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.
Atslēgas vārdi
Neural networks, pre-processing, telecommunications, network traffic
Hipersaite
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 , 168.-178.lpp. ISSN 0085-7130.
Publikācijas valoda
English (en)