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Complexity
Volume 2017, Article ID 4359195, 15 pages
https://doi.org/10.1155/2017/4359195
Research Article

An Improved Belief Entropy and Its Application in Decision-Making

School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China

Correspondence should be addressed to Yongchuan Tang; nc.ude.upwn.liam@nauhcgnoygnat and Wen Jiang; nc.ude.upwn@newgnaij

Received 22 December 2016; Accepted 23 January 2017; Published 16 March 2017

Academic Editor: Jurgita Antucheviciene

Copyright © 2017 Deyun Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • Ying Wu, “Fault diagnosis of civil aircraft electrical system based on evidence theory,” 2017 20th International Conference on Information Fusion (Fusion), pp. 1–7, . View at Publisher · View at Google Scholar
  • Yongchuan Tang, Xueyi Fang, Deyun Zhou, and Xiaofeng Lv, “Weighted deng entropy and its application in uncertainty measure,” 2017 20th International Conference on Information Fusion (Fusion), pp. 1–5, . View at Publisher · View at Google Scholar
  • Yongchuan Tang, Deyun Zhou, Zichang He, and Shuai Xu, “An improved belief entropy–based uncertainty management approach for sensor data fusion,” International Journal of Distributed Sensor Networks, vol. 13, no. 7, pp. 155014771771849, 2017. View at Publisher · View at Google Scholar
  • Yongchuan Tang, Deyun Zhou, and Felix T. S. Chan, “Extending Deng Entropy to the Open World in the Evidence Theory,” 2018 21st International Conference on Information Fusion, FUSION 2018, pp. 629–634, 2018. View at Publisher · View at Google Scholar
  • Yongchuan Tang, Deyun Zhou, and Felix Chan, “An Extension to Deng’s Entropy in the Open World Assumption with an Application in Sensor Data Fusion,” Sensors, vol. 18, no. 6, pp. 1902, 2018. View at Publisher · View at Google Scholar
  • Kajal Chatterjee, Edmundas Kazimieras Zavadskas, Jolanta Tamošaitienė, Krishnendu Adhikary, and Samarjit Kar, “A Hybrid MCDM Technique for Risk Management in Construction Projects,” Symmetry, vol. 10, no. 2, pp. 46, 2018. View at Publisher · View at Google Scholar
  • Xuelian Zhou, and Yongchuan Tang, “Modeling and Fusing the Uncertainty of FMEA Experts Using an Entropy-Like Measure with an Application in Fault Evaluation of Aircraft Turbine Rotor Blades,” Entropy, vol. 20, no. 11, pp. 864, 2018. View at Publisher · View at Google Scholar
  • Yongchuan Tang, Deyun Zhou, and Felix T. S. Chan, “AMWRPN: Ambiguity measure weighted risk priority number model for failure mode and effects analysis,” IEEE Access, pp. 1–1, 2018. View at Publisher · View at Google Scholar
  • Ying Zhou, Yongchuan Tang, and Xiaozhe Zhao, “A Novel Uncertainty Management Approach for Air Combat Situation Assessment Based on Improved Belief Entropy,” Entropy, vol. 21, no. 5, pp. 495, 2019. View at Publisher · View at Google Scholar
  • Qian Pan, Deyun Zhou, Yongchuan Tang, Xiaoyang Li, and Jichuan Huang, “A Novel Belief Entropy for Measuring Uncertainty in Dempster-Shafer Evidence Theory Framework Based on Plausibility Transformation and Weighted Hartley Entropy,” Entropy, vol. 21, no. 2, pp. 163, 2019. View at Publisher · View at Google Scholar