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Author: search.filters.author.Ardhan, S.

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    Item type:Publication,
    ANN based NGN IP traffic prediction in Thailand
    (2007-12-01)
    Satsri, S.
    ;
    Ardhan, S.
    ;
    Chutchavong, V.
    ;
    Sangaroon, O.
    This paper presents a study of using Artificial neural network (ANN) in predicting IP traffic fluctuation in IP based next generation network (NGN) in Thailand. By analyzing the time level correlation of traffic flow over TOT IP core network, monitor by the Multi Router Traffic Grapher (MRTG) from January,2006 to December, 2006 at Latya and Phrakhanong exchange. For comparison purposes, the back propagation learning algorithms are considered, in particular, optimization techniques with statistical methods prediction such us Double Exponential smoothing, Lest Square Methods and Adaptive response rate simple exponential smoothing method are applied for predicting the same node of problems. Computational results by using the data monitoring at Latya exchange for training and actual traffic in Phrakhanong area to check prediction correctness show that the based ANN method obtained better results, it can be prediction more precisely. © ICROS.
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    Improved model for traffic fluctuation prediction by neural network
    (2007-12-01)
    Ardhan, S.
    ;
    Satsri, S.
    ;
    Chutchavong, V.
    ;
    Sangaroon, O.
    The traffic prediction are mainly used to improve the performance of telecommunication network management. This paper improved model for telephone traffic prediction in Thailand by using artificial neural network (ANN) with back propagation learning algorithms. By applied data which is collected at different node in main routes of TOT, Thailand telephone network for learning process and testing. The neural network structure and input/output musters are descried in detail. We present the comparatively results of simulation with another methods, the results shows traffic fluctuation prediction by the method of ANN is accurately. ©ICROS.