A Computational Intelligence Approach for Forecasting Telecommunications Time Series

  • Paris A. Mastorocostas
  • Constantinos S. HilasEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 151)


In this work a computational intelligence-based approach is proposed for forecasting outgoing telephone calls in a University Campus. A modified Takagi–Sugeno-Kang fuzzy neural system is presented, where the consequent parts of the fuzzy rules are neural networks with internal recurrence, thus introducing dynamics to the overall system. The proposed model, entitled Locally Recurrent Neurofuzzy Forecasting System (LR-NFFS), is compared to well-established forecasting models, where its particular characteristics are highlighted.


Fuzzy Rule Mean Absolute Percentage Error Recurrent Neural Network Exponential Smoothing Consequent Part 
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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Paris A. Mastorocostas
    • 1
  • Constantinos S. Hilas
    • 1
    Email author
  1. 1.Department of Informatics and CommunicationsTechnological Educational Institute of SerresSerresGreece

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