相关实验视频

Updated: Sep 16, 2025

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

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通过将反向传播网络与多变量地质物理数据集成,提高水下地形估计

Qiaoqiao Yang1, Zhiqiang Wei2, Lei Huang1

  • 1Faculty of Information Science and Engineering,Ocean University of China, Qingdao, PR China.

Marine pollution bulletin
|July 8, 2025
PubMed
概括

这项研究使用了新的三通道BP神经网络 (MFT-BP) 进行海底地形反转,整合了多个地球物理数据源. 与传统方法相比,MFT-BP模型显著提高了深度预测的准确性.

关键词:
这是BP网络,BP网络.重力数据重力数据在MFT-BP网络中,海底的地形图是海底的地形图.

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