Pre-Processing of Input Data of Neural Networks: The Case of Forecasting Telecommunication Network Traffic

Telektronikk: Telecommunications Forecasting (Special issue in co-operation with International Institute of Forecasters ) 2008
Irina Kļevecka, Jānis Lelis

The aim of our research was to create a functional algorithm of preprocessing of input data taking into account the specific aspects of teletraffic and properties of neural networks. The practical application to forecasting telecommunication data sequences shows that the procedure of data preprocessing decreases the time of learning (what is particularly important in the case of large data sets) and increases the plausibility and accuracy of the forecasts. The algorithm can be applied to forecasting the intensity of plain telephone networks and IP networks.

Keywords
Neural networks, pre-processing, telecommunications, network traffic
Hyperlink
http://www.telenor.com/no/resources/images/168-178_Pre-processingInputData-ver1_tcm26-36193.pdf

Kļevecka, I., Lelis, J. Pre-Processing of Input Data of Neural Networks: The Case of Forecasting Telecommunication Network Traffic. Telektronikk: Telecommunications Forecasting (Special issue in co-operation with International Institute of Forecasters ), 2008, Vol.104, No.3/4 , pp.168-178. ISSN 0085-7130.

Publication language
English (en)