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Updated: Jul 1, 2025

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基于多变量时间序列神经网络模型预测高层建筑机器的姿势

Xi Pan1, Junguang Huang1,2, Yiming Zhang2

  • 1General Engineering Institute of Shanghai Construction Group, Shanghai Construction Group Co., Ltd., Shanghai 200080, China.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
概括

这项研究使用长短期记忆 (LSTM) 和门式循环单元 (GRU) 神经网络来预测高层建筑机器 (HBM) 的姿势. 格鲁模型显示在确保稳定的摩天大楼建设方面更强大的稳定性.

关键词:
高层建筑机器 (HBM) 是指高层建筑机器.多变量时间序列 (MTS)神经网络 (NN) 是一个神经网络.姿势预测 姿势预测钢制平台 (SP) 是一个钢制平台.

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