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A Recurrent Neural Network–based Forecasting System for Telecommunications Call Volume |
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PP: 1643-1650 |
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Author(s) |
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Paris Mastorocostas,
Constantinos Hilas,
Dimitris Varsamis,
Stergiani Dova,
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Abstract |
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| 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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