Ship & Boat ›› 2021, Vol. 32 ›› Issue (04): 89-93.DOI: 10.19423/j.cnki.31-1561/u.2021.04.089

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Application of Ship Wireless Communication Based on Deep Learning Technology

YAN Chao, FU Yu-jia   

  1. Marine Design & Research Institute of China, Shanghai 200011, China
  • Received:2020-07-15 Revised:2021-05-09 Online:2021-08-25 Published:2021-09-13

基于深度学习技术的舰船无线通信应用研究

阎超, 傅雨佳   

  1. 中国船舶及海洋工程设计研究院 上海200011
  • 作者简介:阎 超(1987-),男,硕士,工程师。研究方向:船舶通信系统。傅雨佳(1989-),男,硕士,工程师。研究方向:指挥管理系统和过程建模。

Abstract: Artificial intelligence (AI) technology has been deeply applied in various industries. The future AI technology will be used in different scenarios and will develop towards the direction of differentiation, through the best model and algorithm design to match the features of the scenarios. This article presents the technical principle and state-of-art of the AI technology. The deep learning technology is introduced into the ship wireless communication application. A deep learning neural network with the temporal order memory is designed according to the characteristics of the ship platform. The key theory and engineering technology related to the application of the neural network modeling are also analyzed. It can provide reference for the application of the AI technology in the communication subdivision of the ship platform.

Key words: artificial intelligence, ship wireless communication network, deep learning, temporal order memory, neural network model

摘要: 随着人工智能技术在各产业应用领域的深入,未来的人工智能技术也将应用于不同的落地场景中,会向着差异化方向发展,并通过最佳的模型和算法设计匹配场景特征。该文介绍了人工智能技术原理及发展现状,将深度学习技术引入舰船无线通信网络应用领域,基于舰船平台特点设计具有时序记忆特征的深度学习神经网络,分析神经网络模型实现落地应用有关的关键理论和工程技术,为舰船平台通信细分领域应用人工智能技术提供参考。

关键词: 人工智能, 舰船无线通信网路, 深度学习, 时序记忆, 神经网络模型

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