摘要
由一名新闻记者兼机器人与机器学习每日新闻的工作人员新闻编辑-调查人员讨论机器学习的新发现。根据NewsRx编辑S在新加坡的新闻报道，研究表明，“隧道对交通网络至关重要，需要定期检查和结构退化评估，以确保其运营能力。以前，只开发了传统模型来描述隧道的整体退化，在数据改组的情况下，训练的模式LS忽略了对未来场景中历史数据的利用。”这项研究的财政支持者包括国家研究基金会、新加坡国家研究基金会、新加坡教育部一级研究生院、南洋理工大学。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Machine Lea rning. According to news reporting out of Singapore, Singapore, by NewsRx editor s, research stated, “Tunnels are crucial for transportation networks, necessitat ing regular inspection and structural deterioration evaluation to ensure their o perational capacity. Previously, only traditional models have been developed to characterize the overall degradation of tunnels and with data shuffling the mode ls trained ignore the utilization of historical data for future scenarios.” Financial supporters for this research include National Research Foundation, Sin gapore under its AI Singapore Programme (AISG), Ministry of Education Tier 1 Gra nts, Singapore, Nanyang Technological University.
NETL
NSTL