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Evaluating Customer Satisfaction: Linguistic Reasoning by Fuzzy Artificial Neural Networks

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New Trends in Intelligent Information and Database Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 598))

Abstract

Customer satisfaction is a measure of how a company meets or surpasses customers’ expectations. It is seen as a key element in business strategy; and therefore, enhancing the methods to evaluate the satisfactory level is worth studying. Collecting rich data to know the customers’ opinion is often encapsulated in verbal forms, or linguistic terms, which requires proper approaches to process them. This paper proposes and investigates the application of fuzzy artificial neural networks (FANNs) to evaluate the level of customer satisfaction. Genetic algorithm (GA) and back-propagation algorithm (BP) adjust the fuzzy variables of FANN. To investigate the performances of GA- and BP-based FANNs, we compare the results of each algorithm in terms of obtained error on each alpha-cut of fuzzy values.

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Author information

Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Johor Baharu, Johor, Malaysia

    Reza Mashinchi & Ali Selamat

  2. Advanced Informatics School, Universiti Teknologi Malaysia, 54100, Kuala Lumpur, Malaysia

    Suhaimi Ibrahim

  3. Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove, 500 03, Czech Republic

    Ali Selamat & Ondrej Krejcar

  4. Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17. Listopadu 15, Ostrava Poruba, 70833, Czech Republic

    Marek Penhaker

Authors
  1. Reza Mashinchi
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  2. Ali Selamat
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  3. Suhaimi Ibrahim
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  4. Ondrej Krejcar
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  5. Marek Penhaker
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Corresponding author

Correspondence to Reza Mashinchi .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Dariusz Barbucha

  2. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  3. Graduate Program in Information Technology, Bina Nusantara University, Jakarta, Indonesia

    John Batubara

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© 2015 Springer International Publishing Switzerland

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Mashinchi, R., Selamat, A., Ibrahim, S., Krejcar, O., Penhaker, M. (2015). Evaluating Customer Satisfaction: Linguistic Reasoning by Fuzzy Artificial Neural Networks. In: Barbucha, D., Nguyen, N., Batubara, J. (eds) New Trends in Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 598. Springer, Cham. https://doi.org/10.1007/978-3-319-16211-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-16211-9_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16210-2

  • Online ISBN: 978-3-319-16211-9

  • eBook Packages: EngineeringEngineering (R0)

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