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Performance evaluation of industrial enterprises via fuzzy inference system approach: a case study

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Abstract

The aim of this study is not only to give self-contained and methodological steps of data mining with its areas of applications, but also to provide a compact source of reference for the researchers who want to use data mining and fuzzy inference in their area of work. We construct a fuzzy inference system to predict the profit of the major 500 industrial enterprises of Turkey. For this aim, we use most of the data mining tools. First, we use fuzzy \(c\)-means clustering algorithm and obtain the linguistic terms of the variables. Having used decision tree technique, fuzzy rules are revealed. Eventually, we compare various defuzzification strategies to obtain crisp prediction values of our fuzzy inference system. We can conclude that the prediction results of the smallest of maxima defuzzification strategy-based fuzzy inference system has circa 40 % smaller sum square error than that of classical regression model.

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Acknowledgments

Gözde Ulutagay has been partly supported by Grant 10-183-RG/ITC/AS_C from TWAS (The Academy of Sciences for the Developing World)-COMSTECH (Committee on Scientific and Technological Cooperation).

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Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Izmir University, Gursel Aksel Blv. No. 14, Uckuyular, 35350 , Izmir, Turkey

    Gözde Ulutagay

  2. Department of International Trade and Finance, Faculty of Economics and Administrative Sciences, Afyon Kocatepe University, Afyon, Turkey

    Fatih Ecer

  3. Department of Computer Science, Faculty of Science, Dokuz Eylül University, Izmir, Turkey

    Efendi Nasibov

  4. Institute of Cybernetics, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Efendi Nasibov

Authors
  1. Gözde Ulutagay
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  2. Fatih Ecer
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  3. Efendi Nasibov
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Corresponding author

Correspondence to Gözde Ulutagay.

Additional information

Communicated by T. Allahviranloo.

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Ulutagay, G., Ecer, F. & Nasibov, E. Performance evaluation of industrial enterprises via fuzzy inference system approach: a case study. Soft Comput 19, 449–458 (2015). https://doi.org/10.1007/s00500-014-1263-3

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  • DOI: https://doi.org/10.1007/s00500-014-1263-3

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