
Demand Modelling in Telecommunications
Author(s) -
Martin Chvalina
Publication year - 2009
Publication title -
acta polytechnica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.207
H-Index - 15
eISSN - 1805-2363
pISSN - 1210-2709
DOI - 10.14311/1121
Subject(s) - artificial neural network , computer science , demand forecasting , telecommunications , field (mathematics) , term (time) , artificial intelligence , operations research , engineering , physics , mathematics , quantum mechanics , pure mathematics
This article analyses the existing possibilities for using Standard Statistical Methods and Artificial Intelligence Methods for a short-term forecast and simulation of demand in the field of telecommunications. The most widespread methods are based on Time Series Analysis. Nowadays, approaches based on Artificial Intelligence Methods, including Neural Networks, are booming. Separate approaches will be used in the study of Demand Modelling in Telecommunications, and the results of these models will be compared with actual guaranteed values. Then we will examine the quality of Neural Network models.