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Information Science and Applications (ICISA) 2016 pp 923–932Cite as

Building a Hybrid Method for Analyzing the Risk by Integrating the Fuzzy Logic and the Improved Fuzzy Clustering Algorithm FCM-R

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 376))

Abstract

Analysis of risk is a problem has attracted a special deal of consideration from enterprises. This paper proposes the integrating the fuzzy logic and the improved fuzzy clustering algorithm FCM-R to build a hybrid method for analyzing the risk. The method has two stages. In stage 1, first, the fuzzy logic is used to determine the risk levels of objects. The next, the objects which have risk level is greater or equal a given threshold, are selected for analyzing in the next stage. In stage 2, the improved fuzzy clustering algorithm FCM-R is applied to the objects chosen to create the appropriate number of clusters which are ranked based on the risk level measure of clusters. Here, for illustrating, we choose objects to analyze risk are customers in the enterprise. The proposed method has been experimented with real data set to generate customer clusters ranked according to the risk level measure from high to low. The results will be to use for predicting the customer’s risk and will be to help for offering the risk management policies to avoid loss.

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References

  1. Zadeh, L.A.: Fuzzy logic and approximate reasoning. Synthese 30, 407–428 (1975)

    Article  MATH  Google Scholar 

  2. Zadeh, L.A.: Commonsense knowledge representation based on fuzzy logic. IEEE Computer 16(10), 61–65 (1983)

    Article  Google Scholar 

  3. Zadeh, L.A.: The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems 11, 199–227 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  4. Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  5. Doan, H., Nguyen, D.T., Ho, B.Q.: Building a measure to integrate into a hybrid data mining method to analyze the risk of customer. In: 2015 2nd International Conference on Communication and Computer Engineering-ICOCOE 2015. Phu ket, Thailand, June 9–11, 2015. A Springer LNEE Series (2015)

    Google Scholar 

  6. Bezdek, J.C., Ehrlich, R., Full, W.: FCM: The Fuzzy C-Means Clustering Algorithm. Computers & Geosciences 10(2–3), 191–203 (1984)

    Article  Google Scholar 

  7. Hathaway, R.J., Bezdek, J.C.: Recent Convergence Results for the Fuzzy c-Means Clustering Algorithms. Journal of Classificanon 5, 237–247 (1988)

    Article  MathSciNet  Google Scholar 

  8. Pokorádi, L.: Fuzzy logic-based risk assessment. AARMS 1(1), 63–73 (2002)

    Google Scholar 

  9. Ingle, M.M., Atique, M., Dahad, S.O.: Risk Analysis Using Fuzzy Logic. International Journal of Advanced Engineering Technology E-ISSN 0976-3945. IJAET/Vol.II/ Issue III//96-99, July–September 2011

    Google Scholar 

  10. Ngai, E.W.T., Wat, F.K.T.: Fuzzy decision support system for risk analysis in e-commerce development. Decision Support Systems 40, 235–255 (2005)

    Article  Google Scholar 

  11. Hanafizadeh, P., Paydar, N.R.: A Data Mining Model for Risk Assessment and Customer Segmentation in the Insurance Industry. International Journal of Strategic Decision Sciences 4(1), 52–78 (2013)

    Article  Google Scholar 

  12. Farajian, M.A., Mohammadi, S.: Mining the Banking Customer Behavior Using Clustering and Association Rules Methods. International Journal of Industrial Engineering & Production Research 21(4), 239–245 (2010)

    Google Scholar 

  13. Rajagopal, S.: Customer Data Clustering Using Data Mining Technique. International Journal of Database Management Systems (IJDMS) 3(4), November 2011. doi:10.5121/ijdms.2011.3401

  14. Bezdek, J.C.: Pattern Recognition in Handbook of Fuzzy Computation. IOP Publishing Ltd., Boston (1998). (Chapter F6)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of Information Technology, VNU-HCM, Ho Chi Minh, Vietnam

    Huan Doan & Dinh Thuan Nguyen

Authors
  1. Huan Doan
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  2. Dinh Thuan Nguyen
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Corresponding author

Correspondence to Huan Doan .

Editor information

Editors and Affiliations

  1. Kyonggi University, iCatse Kyonggi University, Seongnam-si, Kyonggi-do, Korea (Republic of)

    Kuinam J. Kim

  2. Chair of IEEE CS STCOS, IBM T.J.Watson Research Center Chair of IEEE CS STCOS, Yorktown Heights, New York, USA

    Nikolai Joukov

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© 2016 Springer Science+Business Media Singapore

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Doan, H., Nguyen, D.T. (2016). Building a Hybrid Method for Analyzing the Risk by Integrating the Fuzzy Logic and the Improved Fuzzy Clustering Algorithm FCM-R. In: Kim, K., Joukov, N. (eds) Information Science and Applications (ICISA) 2016. Lecture Notes in Electrical Engineering, vol 376. Springer, Singapore. https://doi.org/10.1007/978-981-10-0557-2_88

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  • DOI: https://doi.org/10.1007/978-981-10-0557-2_88

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0556-5

  • Online ISBN: 978-981-10-0557-2

  • eBook Packages: EngineeringEngineering (R0)

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