Fuzzy Neural Network for VBR MPEG Video Traffic Prediction

2005 ◽  
pp. 403-408 ◽  
Author(s):  
Xiaoying Liu ◽  
Xiaodong Liu ◽  
Xiaokang Lin ◽  
Qionghai Dai
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Traffic Prediction ◽  
Video Traffic ◽  
Fuzzy Neural ◽  
Video Traffic Prediction

Fuzzy neural network based traffic prediction and congestion control in high-speed networks

2000 ◽  
Vol 15 (2) ◽  
pp. 144-149 ◽  
Author(s):  
Xiang Fei ◽  
Xiaoyan He ◽  
Junzhou Luo ◽  
Jieyi Wu ◽  
Guanqun Gu
Keyword(s):  
Neural Network ◽  
Congestion Control ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
Traffic Prediction ◽  
High Speed Networks ◽  
Fuzzy Neural

Fuzzy-Neural Network Traffic Prediction Framework with Wavelet Decomposition

2003 ◽  
Vol 1836 (1) ◽  
pp. 16-20 ◽  
Author(s):  
Heng Xiao ◽  
Hongyu Sun ◽  
Bin Ran ◽  
Youngtae Oh
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Wavelet Decomposition ◽  
Fuzzy Neural Network ◽  
Wavelet Denoising ◽  
Traffic Prediction ◽  
Denoising Method ◽  
Fuzzy Neural ◽  
Special Factors

The framework of a traffic prediction model that could eliminate noise caused by random travel conditions is investigated. This model also can quantitatively calculate the influence of special factors. The framework combined several artificial intelligence technologies, such as wavelet transform, neural network, and fuzzy logic. The wavelet denoising method is emphasized and analyzed.

Design of a Novel Variable Bit Rate Video Traffic Prediction Model Based on Neural Networks

2014 ◽  
Vol 989-994 ◽  
pp. 4143-4146
Author(s):  
Zuo Zheng Lian ◽  
Hai Zhen Wang ◽  
Da Hui Li
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Prediction Performance ◽  
Traffic Prediction ◽  
Variable Bit Rate ◽  
Video Traffic ◽  
Vbr Video ◽  
Video Traffic Prediction

The video business has gradually become the main business of the network traffic, video traffic is Variable Bit Rate (VBR), which has nonlinear and sudden features, a single prediction model is not fit for describing those features, and prediction accuracy is not high. Because of wavelet analysis has advantages of multi-resolution and dealing with unexpectedness, and the neural network has better nonlinear fitting characteristics, in order to improve the prediction performance, the paper researched on the problem of VBR video traffic prediction based on neural networks, a novel prediction model AMWM is proposed, the model firstly introducing BP neural network to multi-fractal wavelet model, and designing prediction method, which introduced multi-fractal wavelet model to model VBR video traffic, and then applying BP neural network to forecast scale coefficient decomposed, and forecast multiplier using AR model, and predict traffic generated by wavelet reconstruction. Finally, the model is built and simulated. The experimental result shows that prediction performance based AMWM is better compared with multi-fractal wavelet model.

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