A generalized divergence of information volume and its applications

Ali, 2012, A new combination rule for conflict problem of Dempster-Shafer evidence theory, Int. J. Energy Inf. Commun., 3, 35 Atanassov, 1986, Intuitionistic fuzzy sets, vol. 20, 87 Buono, 2020, A dual measure of uncertainty: The deng extropy, Entropy, 22, 582, 10.3390/e22050582 Cao, 2019, Multi-channel EEG recordings during a sustained-attention driving task, Sci. Data, 6, 10.1038/s41597-019-0027-4 Capuano, 2017, Fuzzy group decision making with incomplete information guided by social influence, IEEE Trans. Fuzzy Syst., 26, 1704, 10.1109/TFUZZ.2017.2744605 Chen, 2021, Probability transformation of mass function: A weighted network method based on the ordered visibility graph, Eng. Appl. Artif. Intell., 105, 10.1016/j.engappai.2021.104438 Chen, 2021, Resilience assessment of regional areas against earthquakes using multi-source information fusion, Reliab. Eng. Syst. Saf., 10.1016/j.ress.2021.107833 Dang, 2019, Multiple kernel collaborative fuzzy clustering algorithm with weighted super-pixels for satellite image land-cover classification, Eng. Appl. Artif. Intell., 85, 85, 10.1016/j.engappai.2019.05.004 Dempster, 1966 Deng, 2020, Information volume of mass function, Int. J. Comput. Commun. Control, 15, 3983, 10.15837/ijccc.2020.6.3983 Deng, 2021, Uncertainty measure in evidence theory, Sci. China Inf. Sci., 64 Deng, 2021, An ECR-pcr rule for fusion of evidences defined on a non-exclusive framework of discernment, Chin. J. Aeronaut. Deng, 2021, Information volume of fuzzy membership function, Int. J. Comput. Commun. Control, 16, 4106, 10.15837/ijccc.2021.1.4106 Deng, 2021, Combining conflicting evidence based on pearson correlation coefficient and weighted graph, Int. J. Intell. Syst., 10.1002/int.22593 Ding, 2021, An unsupervised fuzzy clustering approach for early screening of COVID-19 from radiological images, IEEE Trans. Fuzzy Syst. Dzitac, 2017, Fuzzy logic is not fuzzy: World-renowned computer scientist lotfi a. zadeh, Int. J. Comput. Commun. Control, 12, 748, 10.15837/ijccc.2017.6.3111 Fan, 2018, Evidence reasoning for temporal uncertain information based on relative reliability evaluation, Expert Syst. Appl., 113, 264, 10.1016/j.eswa.2018.06.048 Fu, 2020, Comparison of evidential reasoning algorithm with linear combination in decision making, Int. J. Fuzzy Syst., 22, 686, 10.1007/s40815-019-00746-3 Gao, 2021, Generating method of pythagorean fuzzy sets from the negation of probability, Eng. Appl. Artif. Intell., 105, 10.1016/j.engappai.2021.104403 Gao, 2021, Quantum pythagorean fuzzy evidence theory (qpfet): A negation of quantum mass function view, IEEE Trans. Fuzzy Syst. Gao, 2021, Dependence assessment in human reliability analysis under uncertain and dynamic situations, Nuclear Engineering and Technology Gao, 2021, Information volume fractal dimension, Fractals, 10.1142/S0218348X21502637 Gou, 2017, Hesitant fuzzy linguistic entropy and cross-entropy measures and alternative queuing method for multiple criteria decision making, Inform. Sci., 388, 225, 10.1016/j.ins.2017.01.033 Han, 2014, Evaluations of evidence combination rules in terms of statistical sensitivity and divergence, 1 Huang, 2021, Basic probability assignment to probability distribution function based on the Shapley value approach, Int. J. Intell. Syst., 36, 4210, 10.1002/int.22456 Jaynes, 2003 Jiang, 2018, A correlation coefficient for belief functions, Internat. J. Approx. Reason., 103, 94, 10.1016/j.ijar.2018.09.001 Jiang, 2021, Multi-scale metric learning for few-shot learning, IEEE Trans. Circuits Syst. Video Technol., 31, 1091, 10.1109/TCSVT.2020.2995754 Jousselme, 2001, A new distance between two bodies of evidence, Inf. Fusion, 2, 91, 10.1016/S1566-2535(01)00026-4 Kamacı, 2021, Linguistic single-valued neutrosophic soft sets with applications in game theory, Int. J. Intell. Syst., 10.1002/int.22445 Kazemi, 2021, Fractional deng entropy and extropy and some applications, Entropy, 23, 623, 10.3390/e23050623 Khalaj, 2020, New definition of the cross entropy based on the Dempster-Shafer theory and its application in a decision-making process, Comm. Statist. Theory Methods, 49, 909, 10.1080/03610926.2018.1554123 Khan, 2021, Applications of improved spherical fuzzy dombi aggregation operators in decision support system, Soft Comput., 25, 9097, 10.1007/s00500-021-05829-8 Li, 2021, A consensus model to manage the non-cooperative behaviors of individuals in uncertain group decision making problems during the COVID-19 outbreak, Appl. Soft Comput., 99, 10.1016/j.asoc.2020.106879 Liao, 2020, A deng-entropy-based evidential reasoning approach for multi-expert multi-criterion decision-making with uncertainty, Int. J. Comput. Intell. Syst., 13, 1281, 10.2991/ijcis.d.200814.001 Lin, 1991, Divergence measures based on the Shannon entropy, IEEE Trans. Inform. Theory, 37, 145, 10.1109/18.61115 Liu, 2020, Evidence combination based on credal belief redistribution for pattern classification, IEEE Trans. Fuzzy Syst., 28, 618, 10.1109/TFUZZ.2019.2911915 Liu, 2021, A transfer classification method for heterogeneous data based on evidence theory, IEEE Trans. Syst. Man Cybern. Syst., 51, 5129, 10.1109/TSMC.2019.2945808 Liu, 2021, Combination of classifiers with different frames of discernment based on belief functions, IEEE Trans. Fuzzy Syst., 29, 1764, 10.1109/TFUZZ.2020.2985332 Marchau, 2019 Miyamoto, 2012 Murphy, 2000, Combining belief functions when evidence conflicts, Decis. Support Syst., 29, 1, 10.1016/S0167-9236(99)00084-6 Ng, 2020, Investigating consumer preferences on product designs by analyzing opinions from social networks using evidential reasoning, Comput. Ind. Eng., 139, 10.1016/j.cie.2019.106180 Pan, 2021, The constrained pythagorean fuzzy sets and its similarity measure, IEEE Trans. Fuzzy Syst. Pawlak, 1982, Rough sets, Int. J. Comput. Inf. Sci., 11, 341, 10.1007/BF01001956 Rani, 2020, A novel approach to extended fuzzy TOPSIS based on new divergence measures for renewable energy sources selection, J. Cleaner Prod., 257, 10.1016/j.jclepro.2020.120352 Roquel, 2014, Decomposition of conflict as a distribution on hypotheses in the framework on belief functions, Internat. J. Approx. Reason., 55, 1129, 10.1016/j.ijar.2013.12.006 Shafer, 1976 Song, 2021, Entropic explanation of power set, Int. J. Comput. Commun. Control, 16, 4413, 10.15837/ijccc.2021.4.4413 Song, 2019, Divergence-based cross entropy and uncertainty measures of atanassov’s intuitionistic fuzzy sets with their application in decision making, Appl. Soft Comput., 84, 10.1016/j.asoc.2019.105703 Song, 2020, Self-adaptive combination method for temporal evidence based on negotiation strategy, Sci. China Inf. Sci., 63, 1, 10.1007/s11432-020-3045-5 de Souza, 2019, A novel approach for optimum-path forest classification using fuzzy logic, IEEE Trans. Fuzzy Syst., 28, 3076, 10.1109/TFUZZ.2019.2949771 Tian, 2021, Using Z-number to measure the reliability of new information fusion method and its application in pattern recognition, Appl. Soft Comput., 111, 10.1016/j.asoc.2021.107658 Tuğal, 2019, Comparisons of karcı and Shannon entropies and their effects on centrality of social networks, Physica A, 523, 352, 10.1016/j.physa.2019.02.026 Versaci, 2021, Image edge detection: A new approach based on fuzzy entropy and fuzzy divergence, Int. J. Fuzzy Syst., 1 Vylegzhanin, 2019, Fuzzy logic alghorithms for target classification in radar observations, 1 Wang, 2021, A new belief divergence measure for Dempster–Shafer theory based on belief and plausibility function and its application in multi-source data fusion, Eng. Appl. Artif. Intell., 97, 10.1016/j.engappai.2020.104030 Wang, 2021, Feature-based evidential reasoning for probabilistic risk analysis and prediction, Eng. Appl. Artif. Intell., 102, 10.1016/j.engappai.2021.104237 Wen, 2012, A new dsmt combination rule in open frame of discernment and its application, Sci. China Inf. Sci., 55, 551, 10.1007/s11432-011-4532-0 Wong, 1985, Entropy and distance of random graphs with application to structural pattern recognition, IEEE Trans. Pattern Anal. Mach. Intell., 599, 10.1109/TPAMI.1985.4767707 Xiao, 2019, Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy, Inf. Fusion, 46, 23, 10.1016/j.inffus.2018.04.003 Xiao, 2020, Evidence combination based on prospect theory for multi-sensor data fusion, ISA Trans., 106, 253, 10.1016/j.isatra.2020.06.024 Xiao, 2021, CaFtR: A Fuzzy complex event processing method, Int. J. Fuzzy Syst. Xiao, 2021, CEQD: A Complex mass function to predict interference effects, IEEE Trans. Cybern. Xiao, 2021, A distance measure for intuitionistic fuzzy sets and its application to pattern classification problems, IEEE Trans. Syst. Man Cybern. Syst., 51, 3980, 10.1109/TSMC.2019.2958635 Xiong, 2021, Conflicting evidence combination from the perspective of networks, Inform. Sci., 580, 408, 10.1016/j.ins.2021.08.088 Xu, 2018, A belief rule-based evidence updating method for industrial alarm system design, Control Eng. Pract., 81, 73, 10.1016/j.conengprac.2018.09.001 Yager, 2018, Decision making under measure-based granular uncertainty, Granul. Comput., 3, 345, 10.1007/s41066-017-0075-0 Yager, 2013, Pythagorean membership grades, complex numbers, and decision making, Int. J. Intell. Syst., 28, 436, 10.1002/int.21584 Yasmin, 2020, Graph based feature selection investigating boundary region of rough set for language identification, Expert Syst. Appl., 158, 10.1016/j.eswa.2020.113575 Zadeh, 1986, A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination, AI Mag., 7, 85 Zadeh, 1996, Fuzzy sets, 394 Zhao, 2021, Complex network modeling of evidence theory, IEEE Trans. Fuzzy Syst., 29, 3470, 10.1109/TFUZZ.2020.3023760 Zhou, 2020, Assignment of attribute weights with belief distributions for madm under uncertainties, Knowl.-Based Syst., 189, 10.1016/j.knosys.2019.105110