首页|Researchers at Shenzhen University Release New Data on Machine Learning (Analysis of the Relationship Between Metro Ridership and Built Environment: a Machine Learning Method Considering Combinational Features)
Researchers at Shenzhen University Release New Data on Machine Learning (Analysis of the Relationship Between Metro Ridership and Built Environment: a Machine Learning Method Considering Combinational Features)
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NETL
NSTL
Elsevier
A new study on Machine Learning is now available. According to news reporting out of Shenzhen, People's Republic of China, by NewsRx editors, research stated, "Limited studies have examined the relationship between combinational features of the built environment and metro ridership. In this study, we applied the gradient boosting regression tree (GBRT) to explore the non-linearity effects for metro commuter ridership and non-commuter ridership, respectively." Financial support for this research came from National Natural Science Foundation of China (NSFC).
ShenzhenPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningShenzhen University
NETL
NSTL
Elsevier
