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A Method to Determine Generalized Basic Probability Assignment in the Open World

Author

Listed:
  • Wen Jiang
  • Jun Zhan
  • Deyun Zhou
  • Xin Li

Abstract

Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to ; otherwise the BPA of unknown target is equal to minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:hin:jnlmpe:3878634
    DOI: 10.1155/2016/3878634
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    Cited by:

    1. 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.
    2. Zhu, Weidong & Zhang, Tianjiao & Wu, Yong & Li, Shaorong & Li, Zhimin, 2022. "Research on optimization of an enterprise financial risk early warning method based on the DS-RF model," International Review of Financial Analysis, Elsevier, vol. 81(C).
    3. Deng, Yong, 2016. "Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 549-553.
    4. 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.

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