Hydraulic Mental Structure Health Diagnosis Weighting Method

Abstract:

By means of inductive analysis the health diagnosis weighting methods in engineering, this paper discusses the basic principle, advantages, disadvantages and applicable scope of weighting methods. On the basis, combining with multi-level, multi-standard and multi-factor characteristic of hydraulic metal structures health diagnosis, the methods of AHP, information gain, information diffusion and improved entropy are studied, which are applicable to hydraulic metal structures health diagnosis weighting. Based on fuzzy theory, the fuzzy multi-level comprehensive weighting method is put forward and studied, which combined both subjective and objective method advantages and its complementary. In addition, it provides the necessary theory foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

• Periodical: Applied Mechanics and Materials (Volumes 494-495)
• Pages: 925-931
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.494-495.925
• Online since: February 2014
• Authors: Kun Yang*, Guang Ming Yang, Yong Huang, Pan De Jing
• Keywords: Health Diagnosis, Hydraulic Mental Structure, Index, Weighting

References

[1] Yang Guangming, Jia Wenbin. Research to health diagnose model of gate and hoist machinery based on AHP[J]. Advanced Materials Research, Vols. 287-290, pp.3036-3042, (2011).

DOI: 10.4028/www.scientific.net/amr.287-290.3036

[2] Ma J, Fan Z, Huang L.H. A subjective and objective integrated approach to determine attributes weights[J]. European Journal of Operational Research, 1999, 112(2): 397-404.

DOI: 10.1016/s0377-2217(98)00141-6

[3] Ma Hui. Objective weight method in comprehensive evaluation system[J]. Cooperative Economy and Science, 2009, (17): 50-51.

[4] Xu Getting. The application of Delphi method and its difficulties[J]. China Statistics, 2006, (9): 57-59.

[5] Saaty T. The Analytic Hierarchy Process [M]. McGraw-Hill Inc, New York, (1980).

[6] Fan Z, Ma J, Zhang Q. An approach to multiple attribute decision making based on fuzzy preference information on alternatives[J]. Fuzzy sets and systems, 2002, 131(1): 101-106.

DOI: 10.1016/s0165-0114(01)00258-5

[7] Changki Lee, Gary Geunbae Lee. Information gain and divergence-based feature selection for machine learning-based text categorization[J]. Information Processing & Management, 2006, 42(1): 155-165.

DOI: 10.1016/j.ipm.2004.08.006

[8] Masood A. A combined AHP-GP model quality control systems[J]. International Journal of Production Economics. 2001. 72(1): 27-40.

DOI: 10.1016/s0925-5273(00)00077-3

[9] Lu Jianbin, Hu Weidong, Xiao Hui & Yu Wenxian. Novel cued search strategy based on information gain for phased array radar[J]. Journal of Systems Engineering and Electronics, 2008, 12(4): 378-382.

DOI: 10.1016/s1004-4132(08)60081-x

[10] Fan Z, Ma J, Zhang Q. An approach to multiple attribute decision making based on fuzzy preference information on alternatives[J]. Fuzzy sets and systems, 2002, 131(1): 101-106.

DOI: 10.1016/s0165-0114(01)00258-5

[11] Du Dong. Study on 0. 1～0. 9 Scale in AHP[J]. Systems Engineering and Electronics, 2000, 23(5): 36-38.

[12] ZHANG Wen-ge , HUANG Qiang. Scale analysis of AHP and its application in evaluating water conservancy engineering[J]. Journal of Northwest Sci-Tech University of Agriculture and Forestry(Natural Science Edition), 2006, 34(3): 152-156.