Research on the clustering algorithm of ocean big data based on self‐organizing neural network
Yongyi Li, Zhongqiang Yang, Kaixu Han
Abstract
Abstract 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.