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Improving a fuzzy neural network for predicting storage usage and calculating customer value

Author

Listed:
  • Reza Rabieyan

    (Baden-Wuerttemberg Cooperative State University)

  • Philipp Pohl

    (Baden-Wuerttemberg Cooperative State University)

Abstract

Predicting the behavior of customers plays a crucial role in the quality of resource management and customer services. In this article, a fuzzy neural network model for predicting the customer storage usage is identified. The identified fuzzy neural network is improved and finally the result of the improved fuzzy neural network is compared with some other fuzzy neural network and other prediction methods.

Suggested Citation

  • Reza Rabieyan & Philipp Pohl, 2020. "Improving a fuzzy neural network for predicting storage usage and calculating customer value," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(5), pages 292-301, October.
    • Handle: RePEc:pal:jorapm:v:19:y:2020:i:5:d:10.1057_s41272-020-00253-3
    DOI: 10.1057/s41272-020-00253-3
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    References listed on IDEAS

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    1. repec:bla:biomet:v:71:y:2015:i:4:p:1060-1069 is not listed on IDEAS
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
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