机械与电子2025，Vol.43Issue(11)：8-14,7.
基于Bi-LSTM-MLP的水下声速预测
Underwater Sound Speed Prediction Based on Bi-LSTM-MLP
摘要
Abstract
To address the issues of high equipment cost for direct measurement of sound velocity pro-file(SVP)data and low efficiency of frequent observations,a sound velocity profile(SVP)prediction method based on a fusion model of bidirectional long short-term memory network and multi-layer per-ceptron(Bi-LSTM-MLP)is proposed.This model combines the bidirectional long short-term memory network(Bi-LSTM)'s ability to model the dependencies in both directions of time series with the multi-layer perceptron(MLP)'s advantages in nonlinear feature mapping and spatial integration,effectively en-hancing the accuracy and generalization performance of sound velocity profiles prediction.Compared with the Conv-LSTM and Bi-LSTM models under the same conditions,the proposed method improves the mean squared error(MSE)by approximately 43%and 74%respectively.In the prediction results from six different geographical locations,the model's accuracy metric remained stable above 99.91%;while in the monthly continuous prediction at a fixed location,the maximum MSE is controlled at around 0.50 m/s,verifying the model's accuracy and robustness in both temporal and spatial dimensions.关键词
声速预测/深度学习/Bi-LSTM-MLP/SVPKey words
sound speed prediction/deep learning/Bi-LSTM-MLP/SVP分类
信息技术与安全科学引用本文复制引用
周明胡,赵英亮,韩星程,黄嘉瑒,王国祥..基于Bi-LSTM-MLP的水下声速预测[J].机械与电子,2025,43(11):8-14,7.基金项目
国家自然科学青年基金资助项目(62203405) （62203405）
山西省应用基础研究计划项目(202303021212206) （202303021212206）
山西省重点研发计划项目(202202110401015) （202202110401015）
