首页|New Study Findings from Tongji University Illuminate Research in Machine Learnin g (Research on DCT shift strategy for various driving style based on 'driver-veh icle-cloud' machine learning)
New Study Findings from Tongji University Illuminate Research in Machine Learnin g (Research on DCT shift strategy for various driving style based on 'driver-veh icle-cloud' machine learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting from Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “In order to solve th e problem that the DCT static shift strategy cannot adapt to the difference in d riving style, the driving style identification model based on multi-dimensional data mining and intelligent algorithm heavily depends on vehicle terminal data s torage and calculation, an intelligent shift strategy based on “driver-vehicle-c loud” cooperative control is proposed.” Financial supporters for this research include National Natural Science Foundati on of China.
Tongji UniversityShanghaiPeople’s Re public of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSupport Vector MachinesVector Machines
NETL
NSTL
