首页|New Data from China University of Mining and Technology Illuminate Findings in M achine Learning (A Generative Model for Vehicular Travel Time Distribution Predi ction Considering Spatial and Temporal Correlations)
New Data from China University of Mining and Technology Illuminate Findings in M achine Learning (A Generative Model for Vehicular Travel Time Distribution Predi ction Considering Spatial and Temporal Correlations)
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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 th e subject of a report. According to news reporting out of Jiangsu, People’s Repu blic of China, by NewsRx editors, research stated, “Vehicular travel time distri butions (TTDs) are of great importance for traffic management and control, and v arious probability distributions have been used for TTD prediction in previous s tudies. However, it is difficult to determine a generalized probability distribu tion of vehicular travel times on urban roads that is applicable to all traffic conditions in real situations.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Postgraduate Research and Practice Innovation Program of Jia ngsu Province.
JiangsuPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChina University of Mining and Technology
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