首页> 外文期刊>Computational Intelligence >Research on the clustering algorithm of ocean big data based on self-organizing neural network
【24h】

Research on the clustering algorithm of ocean big data based on self-organizing neural network

机译:基于自组织神经网络的海洋大数据聚类算法研究

获取原文
获取原文并翻译 | 示例
       

摘要

In the construction of a smart marine, marine big data mining has a significant impact on the growing maritime industry in the Beibu Gulf. Clustering is the key technology of marine big data mining, but the conventional clustering algorithm cannot achieve the efficient clustering of marine data. According to the characteristics of marine big data, a marine big data clustering scheme based on self-organizing neural network (SOM) algorithm is proposed. First, the working principle of SOM algorithm is analyzed, and the algorithm's two-dimensional network model, similarity model and competitive learning model are focused. Secondly, combining with the working principle of algorithm, the marine big data clustering process and algorithm achievement based on SOM algorithm are developed; finally, experiments show that all vectors in marine big data clustering are stable, and the neurons in the output layer of clustering result have obvious consistency with the data itself, which shows the effectiveness of SOM algorithm in marine big data clustering.
机译:在建设智能海军陆战队海军陆战队的建设中,海洋大数据挖掘对北部海湾的日益增长的海事行业产生了重大影响。聚类是海洋大数据挖掘的关键技术,但传统的聚类算法无法实现海洋数据的有效聚类。根据海洋大数据的特点,提出了一种基于自组织神经网络(SOM)算法的海洋大数据聚类方案。首先,分析了SOM算法的工作原理,并聚焦了算法的二维网络模型,相似性模型和竞争学习模型。其次,结合算法的工作原理,开发了基于SOM算法的海洋大数据聚类过程和算法成果;最后,实验表明,海洋大数据聚类中的所有载体都是稳定的,并且聚类结果的输出层中的神经元与数据本身具有明显的一致性,这表明了SOM算法在海洋大数据聚类中的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号