学习向量量化神经网络在多波束底质分类中的应用研究
Seafloor Classification from Multibeam Backscatter Data Using Learning Vector Quantization Neural Network
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摘要: 利用多波束测深系统获取的反向散射强度数据,应用学习向量量化(learning vector quantization,LVQ)神经网络分类方法实现了对海底砂、砾石和基岩等底质类型的快速、有效的识别。通过比较,证明了该方法能较好地区分出不同海底底质类型。Abstract: We utilize the seafloor backscatter strength data of each beam from multibeam sonar systems and the automatic classification technology to get the seafloor type identification maps.We primarily study on the seafloor classification using learning vector quantization(LVQ) neural network method.Using this classification method,we can rapidly identify all kinds of seafloor types,such as sand,gravel and rock in the experimental surveying areas.