电波科学学报2026，Vol.41Issue(1)：187-196,10.DOI:10.12265/j.cjors.2025011
基于GOA-BP的海域蒸发波导智能预报方法
The intelligent forecasting method of marine evaporation duct based on GOA-BP model
摘要
Abstract
To meet the demand for accurate high-resolution evaporation duct height forecasting over large areas in tropospheric over-the-horizon(OTH)communication,this study proposes a prediction model that integrates the gannet optimization algorithm(GOA)with a back-propagation(BP)neural network,termed the GOA-BP model.First,regional environmental meteorological parameters are obtained using the weather research and forcasting model(WRF)mesoscale numerical model.Then,the evaporation duct height is predicted by combining the NPS model from the U.S.Naval Postgraduate School,creating a joint dataset containing environmental information and forecasted duct height values.Next,the GOA algorithm is introduced to optimize the initial parameters of the BP neural network,significantly enhancing the model's global search ability and convergence speed,thus avoiding the drawback of traditional BP neural networks,which are prone to getting trapped in local optima.Finally,the GOA-BP model is obtained through training.The results show that the coefficient of determination(R2)reaches 0.972 1,with an average verification error(RMSE)of 2.24 meters,demonstrating that the GOA-BP model can more accurately and effectively predict the evaporation duct height.This can provide valuable reference for planning and application of ultra-shortwave/microwave beyond-line-of-sight radar and radio communication systems.关键词
蒸发波导预报/WRF/NPS模型/反向传播(BP)神经网络/塘鹅优化算法(GOA)Key words
evaporation duct prediction/weather research and forecasting model(WRF)/Naval Postgraduate School(NPS)model/back propagation(BP)neural network/gannet optimization algorithm(GOA)分类
信息技术与安全科学引用本文复制引用
文凯,闫晓龙,廖希..基于GOA-BP的海域蒸发波导智能预报方法[J].电波科学学报,2026,41(1):187-196,10.基金项目
国家自然科学基金面上项目(62271095,62171071) （62271095,62171071）
重庆市自然科学基金面上项目(CSTB2022NSCQ-MSX1125) （CSTB2022NSCQ-MSX1125）
重庆市教委科学技术研究项目(KJZD-K202300607) （KJZD-K202300607）
重庆市自然科学基金创新发展联合基金(CSTB2022NSCQ-LZX0037)General Program of the National Natural Science Foundation of China(62271095,62171071) （CSTB2022NSCQ-LZX0037）
General Program of the Natural Science Foundation of Chongqing(CSTB2022NSCQ-MSX1125) （CSTB2022NSCQ-MSX1125）
Science and Technology Research Program of Chongqing Municipal Education Commission(KJZD-K202300607) （KJZD-K202300607）
Innovation and Development Joint Fund of Chongqing Natural Science Foundation(CSTB2022NSCQ-LZ0037) （CSTB2022NSCQ-LZ0037）
