Research on HF Radio Propagation on the Sea by Machine Learning Optimized Model

2018 International Conference on Civil and Hydraulic Engineering

土木建筑工程;水利工程

Song, Yining^1 ; Wang, Meng^2 ; Yuan, Qing^3

School of Mathematical Sciences, Yangzhou University, Yangzhou, Jiangsu

225000, China^1

School of Mechanical Engineering, Yangzhou University, Yangzhou, Jiangsu

225000, China^2

School of Environmental Science and Engineering, Yangzhou University, Yangzhou, Jiangsu

225000, China^3

关键词: Continuous functionals;    Energy attenuation;    Environmental parameter;    Functional relationship;    HF radio propagation;    Matlab programming;    Multi-objective optimization models;    Optimal transmission;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/189/6/062047/pdf
DOI  :  10.1088/1755-1315/189/6/062047

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

In order to research HF radio propagation, the energy attenuation of HF radio propagation in the transmission process has been studied, especially under the condition of sea surface with wind waves. A multi-objective optimization model is obtained by the method of machine learning. First, A multi-objective optimization model(M-BOM) were set up, which is based on machine learning to calculate the signal energy loss. The optimal transmission target is achieved by determining the control variable frequency and launching angle. Meanwhile, the database of equivalent virtual height is established by using the global map data. Next, the method machine learning is used to synthesize continuous functional relationships from data that is called from the database each time. Through these functional relationships, the minimum energy loss solution can be obtained with any environmental parameter. Additionally, we get the generate energy loss and launch angle of specific values and maximum jump hops through MATLAB programming.