摘要
为提高船舶航运安全和智能化管理,可采用船联网技术将航运场合中涉及到的多类事物通过无线网络连接在一起。由于船联网中存在多类别海量数据,需要网络中专门的处理设备针对网络数据开展处理,进行分类。为了避免数据处理导致的高延时,提高网络数据传输的效率,可采用BP神经网络来进行分类,提高处理速度,克服船联网中由于高纬度、海量数据导致传输效率低的瓶颈。并通过实验验证了算法的可行性。
In order to enhance shipping safety and manage ships intelligently,we connect these things in shipping occasions together over a wireless network. Because there are many kinds of data in the internet of vessels,there needs to be a processing equipment to classify these massive amounts of data. In order to avoid high latency caused by data processing, and improve the efficiency of network data transmission,we use the BP neural network to classify. At the same time,overcome the ship networking transmission efficiency is low due to high latitudes,huge amounts of data in the bottleneck. Finally,the experiment result shows that the algorithm is effective.
出处
《舰船科学技术》
北大核心
2016年第2X期133-135,共3页
Ship Science and Technology
关键词
船联网
通信数据
BP神经网络
internet of vessels
communication data
BP neural network
