Fuzzy process accuracy index to evaluate risk assessment of drought effects in Turkey

Human and Ecological Risk Assessment

Volumn 15, Issue 4, 2009, Pages 789-810

  Kahraman, Cengiz ^a   Kaya, Ihsan ^a  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Drought; Fuzzy capability indices; Fuzzy set theory; Process accuracy index; Process capability; Risk assessment

Indexed keywords

EID: 74949114129     PISSN: 10807039     EISSN: 15497860     Source Type: Journal    
DOI: 10.1080/10807030903051242     Document Type: Article

References (40)

1. Besten JP. 2007. Risk assessment approaches in European countries. Sustainable Management of Sediment Resources 3:153-205
2. pm. J Quality Technol 20:162-75
3. Chen KS and Chen TW. 2007. Multi-process capability plot and fuzzy inference evaluation. Int J Production Econ. doi:10.1016/j.ijpe.2006.12.056
4. Chen TW, Chen KS, and Lin JY. 2003a. Fuzzy evaluation of process capability for bigger-the best type products. Internat J Advanced Manufacturing Technol 21:820-6
5. pm. Internat J Adv Manufacturing Technol 22:534-40
6. Fairman R, Mead C, and Williams WP. 1999. Environmental Risk Assessment - Approaches, Experiences and Information Sources. European Environment Agency-1999. Available at http://reports.eea.eu.int/GH-07-97-595-EN-C2/en
7. Gao Y and Huang M. 2003. Optimal process tolerance balancing based on process capabilities. Internat J Adv Manufacturing Technol 21:501-7
8. Green S. 2000. Negotiating with the future: The culture of modern risk in global financial markets. Environment and Planning D: Society and Space 18:77-89
9. Hsu BM and Shu MH. 2007. Fuzzy inference to assess manufacturing process capability with imprecise data. Eur J Oper Res. doi:10.1016/j.ejor.2007.02.023
10. İWSA (İstanbulWater and Sewerage Administration). 2009a. Fullness Rates of Dams. Available at http://www.iski.gov.tr/surezervleri/msu2.phtm
11. İWSA (İstanbul Water and Sewerage Administration). 2009b. Filling Rates of Our Dams. Available at http://www.iski.gov.tr/en-US/surezervleri/5.phtm
12. Jinno K, Zongxue X, Kawamura A, et al. 1995. Risk assessment of a water supply system during drought. Water Resour Develop 11(2):185-204
13. Kahraman C and Kaya I. 2007. Fuzzy process capability indices for quality control of irrigation water. Proceedings of the 1st International Conference on Risk Analysis and Crisis Response. Book Series: Advances in Intelligent System Research 2:144-9
14. Kahraman C and Kaya I. 2008. Fuzzy process capability indices for quality control of irrigation water. Stochastic Environ Res Risk Assess 23:451-462
15. Kane VE. 1986. Process capability indices. J Quality Technol 18:41-52
16. Karaböork M.ÇC . 2007. Trends in drought patterns of Turkey. J Environ Eng Sci 6:45-52
17. Kaya I and Kahraman C. 2007a. Learning processes and their fuzzy capability analyses. 12th International Conference on Fuzzy Theory and Technology, Salt Lake City, UT, USA, World Scientific Publishing. doi:10.1142/9789812709677 0186, 1312-1317
18. Kaya I and Kahraman C. 2007b. Air pollution control using six sigma approach. Proceedings of the 1st International Conference on Risk Analysis and Crisis Response. Book Series: Advances In Intelligent System Research 2:110-5
19. Kaya I and Kahraman C. 2008a. Fuzzy process capability analyses: An application to teaching processes. J Intel Fuzzy Syst 19:259-272
20. Kaya I and Kahraman C. 2008b. Fuzzy robust process capability indices for risk assessment of air pollution. Stochastic Environ Res Risk Assess. 23:529-541
21. Kotz S and Johnson N. 2002. Process capability indices-a review 1992-2000. J Qual Technol 34:2-19
22. Kundzewicz ZW, Rosbjerg D, Simonovic SP, and Takeuchi K. 1993. Extreme hydrological events: precipitation, floods and droughts. Yokohama, Japan
23. Lee HK. 2005. First Course on Fuzzy Theory and Applications. Springer, New York, NY, USA
24. Lee HT. 2001. Cpk index estimation using fuzzy numbers. Eur J Oper Res 129:683-8
25. Lee JC, Hung HN, Pearn WL, et al. 2002. On the distribution of the estimated process yield index Spk. Quality Reliab Eng Int 18:111-6
26. Lin GH. 2006. A random interval estimation of the estimated process accuracy index. Int J Adv Manuf Tech 27:969-74
27. Montgomery DC. 2005. Introduction to Statistical Quality Control. John Wiley & Sons, New York, NY, USA
28. Parchami A and Mashinchi M. 2007. Fuzzy estimation for process capability indices. Inform Sciences 177:1452-62
29. Parchami A, Mashinchi M, Yavari AR, et al. 2006. Fuzzy confidence interval for fuzzy process capability index. J Intel Fuzzy Syst 17(3):287-95
30. Parchami A, Mashinchi M, Yavari AR, and Maleki HR. 2005. Process Capability Indices as Fuzzy Numbers. Austrian Journal of Statistics 34(4):391-402.
31. Pearn WL and Kotz S. 2006. Encyclopedia andHandbook of Process Capability Indices. Series on Quality, Reliability and Engineering Statistics 12, World Scientific
32. Pearn WL, Lin GH, and Chen KS. 1998. Distributional and inferential properties of the process accuracy and process precision indices. Commun Stats-Theor M 27(4):985-1000
33. Steila D 1983. Quantitative vs qualitative drought assessment. Prof Geogr 35:192-94
34. Tran L and Duckstein L. 2002. Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Sets and Systems 130:331-41
35. p with fuzzy numbers. Int J Adv Manuf Tech 30:334-9
36. USEPA (Environmental Protection Agency). 1989. Risk Assessment Guidance for Superfund, vol 1. Human Health Evaluation Manual. EPA540/002. Washington, DC, USA
37. USEPA. 1992. Framework for Ecological Risk Assessment. EPA/630/R-92/001. Washington, DC, USA
38. USEPA. 1998. Guidelines for Ecological Risk Assessment. EPA/630/R-95/002F. Washington, DC, USA
39. Yuan Y. 1991. Criteria for evaluating fuzzy ranking methods. Fuzzy Set Syst 43:139-57
40. Zadeh LA. 1965. Fuzzy sets. Inform Control 8:338-59