Wharf Risk Assessment Based on AHP&D-S Evidence Theory

Abstract:

AHP is a method broadly applied in Risk Assessment. However this method has some shortcomings in evaluations. The subjective qualitative analysis of risk events and impacts in the wharf risk assessment make the conclusion with vagueness, which reduces the credibility of the result. The core idea of the Evidence Theory is the synthesis of evidence, which can be a good expression of "uncertainty" and "unknown", using the theory in the assessment can reveal the uncertainty effectively. In order to improve the accuracy and reliability of the assessment, this method combines AHP with D-S Evidence Theory, in which the D-S Evidence Theory applied to fuse and correct the expert rating data for determine-making of the wharf risk and AHP used to establish the system of assessment and determine the value. The Combination Rule for data fusion of multi- reliability can improve the reliability and make up for the lack of AHP. Through correction and data fusion by Synthetic Formula, the high support reviews get higher credibility, the low support reviews get lower credibility after synthesis, the polarization phenomenon lets the result more realistic and accurate. Taking a wharf project for example to prove the new combination method is more applicable to the wharf risk assessment.

• Periodical: Advanced Materials Research (Volumes 779-780)
• Pages: 769-773
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.779-780.769
• Online since: September 2013
• Authors: Ying He, Zhan Li Jiao, Fu Cai Jiang
• Keywords: Analysis Hierarchy Process (AHP), Correction of Data, D-S Evidence Theory, Fusion

References

[1] Jack A. Jones, An introduction to Evaluation Analysis of Information Risk (FAIR). [R], (2005).

[2] Ding Songbin, Airline Safety System Assessment Based on Evidence Theory [J]. Journal of Transportation Systems Engineering and Information Technology. 2007, 7(2): 77-82.

[3] Tang Guojie, Navigation Risk Assessment of VLCC in Restricted Waters [J], Navigation of China, 2010, 33(3): 105-108.

[4] Deng Yong, Fuzzy Information Fusion Based on Evidence Theory and Its Application in Target Recognition [J], 2005, 26(6): 754-758.

[5] Wang Zhuang, Dempster-Shafer Evidence Theory in Data Fusion[J], Fire Control Command Control, 2001, 26(3): 6-10.

[6] Fan Hong, An Approach for Formal Safety Assessment on Ship Based on Evidence Theory[J], Journal of Wuhan University of Technology, 2004, 28(4): 547-549.

[7] Qin Tingrong, Application of Evidence Theory in the Safety Combined Assessment of Harbor Navigation Environment [J], China Safety Science Journal, 2007, 17(9): 119-123.

[8] TU Jia-wen, XU Shou-shi. Discussion of Bayesian Method and Dempster-Shafer evidence Theory [J]. Infrared and Laser Engineering, 2001, 30(2): 139-142.

[9] Han Liyan, Knowledge fusion based on D-S evidence theory and its application[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(1): 65-73.

[10] Hai Feng, Application of D-S Theory in Information Fusion of Water Quality Measurement Sensors, 2012, Applied Mechanics and Materials, 241-244, 956.

[11] Hong Xian Tian, Application of D-S Evidence Deducing Theory to one Kind of Mechanical Fault Diagnosis, 2011, Applied Mechanics and Materials, 48-49, 249.

DOI: 10.4028/www.scientific.net/amm.48-49.249