Fuzzy Risk Analysis Vs. Probability Risk Analysis

  • Chongfu Huang
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 76)


In this chapter, we discuss the essential difference between fuzzy risk analysis and probability risk analysis. Then, we use the method of the information distribution to improve probability estimate in the probability risk analysis, and we develop the method to calculate the fuzzy risk with respect to the possibility-probability. The benefit of fuzzy risk assessment is that the new result saves more information for risk management.


Risk Analysis Fuzzy Number Information Diffusion Information Distribution Frequency Histogram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    C.B. Brown, A fuzzy safety measure, J. Engineering Mechanics 105 (1979), 855–872.Google Scholar
  2. [2]
    Chongfu Huang and Da Ruan, Information diffusion principle and application in fuzzy neuron, Fuzzy Logic Foundations and Industrial Applications (edited by Da Ruan, Kluwer Academic Publishers, Massachusetts, 1996 ), 165–189.Google Scholar
  3. [3]
    D.P. Clement, Fuzzy Ratings for Computer Security Evaluation, Ph.D. Dissertation, University of California at Berkeley (1977).Google Scholar
  4. [4]
    M. Delgado, J.L. Verdegay and M.A. Vila, A model for linguistic partial information in decision-making problems, International Journal of Intelligent Systems, 9 (1994), 365–378.CrossRefGoogle Scholar
  5. [5]
    W.M. Dong and et al., Fuzzy computation in risk and decision analysis, Civil Engineering Systems 2 (1986), 201–208.CrossRefGoogle Scholar
  6. [6]
    A.O. Esogbue and et al., On the application of fuzzy sets theory to the optimal flood control problem arising in water resources systems, Fuzzy Sets and Systems 48 (1992), 155–172.CrossRefGoogle Scholar
  7. [7]
    F.C. Hadipriono, A rule-based fuzzy logic deduction technique for damage assessment of protective structures, Fuzzy Sets and Systems 44 (1991), 459–468.CrossRefGoogle Scholar
  8. [8]
    L.J. Hoffman, E.H. Michelmen and D.P. Clements, SEURAT—Security evaluation and analysis using fuzzy metrics, Proc. of the 1978 National Computer Conference (AFIPS Press, Montvale, New Jersey, 1978 ) 47, 531–540.Google Scholar
  9. [9]
    Huang Chongfu, Principle of information diffusion, Fuzzy Sets and Systems, 91 (1) (1997), 69–90.CrossRefGoogle Scholar
  10. [10]
    Huang Chongfu, Concepts and methods of fuzzy risk analysis, Proceedings of the First China-Japan Conference on Risk Assessment and Manage-ment,Beijing, China, November, 1998, 12–23.Google Scholar
  11. [11]
    Huang Chongfu and Shi Peijun, Fuzzy risk and calculation, Proceedings of 18th International Conference of the North American Fuzzy Information Processing Society, (1999), 90–94Google Scholar
  12. [12]
    M. Jablonowski, Fuzzy risk analysis: using AI system, AI Expert, 9 (12) (1994), 34–37.Google Scholar
  13. [13]
    Huang Chongfu, Fuzzy risk assessment of urban natural hazards, Fuzzy Sets and Systems, 83 (1996), 271–282CrossRefGoogle Scholar
  14. [14]
    E.E. Kerre, Fuzzy Sets and Approximate Reasoning (Xian Jiaotong University Press, Xian, China, 1999 ).Google Scholar
  15. [15]
    R. V. Kolluru, S. M. Bartell, R.M., Pitblado, and R. S. Stricoff, Risk Assessment and Management Handbook for Environmental, Health, and Safety Professionals ( McGraw-Hill, New York, 1996 )Google Scholar
  16. [16]
    A.V. Machias and G.D. Skikos, Fuzzy risk index of wind sites, IEEE Trans. Energy Conversion, 7 (4) (1992), 638–643.CrossRefGoogle Scholar
  17. [17]
    A.P. Sage and E.B. White,Methodologies for risk and hazard assessment: a survey and status report, IEEE Trans. Systems, Man, and Cybernetics, SMC-10(8)(1980), 425–446.Google Scholar
  18. [18]
    K.J. Schmucker, Fuzzy Sets, Natural Language Computations, and Risk Analysis (Computer Science Press, Rockvill, Maryland, 1984 )Google Scholar
  19. [19]
    L.A. Zadeh, Fuzzy sets, Information and Control, 8 (3) (1965), 338–353.CrossRefGoogle Scholar
  20. [20]
    L.A. Zadeh, Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic, Fuzzy Sets and Systems 90 (2) (1971), 111–127.CrossRefGoogle Scholar
  21. [21]
    L.A. Zadeh, Toward a restructuring of the foundations of fuzzy logic (FL), Proceedings of FUZZ-IEEE’98, Anchorage, USA, May, 1998, 1676–1677.Google Scholar

Copyright information

© Physica-Verlag Heidelberg 2001

Authors and Affiliations

  • Chongfu Huang
    • 1
    • 2
  1. 1.Institute of Resources ScienceBeijing Normal UniversityChina
  2. 2.Key Laboratory of Environmental Change and Natural DisasterThe Ministry of Education of ChinaBeijingChina

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