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首页> 外文期刊>Robotics & Machine Learning Daily News >Researchers from Southwest Jiaotong University Describe Findings in Machine Learning (A Simulation and Machine Learning Based Optimization Method for Integrated Pedestrian Facilities Planning and Staff Assignment Problem In the Multi-mode Rail …)
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Researchers from Southwest Jiaotong University Describe Findings in Machine Learning (A Simulation and Machine Learning Based Optimization Method for Integrated Pedestrian Facilities Planning and Staff Assignment Problem In the Multi-mode Rail …)

机译:西南交通大学的研究人员在机器学习(描述的发现仿真和基于机器学习的优化方法综合行人设施规划和员工分配问题在多模铁路…)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting out of Chengdu, People’s Republic of China, by NewsRx editors, research stated, “To face the booming passenger flow volumes, the optimization of pedestrian facilities plans and the associated staff assignment plans in the transfer station, including adjusting pedestrian flow routes and adopting different numbers of machines, is an efficient measure to promote transfer connection and avoid passengers congestion in order to enhance the service level. We propose an integrated optimization model based on the simulation model and machine learning method aiming to provide optimal pedestrian facilities plans and the corresponding staff assignment simultaneously.”
机译:机器人技术与新闻记者新闻编辑机器学习每日新闻每日新闻——新机器学习是研究的主题报告。成都、中华人民共和国、NewsRx编辑,研究指出:“面对蓬勃发展客流总量,优化行人设施计划和相关的员工作业计划在换乘站,包括人流路线和调整采用不同数量的机器,是一个有效的措施促进传输连接,避免乘客拥堵为了提高服务水平。基于集成优化模型仿真模型和机器学习方法旨在提供最佳行人设施计划和相应的人员分配同时。”

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