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Modeling non linear real processes with ANN techniques

机译:使用ANN技术为非线性真实过程建模

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In this paper we are interested to model real process by applying artificial neural networks technique. The performance and the aptitude of two types of this technique (multilayer perceptron neural network (MLP) and a radial basis function neural network (RBF)) are compared and applied for identifying non linear system of internet traffic network processes. In term of statistical criteria, the obtained results show the advantages of the developed model based on the RBF to describe the internet traffic.
机译:在本文中,我们有兴趣通过应用人工神经网络技术对真实过程进行建模。比较了两种技术(多层感知器神经网络(MLP)和径向基函数神经网络(RBF))的性能和适用性,并将其应用于识别互联网交通网络过程的非线性系统。从统计标准来看,所得结果显示了基于RBF的模型描述互联网流量的优势。

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