基于自组织神经网络的声速剖面分类方法研究

利用自组织神经网络技术,结合声速剖面特点,研究了声速剖面的描述方法、网络中神经元个数的确定、获胜神经元的邻域及其邻域内神经元的拓扑关系等对网络结构和声速剖面类别划分的影响,给出了分类声速剖面的网络构造思想和神经网络结构。实验验证了该方法的正确性。

Classification of Sound Speed Profile with SOFM Neuron Network

It is very important to classify sound speed profile for analyzing and understanding its variation.In order to eliminate the artificial effect in the classification,self-organization manage feature(SOMF) neuron network is introduced into the work.For the efficient appli-cation of SOMF in the classification,integrated with character of sound speed profile,the expression ways of sound speed profile,the determination of neuron cell number,and the definition of adjacent area neuron cell and the construction of the network in the network are studied.By trainings and experiments of the network,the effect of training times for the frame and performance of the network are analyzed and discussed.Finally,a SOMF network is built which is used for classifying 3 teams sound speed profiles.The results are compared with the results obtained by custom method and proved to be right and credible.