This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Shafer, G. A Mathematical Theory of Evidence. Princeton University Press, 1976.Search in Google Scholar
Dubois, D., H. Prade. A Set-Theoretic View of Belief Functions: Logical Operations and Approximations by Fuzzy Sets. – Int. J. of General Systems, Vol. 12, 1986, pp. 193-226.Search in Google Scholar
Yager, R. On the Maximum Entropy Negation of a Probability Distribution. – IEEE Trans. on Fuzzy Systems, Vol. 23, October 2015, No 5, pp. 1899-1902.Search in Google Scholar
Dezert, J. An Effective Measure of Uncertainty of Basic Belief Assignments. – In: Proc. of Fusion 2022 Conf., Linköping, Sweden, July, 2022, pp. 1-10.Search in Google Scholar
Dezert, J., A. Tchamova. On Effectiveness of Measures of Uncertainty of Basic Belief Assignments. – Information & Security International Journal, Vol. 52, February 2022.Search in Google Scholar
Shannon, C. E. A Mathematical Theory of Communication. – The Bell System Technical Journal, Vol. 27, July & October 1948, pp. 379-423 & 623-656 (reprinted in [7]).Search in Google Scholar
N. J. A. Sloane, A. D. Wyner, Eds. Claude Elwood Shannon – Collected Papers. – IEEE Press, 1993. 924 p.Search in Google Scholar
Batyrshin, I. Z., N. I. Kubysheva, V. R. Bayrasheva, O. Kosheleva, V. Kreinovich. Negations of Probability Distributions: A Survey. – Computer Systems Ecatepes (Computacion y Sistemas de Ecatepes), Vol. 25, 2021, No 4, pp. 775-781.Search in Google Scholar
Srivastava, A., S. Maheshwari. Some New Properties of Negation of a Probability Distribution. – Int. J. of Intelligent Systems, Vol. 33, 2018, No 6, pp. 1133-1145.Search in Google Scholar
Srivastava, A., A. L. Kaur. Uncertainty and Negation – Information Theoretic Applications. – Int. J. of Intelligent Systems, Vol. 34, 2019, No 6, pp. 1248-1260.Search in Google Scholar
Zhang, J., R. Liu, Zhang, B. Kang. Extension of Yager’s Negation of a Probability Distribution Based on Tsallis Entropy. – Int. J. of Intel. Systems, Vol. 35, 2020, No 1, pp. 72-84.Search in Google Scholar
Wu, Q., Y. Deng, N. Xiong. Exponential Negation of a Probability Distribution. – Soft Computing, Vol. 26, 2022, pp. 2147-2156.Search in Google Scholar
Yin, L., X. Deng, Y. Deng. The Negation of a Basic Probability Assignment. – IEEE Trans. Fuzzy Syst., Vol. 27, 2019, No 1, pp. 135-143.Search in Google Scholar
Gao, X., Y. Deng. The Negation of Basic Probability Assignment. – IEEE Access, Vol. 7, 2019.Search in Google Scholar
Xie, K., F. Xiao. Negation of Belief Function Based on the Total Uncertainty Measure. – Entropy, Vol. 21, 2019, No 1, pp. 73.Search in Google Scholar
Deng, X., W. Jiang. On the Negation of a Dempster-Shafer Belief Structure Based on Maximum Uncertainty Allocation. – Information Sciences, Vol. 516, 2020, pp. 346-352.Search in Google Scholar
Batyrshin, L. Z. Contracting and Involutory Negations of Probability Distributions. – Mathematics, Vol. 9, 2389. arXiv preprint arXiv:2103.16176, 2021.Search in Google Scholar
Batyrshin, L. Z, et al. Generating Negations of Probability Distributions. – Soft Computing, Vol. 25, 2021, pp. 7929-7935.Search in Google Scholar
Liu, R., Y. Deng, Z. Li. The Maximum Entropy Negation of Basic Probability Assignment. – Soft Computing, 2023 (published online 12 April 2023).Search in Google Scholar
F. Smarandache, J. Dezert, Eds. Advances and Applications of DSmT for Information Fusion (Collected Works). – ARP, Vol. 2-4, 2006, 2009 & 2015.Search in Google Scholar
Dezert, T., J. Dezert, F. Smarandache. Improvement of Proportional Conflict Redistribution Rules of Combination of Basic Belief Assignments. – Journal of Advances in Information Fusion (JAIF), Vol. 16, June 2021, No 1.Search in Google Scholar
Smarandache, F. A In-Depth Look at Quantitative Information Fusion Rules, Chap. 8 of [23], June 2009, Vol. 2, pp. 205-236.Search in Google Scholar
Zadeh, L. A. On the Validity of Dempster’s Rule of Combination. – In: Memo M79/24, Univ. of California, Berkeley, U.S.A., 1979.Search in Google Scholar
Dezert, J., P. Wang, A. Tchamova. On the Validity of Dempster-Shafer Theory. – In: Proc. of 15th Int. Conf. on Information Fusion, Singapore, 9-12 July 2012, pp. 655-660.Search in Google Scholar
Dezert, J., A. Tchamova, D. Han. Total Belief Theorem and Generalized Bayes’ Theorem. – In: Proc. of Fusion 2018 Conf., Cambridge, UK, 10-13 July 2018.Search in Google Scholar
Tchamova, A., J. Dezert. On the Behavior of Dempster’s Rule of Combination and the Foundations of Dempster-Shafer Theory. – IEEE IS’2012, Sofia, Bulgaria, 6-8 September, 2012.Search in Google Scholar
Smarandache, F., J. Dezert, A. Tchamova. Examples where Dempster’s Rule is Insensitive to the Conflict Level between the Sources of Evidence. – Octogon Mathematical Magazine, Vol. 25, 2017, No 2, pp. 284-290.Search in Google Scholar
Blackman, S., R. Popoli. Design and Analysis of Modern Tracking Systems. AH, 1986.Search in Google Scholar
Tchamova, A., J. Dezert, F. Smarandache. New Fusion Rules for Solving Blackman’s Association Problem. Chap 15 of [23], Vol. 3, 2009, pp. 425-436.Search in Google Scholar
Dezert, J., D. Han, J.-M. Tacnet, S. Carladous, Y. Yang. Decision-Making with Belief Interval Distance. – In: Proc. of Belief 2016 Int. Conf., Prague, CZ, 2016 pp. 21-23.Search in Google Scholar