首页|Investigators from Southeast University Release New Data on Machine Learning (Wh at Influences Intermodal Choices: Metrocentric, Bus-centric, Hybrid? Insights F rom Machine Learning Approaches)
Investigators from Southeast University Release New Data on Machine Learning (Wh at Influences Intermodal Choices: Metrocentric, Bus-centric, Hybrid? Insights F rom Machine Learning Approaches)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published.According to news reporting originating in Nanjing, Peo ple’s Republic of China, by NewsRx journalists, research stated, “Three types of intermodals are defined: bus-centric, metro-centric, and hybrid, each represent ing combinations of bus, metro, and a mix of metro and bus with other travel mod es for a trip, respectively.Using the household survey from Nanjing, China, com prising 162,191 trips, we applied the multiple models to reveal the nonlinear ef fects of socio-demographic and travel-related attributes on intermodal travel ch oices.”Funders for this research include National Natural Science Foundation of China ( NSFC), Science and Technology Project of Hebei Education Department.
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSoutheast University
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