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Deng entropy

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  • Deng, Yong

Abstract

Dempster Shafer evidence theory has been widely used in many applications due to its advantages to handle uncertainty. However, how to measure uncertainty in evidence theory is still an open issue. The main contribution of this paper is that a new entropy, named as Deng entropy, is presented to measure the uncertainty of a basic probability assignment (BPA). Deng entropy is the generalization of Shannon entropy since the value of Deng entropy is identical to that of Shannon entropy when the BPA defines a probability measure. Numerical examples are illustrated to show the efficiency of Deng entropy.

Suggested Citation

  • Deng, Yong, 2016. "Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 549-553.
    • Handle: RePEc:eee:chsofr:v:91:y:2016:i:c:p:549-553
    DOI: 10.1016/j.chaos.2016.07.014
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    References listed on IDEAS

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    1. Kabir, Golam & Tesfamariam, Solomon & Francisque, Alex & Sadiq, Rehan, 2015. "Evaluating risk of water mains failure using a Bayesian belief network model," European Journal of Operational Research, Elsevier, vol. 240(1), pages 220-234.
    2. Deng, Xinyang & Deng, Yong, 2014. "On the axiomatic requirement of range to measure uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 163-168.
    3. Wen Jiang & Jun Zhan & Deyun Zhou & Xin Li, 2016. "A Method to Determine Generalized Basic Probability Assignment in the Open World," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-11, May.
    4. Fu, Chao & Yang, Jian-Bo & Yang, Shan-Lin, 2015. "A group evidential reasoning approach based on expert reliability," European Journal of Operational Research, Elsevier, vol. 246(3), pages 886-893.
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