IEICE TRANSACTIONS on Communications
Forecasting Traffic Volumes for Intelligent Telecommunication Services Based on Service Characteristics
Summary :
A method is proposed for deriving a traffic characteristics model that can be used to forecast the traffic volume for intelligent telecommunication services. A sort of regression analysis with dummy variables is used to represent the service quantitatively and to construct the traffic characteristics model. Recursive least squares estimation, which is a special case of the Kalman filter, is applied to the traffic characteristics model to forecast the traffic volume. In the proposed modeling and forecasting, qualitative factors representing a certain service attribute are selected and using an information criterion, the model with the best fit is identified as the most suitable forecasting model. Numerical results using practical observation data showed that the proposed method produces an accurate forecast and is thus effective for practical use.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E81-B No.12 pp.2487-2494
- Publication Date
- 1998/12/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Issue on the Latest Development of Telecommunication Research)
- Category
- Network Design, Operation, and Management
Authors
Keyword
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Takeshi YADA, Isami NAKAJIMA, Ichiro IDE, Hideyo MURAKAMI, "Forecasting Traffic Volumes for Intelligent Telecommunication Services Based on Service Characteristics" in IEICE TRANSACTIONS on Communications,
vol. E81-B, no. 12, pp. 2487-2494, December 1998, doi: .
Abstract: A method is proposed for deriving a traffic characteristics model that can be used to forecast the traffic volume for intelligent telecommunication services. A sort of regression analysis with dummy variables is used to represent the service quantitatively and to construct the traffic characteristics model. Recursive least squares estimation, which is a special case of the Kalman filter, is applied to the traffic characteristics model to forecast the traffic volume. In the proposed modeling and forecasting, qualitative factors representing a certain service attribute are selected and using an information criterion, the model with the best fit is identified as the most suitable forecasting model. Numerical results using practical observation data showed that the proposed method produces an accurate forecast and is thus effective for practical use.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e81-b_12_2487/_p
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@ARTICLE{e81-b_12_2487,
author={Takeshi YADA, Isami NAKAJIMA, Ichiro IDE, Hideyo MURAKAMI, },
journal={IEICE TRANSACTIONS on Communications},
title={Forecasting Traffic Volumes for Intelligent Telecommunication Services Based on Service Characteristics},
year={1998},
volume={E81-B},
number={12},
pages={2487-2494},
abstract={A method is proposed for deriving a traffic characteristics model that can be used to forecast the traffic volume for intelligent telecommunication services. A sort of regression analysis with dummy variables is used to represent the service quantitatively and to construct the traffic characteristics model. Recursive least squares estimation, which is a special case of the Kalman filter, is applied to the traffic characteristics model to forecast the traffic volume. In the proposed modeling and forecasting, qualitative factors representing a certain service attribute are selected and using an information criterion, the model with the best fit is identified as the most suitable forecasting model. Numerical results using practical observation data showed that the proposed method produces an accurate forecast and is thus effective for practical use.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Forecasting Traffic Volumes for Intelligent Telecommunication Services Based on Service Characteristics
T2 - IEICE TRANSACTIONS on Communications
SP - 2487
EP - 2494
AU - Takeshi YADA
AU - Isami NAKAJIMA
AU - Ichiro IDE
AU - Hideyo MURAKAMI
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E81-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 1998
AB - A method is proposed for deriving a traffic characteristics model that can be used to forecast the traffic volume for intelligent telecommunication services. A sort of regression analysis with dummy variables is used to represent the service quantitatively and to construct the traffic characteristics model. Recursive least squares estimation, which is a special case of the Kalman filter, is applied to the traffic characteristics model to forecast the traffic volume. In the proposed modeling and forecasting, qualitative factors representing a certain service attribute are selected and using an information criterion, the model with the best fit is identified as the most suitable forecasting model. Numerical results using practical observation data showed that the proposed method produces an accurate forecast and is thus effective for practical use.
ER -
English
