Shenzhen University

Southern Marine Science and Engineering Guangdong Laboratory (guangzhou)

Shenzhen Langcheng Technology Co., Ltd

Hao Qin

Yan Li

Daosheng Wang

Lin Mu

A method, device, computing equipment, and storage medium for predicting the drift of the floating object are provided. A method for predicting drift velocity includes: obtaining environmental characteristic parameters at the location of the floating object to be predicted, wherein the environmental characteristic parameters include wave characteristic parameters; inputting the wave characteristic parameters into a deep learning model for wave-induced drift velocity to obtain the wave-induced drift velocity; wherein the deep learning model for wave-induced drift velocity is trained based on first sample drift data, wherein the first sample drift data includes observed drift velocity of sample floating objects, corresponding sample water surface flow characteristic parameters, sample wind characteristic parameters, and sample wave characteristic parameters.

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Shenzhen, China

Hao Qin