IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v91y2016icp549-553.html
   My bibliography  Save this article

Deng entropy

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077916302363
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2016.07.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    2. Iman Moslehi & Mohammadreza Jalili_Ghazizadeh, 2020. "Pressure-Pipe Breaks Relationship in Water Distribution Networks: A Statistical Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2851-2868, July.
    3. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    4. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    5. Zhang, Qi & Luo, Chuanhai & Li, Meizhu & Deng, Yong & Mahadevan, Sankaran, 2015. "Tsallis information dimension of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 707-717.
    6. Deyun Zhou & Yongchuan Tang & Wen Jiang, 2017. "An Improved Belief Entropy and Its Application in Decision-Making," Complexity, Hindawi, vol. 2017, pages 1-15, March.
    7. Xue, Min & Fu, Chao & Yang, Shan-Lin, 2020. "Group consensus reaching based on a combination of expert weight and expert reliability," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    8. Liguo Fei & Jun Xia & Yuqiang Feng & Luning Liu, 2019. "A novel method to determine basic probability assignment in Dempster–Shafer theory and its application in multi-sensor information fusion," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
    9. Zhang, Zhi-Gang & Hu, Xiao & Liu, Zhao-Ting & Zhao, Lu-Tao, 2021. "Multi-attribute decision making: An innovative method based on the dynamic credibility of experts," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    10. Dawid Szpak, 2020. "Method for Determining the Probability of a Lack of Water Supply to Consumers," Energies, MDPI, vol. 13(20), pages 1-16, October.
    11. Quan, Ji & Zhou, Yawen & Wang, Xianjia & Yang, Jian-Bo, 2020. "Information fusion based on reputation and payoff promotes cooperation in spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    12. Robles-Velasco, Alicia & Cortés, Pablo & Muñuzuri, Jesús & Onieva, Luis, 2020. "Prediction of pipe failures in water supply networks using logistic regression and support vector classification," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    13. Ran Fang & Huchang Liao, 2021. "Emergency material reserve location selection by a time-series-based evidential reasoning approach under bounded rationality," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1397-1417, August.
    14. Ramos-Salgado, Cristóbal & Muñuzuri, Jesús & Aparicio-Ruiz, Pablo & Onieva, Luis, 2022. "A comprehensive framework to efficiently plan short and long-term investments in water supply and sewer networks," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    15. Kabir, Golam & Tesfamariam, Solomon & Sadiq, Rehan, 2015. "Predicting water main failures using Bayesian model averaging and survival modelling approach," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 498-514.
    16. Zhao, Lu-Tao & Liu, Zhao-Ting & Cheng, Lei, 2021. "How will China's coal industry develop in the future? A quantitative analysis with policy implications," Energy, Elsevier, vol. 235(C).
    17. Chao Fu & Weiyong Liu & Wenjun Chang, 2020. "Data-driven multiple criteria decision making for diagnosis of thyroid cancer," Annals of Operations Research, Springer, vol. 293(2), pages 833-862, October.
    18. Min Xue & Chao Fu & Shan-Lin Yang, 2021. "Dynamic Expert Reliability Based Feedback Mechanism in Consensus Reaching Process with Distributed Preference Relations," Group Decision and Negotiation, Springer, vol. 30(2), pages 341-375, April.
    19. Yutong Chen & Yongchuan Tang, 2021. "An Improved Approach of Incomplete Information Fusion and Its Application in Sensor Data-Based Fault Diagnosis," Mathematics, MDPI, vol. 9(11), pages 1-16, June.
    20. Vijayta Fulzele & Ravi Shankar, 2023. "Performance measurement of sustainable freight transportation: a consensus model and FERA approach," Annals of Operations Research, Springer, vol. 324(1), pages 501-542, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:91:y:2016:i:c:p:549-553. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.