신경망을 이용한 ATM 망에서 트래픽 제어에 관한 연구 = A Study on the Traffic control using Neural Network in ATM Networks

다국어 초록 (Multilingual Abstract)

A traffic control using back-propagation neural networks propose for the ATM communications networks. This paper proposes adaptive call admission control using back-propagation algorithm in link capacity control.
In this paper, back-propagation algorithm is trained to estimate call admission rate from traffic load and link capacity, and link capacity assignment is optimized by back-propagation algorithm method which used learning rate and moment term.
Therefore, simulation results yield efficient ATM traffic control which use neural networks training between quality of service(QOS) and traffic parameter in the number of class 1, 2 and evaluate call loss rate 10exp(-6) using the Erlang-Bequation by trained back-propagation neural networks.