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A Type-2 Fuzzy Hybrid Expert System for Commercial Burglary

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

In this paper, an interval type-2 fuzzy hybrid expert system is proposed for commercial burglary. This method is the combination of Sugeno and Mamdani inference system. After identifying the system domain, the inputs and output of the system are determined. Then the k-nearest neighborhood functional dependency approach is used to select the most important variables for the system. The indirect approach is used to fuzzy system modeling by implementing the Kwon validity index for determining the number of rules in the fuzzy clustering approach. Next, the output membership values are projected onto the input spaces to generate the membership values of input variables, and the membership functions of inputs and output are tuned. Then, the type-1 fuzzy hybrid system has been implemented. After that, we transformed the type-1 fuzzy hybrid rule base into an interval type-2 fuzzy hybrid rule base for enhancing the robustness of the system. For generating interval type-2 fuzzy hybrid rule base, the Gaussian primary MF with an uncertain standard deviation and a fixed mean is used. In order to validate our method, we developed two system modeling techniques and compared the results with the proposed interval type-2 fuzzy hybrid expert system. These techniques are multiple regression, and type-1 fuzzy expert system. The results of this study show that the proposed interval type-2 fuzzy hybrid expert system has a better performance in comparison to type-1 fuzzy and multiple regression models.

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Authors and Affiliations

  1. Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

    M. H. Fazel Zarandi, A. Seifi, H. Esmaeeli & Sh. Sotudian

Authors
  1. M. H. Fazel Zarandi
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  2. A. Seifi
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  3. H. Esmaeeli
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  4. Sh. Sotudian
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Corresponding author

Correspondence to M. H. Fazel Zarandi .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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Fazel Zarandi, M.H., Seifi, A., Esmaeeli, H., Sotudian, S. (2018). A Type-2 Fuzzy Hybrid Expert System for Commercial Burglary. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_5

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