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

Authors

Paris Mastorocostas, Department of Informatics and Communications, Technological Education Institute of Serres, 62124 Serres, GreeceFollow
Constantinos Hilas
Dimitris Varsamis
Stergiani Dova

Author Country (or Countries)

Greece

Abstract

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.

Suggested Reviewers

N/A

Recommended Citation

Mastorocostas, Paris; Hilas, Constantinos; Varsamis, Dimitris; and Dova, Stergiani (2013) "A Recurrent Neural Network–based Forecasting System for Telecommunications Call Volume," Applied Mathematics & Information Sciences: Vol. 07: Iss. 5, Article 1.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol07/iss5/1