… In the componentized taxonomy, knowledge enhanced data-driven, data optimized
knowledge-driven, and complementary knowledge and data driven methods are introduced. Finally, …

… knowledge-driven methods based on relevant knowledge are used in road extraction work.
On … this study divides the knowledge-driven methods by three kinds: geometric knowledge …

… in the intelligent traffic management system, autonomous driving system, and cooperative
vehicle-… Knowledge-driven service offloading decision for vehicular edge computing: a deep …

… Optimal coordination of platoons of connected and automated vehicles at signal-free
intersections. IEEE Transactions on Intelligent Vehicles, 2022, 7(2): 186-197 doi: 10.1109/TIV.…

… In the current era of a knowledge-driven economy, higher education plays a crucial role in
the overall socio-economic growth of any region or country. No society can progress without …

… Knowledge-driven deep deterministic policy gradient for robotic multiple peg-in-hole …
Advanced planning for autonomous vehicles using reinforcement learning and deep inverse …

… This paper aims to look at two successful economies Ireland and Taiwan, and analyze the
driving forces behind the success of each economy by looking at the entrepreneurial behavior …

… UG/NX 软件的知识驱动自动化系统 UG/NX 软件提供了知识驱动自动化 (Knowledge driven
automation, KDA)解决方案,集成 了Intent 语言,推出知识熔接模块UG/KF (Knowledge fusion),将…

Software Engineering Environments (SEEs) aim at providing an integrated and coherent set
of tools for managing the design, construction, testing, use, and eventual reuse of software, …

… -precision prediction for autonomous vehicles in heterogeneous, … trajectory prediction for
autonomous driving. Based on this, the … Vehicle trajectory prediction by knowledge-driven LSTM …