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Integrated Fuzzy Approach for System Modeling and Risk Assessment

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Modeling Decisions for Artificial Intelligence (MDAI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3885))

Abstract

Subjective nature of system components makes the natural problems more complicated and harder to quantify. Thus, effective reflection of uncertainties, which is essential for generating reliable and realistic outcomes, has become a major concern for risk assessment. With the growing trend of fuzzy modeling and simulation of environmental problem, there is a need to develop a risk analysis approach which can use the fuzzy number output for characterization of risk. This study has been done to fulfil that need. Integration of system simulation and risk analysis using fuzzy approach allowed to incorporate system modelling uncertainty and subjective risk criteria. In this study, an integrated fuzzy relation analysis (IFRA) model is proposed for risk assessment involving multiple criteria. Model is demonstrated for a multi-components groundwater contamination problem. Results reflect uncertainties presented as fuzzy number for different modelling inputs obtained from fuzzy system simulation. Integrated risk can be calculated at different membership level which is useful for comprehensively evaluating risks within an uncertain system containing many factors with complicated relationship. It has been shown that a broad integration of fuzzy system simulation and fuzzy risk analysis is possible.

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© 2006 Springer-Verlag Berlin Heidelberg

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Kumar, V., Schuhmacher, M., García, M. (2006). Integrated Fuzzy Approach for System Modeling and Risk Assessment. In: Torra, V., Narukawa, Y., Valls, A., Domingo-Ferrer, J. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2006. Lecture Notes in Computer Science(), vol 3885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11681960_23

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  • DOI: https://doi.org/10.1007/11681960_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32780-6

  • Online ISBN: 978-3-540-32781-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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