 2017, Inf. Sci..
[31] Xiao Zhang,et al. Rule-preserved object compression in formal decision contexts using concept lattices , 2014, Knowl. Based Syst..
[32] Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .
[33] Yiyu Yao,et al. Concept lattices in rough set theory , 2004, IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04..
[34] Yiming Cao,et al. A method of multimedia teaching evaluation based on fuzzy linguistic concept lattice , 2019, Multimedia Tools and Applications.
[35] Zhi-Hua Zhou,et al. Abductive learning: towards bridging machine learning and logical reasoning , 2019, Science China Information Sciences.
[36] Tao Zhang,et al. Incremental concept-cognitive learning based on attribute topology , 2020, Int. J. Approx. Reason..
[37] Lotfi A. Zadeh,et al. The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .
[38] Francisco Herrera,et al. Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions , 2018, Knowl. Based Syst..
[39] Witold Pedrycz,et al. Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system , 2017, Int. J. Approx. Reason..