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Forecasting Project Costs by Using Fuzzy Logic

  • M. Bouabaz
  • M. Belachia
  • M. Mordjaoui
  • B. Boudjema
Chapter

Abstract

This paper will present a comprehensive overview of the use of fuzzy logic approach in modeling as a decision support tool for cost estimation. The model is based on expectation-maximisation (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models. The clusters given by the EM algorithm has lead to the development of fuzzy rules. The best fuzzy logic model was found to consist of two fuzzy rules. The result also indicates that kind of behavior given by the EM clustering algorithm has reduced the uncertainty of estimate, which in turn the accuracy of the estimate is improved.

Keywords

Fuzzy Logic Partition Coefficient Fuzzy Rule Fuzzy Cluster Expectation Maximization Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Zadeh, L. A. Fuzzy sets. Information and Control. 8, pp 338–353 (1965)Google Scholar
  2. 2.
    Takagi T. and M. Sugeno Fuzzy Identification of Systems and its Applications to Modeling and Control, IEEE Transactions on Systems, Man, and Cybernetics 15(1), pp 116–132 (1985)MATHGoogle Scholar
  3. 3.
    Abonyi J (2003). Fuzzy Modeling Identification for Control. Birkhäuser, Boston (2003)Google Scholar
  4. 4.
    Gath I and Geva, A.B (1989). Unsupervised Optimal Fuzzy Clustering. IEEE Trans Pattern and Machine Intell, vol. 11 (7), pp 773–781 (1989)Google Scholar
  5. 5.
    Bezdeck J C.; Ehrlich, R,; Full, W. FCM: Fuzzy C-means Algorithm. Computers and Geoscience, 10(2–3):pp 191–203 (1984)Google Scholar
  6. 6.
    Bezdeck, J C. Cluster Validity With Fuzzy Sets, Cybernetics 3(3), pp 58–73 (1975)Google Scholar
  7. 7.
    Bouabaz M. and Horner RMW. Modeling and predicting bridge repair and maintenance costs, Proc. Int. Conf. on Bridge Management, London pp 187–197 (1990)Google Scholar
  8. 8.
    Abonyi J Balasko B, and Balazs L Fuzzy Clustering and Data Analysis Toolbox for Use With Matlab (2005)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • M. Bouabaz
    • 1
  • M. Belachia
  • M. Mordjaoui
  • B. Boudjema
  1. 1.Civil Engineering DepartmentUniversity of 20AugustSkikdaAlgeria

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