Robotics & Machine Learning Daily News2024,Issue(Nov.29) :52-53.

Findings from Beijing Jiaotong University in the Area of Machine Learning Report ed (Built Environment’s Non-linear Impact On Subway Passenger Flow Through Impro ved Interpretable Machine Learning)

北京交通大学在机器学习领域的发现报告ED(通过改进的可解释性机器学习,建筑环境对地铁客流的非线性影响)

Robotics & Machine Learning Daily News2024,Issue(Nov.29) :52-53.

Findings from Beijing Jiaotong University in the Area of Machine Learning Report ed (Built Environment’s Non-linear Impact On Subway Passenger Flow Through Impro ved Interpretable Machine Learning)

北京交通大学在机器学习领域的发现报告ED(通过改进的可解释性机器学习,建筑环境对地铁客流的非线性影响)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的最新研究结果已经发表。根据研究称,NewsRx记者源于中华人民共和国北京的新闻报道,“了解建筑环境与地铁客流之间的复杂关联可以”为交通运营和城市协调政策的发展提供独特的见解。很少有研究系统地分析了建筑环境变量选择的比值性,并进一步探讨了建筑环境变量选择的探讨了非线性耳朵关系。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According tonews reporting originating in Beijing, Peo ple’s Republic of China, by NewsRx journalists, research stated,“Understanding the complex correlation between the built environment and subway passenger flow canprovide unique insights for the development of transportation operations and urban coordination policies.Few studies have systematically analyzed the ratio nality of selecting built environment variables and furtherexplored the non-lin ear relationships.”

Key words

Beijing/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Beijing Jiaotong University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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