ATM网络仿真的智能方法

SympoTIC'03. Joint 1st Workshop on Mobile Future and Symposium on Trends in Communications Pub Date : 2003-12-03 DOI:10.1109/TIC.2003.1249096

D. Radev, S. Radeva

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引用次数: 4

摘要

本文介绍了基于时间序列和状态模型的ATM流量预测和仿真的智能方法实现问题的一些研究结果。提出了一种基于神经模糊模型和学习向量量化(LVQ)的预测方法，并给出了随机和远程依赖源模型的实现。

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Intelligent methods for simulation in ATM networks

The paper presents results from a number of investigations into the problems of implementing intelligent methods in the prediction and simulation of ATM traffic, based on time series and state models. A prognosis method based on a neuro-fuzzy model and learning vector quantization (LVQ) is suggested The implementation for stochastic and long range dependence source models is shown.

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来源期刊

SympoTIC'03. Joint 1st Workshop on Mobile Future and Symposium on Trends in Communications

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