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A Stampede Fault Diagnosis Analysis Method of Scenic Spots Based on Interval Type-2 Intuitionistic Fuzzy Bayesian Networks

Author

Listed:
  • Lin Pingping

    (School of Economics and Management, Minjiang University, China)

  • Yu Gao-Feng

    (School of Business Administration, Fujian Business University, China)

  • Shi Ting-Ting

    (School of Economics and Management, Minjiang University, China)

Abstract

In order to diagnose the root causes of stampede accident in scenic spots under uncertainty, this paper proposes an interval type-2 intuitionistic fuzzy Bayesian network (BN) method, which includes four steps. First, interval type-2 trapezoidal intuitionistic fuzzy numbers are used to express experts' cognitive judgments about probability information of root nodes. Second, fuzzy possibility-probability transformation functions are extended to obtain the prior probability of root nodes. Third, BN deductive reasoning is conducted to obtain the occurrence probability of the top event. Last, BN abductive reasoning is performed to conduct BN probability updating analysis and important analysis. The proposed approach was implemented in an empirical study of the Mount Hua scenic spot in China. The results showed the overcrowding of tourists, poor management of tourist diversion, and tourists' psychological panic are the main root causes. These findings can offer insightful suggestions for alleviating tourist stampede risk in the Mount Hua scenic spot.

Suggested Citation

  • Lin Pingping & Yu Gao-Feng & Shi Ting-Ting, 2026. "A Stampede Fault Diagnosis Analysis Method of Scenic Spots Based on Interval Type-2 Intuitionistic Fuzzy Bayesian Networks," International Journal of Fuzzy System Applications (IJFSA), IGI Global Scientific Publishing, vol. 15(1), pages 1-40, January.
    • Handle: RePEc:igg:jfsa00:v:15:y:2026:i:1:p:1-40
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