船舶物联网远程监控数据分类处理

Classification and processing of remote monitoring data in ship internet of things

传统方法在处理船舶远程监控数据分类问题时会倾向于单一处理,导致分类结果过于分散,且处理速度过慢,不利于对船舶远程监控数据的整体分析,为此提出并设计了船舶物联网远程监控数据分类处理方法。利用动态数据的映射反应对多维空间内的远程监控数据进行标记,并确定分类处理的数据范围,引用BP神经网络算法,对远程监控数据进行分类计算,将监控数据执行分类处理逻辑,实现远程监控数据的分类过程。仿真实验结果表明,设计的数据分类方法能够实现远程监控数据的有序、紧密分类,且数据处理速度比传统方法的处理速度高出23.1%,具备极高的有效性。

Traditional methods tend to deal with the classification of ship remote monitoring data in a single way,which results in the classification results being too scattered and the processing speed too slow, which is not conducive to the overall analysis of ship remote monitoring data. For this reason, a classification method of ship remote monitoring data in the Internet of Things is proposed and designed. The mapping response of dynamic data is used to mark the remote monitoring data in multi-dimensional space, and determine the data range of classification processing. The BP neural network algorithm is used to classify and calculate the remote monitoring data. The classification processing logic of monitoring data is implemented to realize the classification process of remote monitoring data. The simulation results show that the designed data classification method can achieve orderly and compact classification of remote monitoring data, and the data processing speed is 23.1% faster than the traditional method, which has a very high efficiency.