以保障船舶通信网络信号传输安全和快速为目的，设计基于数据挖掘的船舶通信网络信号传输数学模型。该模型采集船舶通信网络信号强度指纹后，以其为基础建立船舶通信网络能耗模型，通过该模型获取当前船舶通信网络能耗，再依据该能耗，根据博弈论选择船舶通信网络最优通信链路，按照该最优通信链路，使用数据挖掘算法中的卷积神经网络构建船舶通信网络信号传输数学模型，利用该模型实现船舶通信网络信号传输。实验结果表明，该模型可有效传输船船舶通信网络信号，传输耗时较小，且网络节点剩余能量较高，应用效果较好。
In order to ensure the safety and speed of signal transmission in ship communication networks, a mathematical model for signal transmission in ship communication networks based on data mining is studied. After collecting the signal strength fingerprint of the ship communication network, this model will establish a ship communication network energy consumption model based on it. The current ship communication network energy consumption will be obtained through this model, and then based on this energy consumption, the optimal communication link of the ship communication network will be selected according to game theory. According to this optimal communication link, a convolutional neural network in data mining algorithms will be used to construct a mathematical model for ship communication network signal transmission, Utilize this model to achieve signal transmission in ship communication networks. The experimental results show that the model can effectively transmit signals from ship to ship communication networks, with less transmission time and higher residual energy of network nodes. The application effect is good.
2023,45(19): 169-172 收稿日期：2023-04-12
DOI：10.3404/j.issn.1672-7649.2023.19.031
分类号：TN929.5
作者简介：赵琳(1983-),女,硕士,讲师,研究方向为数学
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