Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and the El Niño phenomenon. This paper proposes …
目前主要从时空角度出发对海洋三维温度场进行预测，却忽略了相邻位置的海温相关关系。为弥补这一不足，构建一种融合了自注意力记忆模块与卷积式长短时记忆神经网络（ConvLSTM）模型的SA-ConvLSTM三维温度场预测模型，不仅可以从历史三维温度场中提取海温时空特征，还能获取并记忆相邻点位置信息，从而实现对三维温度场时空变化的把握。实验结果表明：相较于 …
Accurately and effectively estimating of the barrier layer thickness (BLT) is essential for the research of ocean thermodynamics, ocean dynamics, and air-sea interaction. …
海洋次表层的热力结构对于海洋环流和全球气候变化具有重要的意义。提出一种新的融合高斯混合模型(gaussion mixture model, GMM)和 轻量级梯度提升机(light gradient boosting machine, LightGBM)算法的海洋次表层温度(ocean subsurface temperature, OST)反演 模型，利用 …
Estimating the ocean subsurface thermal structure (OSTS) based on multisource sea surface data in the western Pacific Ocean is of great significance for studying ocean dynamics …
Using the data of three M eteorological Stations at Fushan, Jiʼnan and Juxian, 2000-2003, the Elman neural network model was established to estimate the daily solar irradiance. The …