A Recurrent Neural Network–based Forecasting System for Telecommunications Call Volume

نویسندگان

  • Paris Mastorocostas
  • Constantinos Hilas
  • Dimitris Varsamis
  • Stergiani Dova
چکیده

A recurrent neural network–based forecasting system for telecommunications call volume is proposed in this work. In particular, the forecaster is a Block–Diagonal Recurrent Neural Network with internal feedback. Model’s performance is evaluated by use of real–world telecommunications data, where an extensive comparative analysis with a series of existing forecasters is conducted, including both traditional models as well as neural and fuzzy approaches.

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تاریخ انتشار 2013