Open Access
Issue
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 71, Number 1, January–February 2016
Article Number 17
Number of page(s) 15
DOI https://doi.org/10.2516/ogst/2014044
Published online 22 January 2016
  • AIChE/CCPS (1999) Guidelines for Consequence Analysis of Chemical Releases, The Center for Chemical Process Safety of the American Institute of Chemical Engineers Publishers, New York. [Google Scholar]
  • API (2008) Recommended Practice 581, Risk based inspection technology, Part 3: Consequence analysis in an API RBI assessment, 2nd ed., American Petroleum Institute, Washington DC. [Google Scholar]
  • Baloi D., Price A.D.F. (2003) Modeling global risk factors affecting construction cost performance, International Journal of Project Management 21, 261–269. [CrossRef] [Google Scholar]
  • Belohlavek R., Klir G. (2011) Concepts and fuzzy logic, The MIT Press, Massachusetts. [Google Scholar]
  • Black M. (1937) Vagueness: An exercise in logical analysis, Philosophy of Science 4, 427–455. [CrossRef] [Google Scholar]
  • Blair A.N., Ayyub B.M., Bender W.J. (2001) Fuzzy stochastic risk-based decision analysis with the mobile offshore base as a case study, Marine Structures 14, 69–88. [CrossRef] [Google Scholar]
  • Bowles J.B., Pelaez C.E. (1995) Application of fuzzy logic to reliability engineering, Proceeding of IEEE 83, 3, 435–449. [CrossRef] [Google Scholar]
  • Chapman C.B., Ward S.C. (1997) Project risk management: process techniques and insights, John Wiley and Sons, New York. [Google Scholar]
  • Chia S.E. (2006) Risk assessment framework for project management, 2006 IEEE International Engineering Management Conference, 17-20 Sept, Bahia, pp. 376–379. [Google Scholar]
  • Chiu S. (1994) Fuzzy model identification based on cluster estimation, Journal of Intelligent and Fuzzy Systems 2, 3–10. [Google Scholar]
  • Crowl D.A., Louvar J.F. (2001) Chemical Process Safety: Fundamentals with Applications, 2nd ed., Prentice Hall, Englewood Cliffs, New Jersey. [Google Scholar]
  • Dahab M.F., Lee Y.W., Bogardi I. (1994) A rule based fuzzy set approach to risk analysis of nitrate contaminated groundwater, Water Science and Technology 7, 45–52. [Google Scholar]
  • Darbra R.M., Eljarrat E., Barcelo D. (2008a) How to measure uncertanties in environmental risk assessment, Trends in Analytical Chemistray 27, 377–387. [CrossRef] [Google Scholar]
  • Darbra R.M., Demichela M., Mure S. (2008b) Preliminary risk assesment of ecotoxic substances accidental releases in major risk installations through fuzzy logic, Process Safety and Environmental Protection 86, 103–111. [CrossRef] [Google Scholar]
  • Darbra R.M., Casal J. (2009) Environmental risk assessment of accidental releases in chemical plants through fuzzy logic, Chemical Engineering Transactions 17, 287–292. [Google Scholar]
  • DNV (2006) Report No. T14: Technical note process equipment failure frequencies. [Google Scholar]
  • Duboise D., Esteva F., Godo L., Prade H. (2007) Fuzzy set based logics- an history oriented presentation of their main development. Handbook of the History of Logic, Vol. 8, Elsevier, New York. [Google Scholar]
  • Duboise D., Prade H. (1990) Resolution principles in possibilistic logic, International Journal of Approximate Reasoning 4, 1–21. [CrossRef] [MathSciNet] [Google Scholar]
  • Ferson S. (2002) RAMAS Risk calc 4.0 software: risk assessment with uncertain numbers, Lewis publishers, Boca Raton. [Google Scholar]
  • Gentile M., Rogers W.J., Mannan M.S. (2003) Development of a fuzzy logic-based inherent safety index, ICHEM Journal 81, 444–456. [Google Scholar]
  • Gottwald S. (2006) Universes of fuzzy sets and axiomatizations of fuzzy set theory. Part I: Model-based and axiomatic approaches, Studia Logica 82, 211–244. [CrossRef] [MathSciNet] [Google Scholar]
  • Grima M.A., Bruines P.A., Verhoef P.N.W. (2000) Modeling tunnel boring machine performance by nuero fuzzy methods, Tunneling and Underground Space Technology 15, 259–269. [CrossRef] [Google Scholar]
  • Guimaraes A.C.F., Lapa C.M.F. (2007) Fuzzy inference to risk assessment on nuclear engineering systems, Applied Soft Computing 7, 17–28. [CrossRef] [Google Scholar]
  • Hertz D.B., Thomas H. (1994) Risk analysis and its applications, 2nd ed., John Wiley and Sons, New York. [Google Scholar]
  • IP 323 (1998) A Risk-Based Approach to Hazardous Area Classification, The Institute of Petroleum, London. [Google Scholar]
  • Iphar M., Goktan R.M. (2006) An application of fuzzy sets to the diaggability index rating method for surface mine equipment selection, International Journal of Rock Mechanicas and Mining Science 43, 253–266. [CrossRef] [Google Scholar]
  • Jafari A. (2001) Management of risk, uncertainties and opportunities on projects: time for fundamental shift, International Journal of Project Management 19, 89–101. [CrossRef] [Google Scholar]
  • Jamshidi A., Jang J.S.R., Sun C.T., Mizutani E. (1997) Neural fuzzy and soft computing, Prentice Hall, Englewood Cliff, New Jersey. [Google Scholar]
  • Jamshidi A., Yazdani A., Yakhchali S., Khaleghi S. (2012) Developing a new fuzzy inference system for pipeline risk assessment, Journal of Loss Prevention in the Process Industries, In Press. [Google Scholar]
  • Jang J.S., Sun C.T. (1997) Neuro fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, New Jersey, Englewood Cliffs. [Google Scholar]
  • Karimi I., Hüllermeier E. (2007) Risk assessment system of natural hazards: A new approach based on fuzzy probability, Fuzzy Sets and Systems 158, 987–999. [CrossRef] [MathSciNet] [Google Scholar]
  • Kentel E., Aral M.M. (2007) Risk Tolerance Measure for Fuzzy Health Risk Assessment, International Journal for Stochastic Environmental Research and Risk Assessment 21, 405–417. [CrossRef] [Google Scholar]
  • Kirchsteiger C. (2005) Review of industrial safety management by international agreements and institutions, Journal of Risk Research 8, 31–51. [CrossRef] [Google Scholar]
  • Kletz T.A. (1977) Unconfined Vapor cloud explosions, AICHE Loss Prevention 11, 50–61. [Google Scholar]
  • Lees F.P. (2001) Loss prevention in the process industries, hazard identification, assessments and control, 2nd ed., Butter Worth-Heinemann, Oxford. [Google Scholar]
  • Li Z. (2006) Fuzzy chaotic systems: modeling, control, and applications, Springer, Germany. [Google Scholar]
  • Ma H.W. (2002) Stochastic multimedia risk assessment for a site with contaminated groundwater, Stochastic Environmental Research and Risk Assessment 16, 464–478. [CrossRef] [Google Scholar]
  • Mamdani E.H. (1976) Advances in the linguistic synthesis of fuzzy controllers, International Journal of Man-Machine Studies 8, 669–678. [CrossRef] [Google Scholar]
  • Mamdani E.H., Assilian S. (1975) An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7, 1–13. [CrossRef] [Google Scholar]
  • Mark W., Cohen P.E., Glen R.P. (2004) Project risk identification and management, AACE International Transaction 01, 1–5. [Google Scholar]
  • Markowski A.S., Mannan M.S. (2008) Fuzzy risk matrix, Journal of Hazardous Materials 159, 152–157. [CrossRef] [PubMed] [Google Scholar]
  • Markowski A.S., Mannan M.S. (2009a) Fuzzy logic for piping risk assessment, Journal of Loss Prevention in the Process Industries 22, 921–927. [CrossRef] [Google Scholar]
  • Markowski A.S., Mannan M.S., Bigoszewska A. (2009b) Fuzzy logic for process safety analysis, Journal of Loss Prevention in the Process Industries 22, 695–702. [CrossRef] [Google Scholar]
  • McKone T.E., Deshpande A.W. (2005) Can fuzzy logic bring complex environmental problems into focus? Environmental Science Technology 39, 42–47. [CrossRef] [Google Scholar]
  • Modarres M. (2006) Risk analysis techniques, tools and trends, CRC Press, Florida. [Google Scholar]
  • Naderi M. (2008) Fuzzy logic application in risk analysis of construction management, M.S. Thesis, Dep. of Civil and Environmental Engineering, Alberta [Google Scholar]
  • Nieto-Morote A., Ruz-Vila F. (2011) A fuzzy approach to construction project risk assessment, International Journal of Project Management 29, 220–231. [CrossRef] [Google Scholar]
  • OREDA (2009) Offshore Reliability Data Handbook, 5th ed., SINTEF Industrial Management, Norway. [Google Scholar]
  • OGP (2010) Report No. 434-1: Risk Assessment Data Directory: Process Release Frequencies, International Association of Oil and Gas Procedures. [Google Scholar]
  • Perry J.G., Hayes R.W. (1985) Risk and its management in construction projects, Proceeding of Institution Civil Engineers 78, 499–521. [CrossRef] [Google Scholar]
  • POGC (2010) Pars Oil and Gas Company (POGC), report on general storage area in Assaluye and Tobmak in South Pars Industrial area, www.POGC.ir, Tehran. [Google Scholar]
  • Pokoradi L. (2002) Fuzzy logic based risk assessment, Academic and Applied Research in Military Science 1, 63–73. [Google Scholar]
  • Ross T.J. (2010) Fuzzy logic with engineering applications, 2nd ed., John Wiley and Sons, New York. [CrossRef] [Google Scholar]
  • Uricchio V.F., Giordano R., Lopez N. (2004) A fuzzy knowledge based decision support for groundwater pollution risk evaluation, Journal of Environmental Management 73, 189–197. [CrossRef] [PubMed] [Google Scholar]
  • Vemula V.R.S., Mujumdar P.P., Ghosh S. (2004) Risk evaluation in water quality management of a river system, Journal of Water Resources Planning and Management 130, 411–420. [CrossRef] [Google Scholar]
  • Wulan M., Petrovic D. (2012) A fuzzy logic based system for risk analysis and elevation within enterprose collaborations, Computers in Industry 63, 739–748. [CrossRef] [Google Scholar]
  • Xie M. (2003) Fundamentals of robotics: linking perception to action, World Scientific Publishing Co., London. [CrossRef] [Google Scholar]
  • Zadeh L. (1965) Fuzzy sets, Information and Control 8, 338–353. [CrossRef] [MathSciNet] [Google Scholar]
  • Varnes D.J. (1984) Commissioning on landslides and other mass movements, IAEG. Landslide hazard zonation: a review of principles and practices, The UNESCO Press, Paris. [Google Scholar]

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