摘要
物联网感知层的关键数据查询结果直接影响船舶避碰系统的性能,针对当前物联网感知层的关键数据查询效率差,查询精度低等不足,提出一种新型的物联网感知层的关键数据查询算法。首先对当前物联网感知层的关键数据查询研究进行分析,指出当前算法存在局限性的原因,然后采用聚类算法对物联网感知层数据进行聚类分析,降低数据冗余,并采用群智能优化算法对物联网感知层的关键数据进行查询,最后的物联网感知层的关键数据查询仿真测试结果表明,本文算法可以快速、准确找到物联网感知层的关键数据,比其它算法的物联网感知层的关键数据查询结果更优。
The key data query results of the IOT perception layer directly affect the performance of the ship collision avoidance system. In view of the poor efficiency of the key data query and the low query precision, a new key data query algorithm for the IOT perception layer is proposed. First, this paper analyzes the key data query in the current IOT perception layer, points out the reasons for the limitations of the current algorithm, and then uses clustering algorithm to cluster analysis of the IOT perception layer data to reduce the data redundancy, and uses group intelligent optimization to query the key data of the IOT perception layer, and the final object connection. The simulation test results of the key data query of the network perception layer show that the algorithm can quickly and accurately find the key data of the IOT perception layer, which is better than the key data query results of the other algorithms.
引文
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