… energy conservation, smart cities, smart grids, etc. With the large-scale deployment of smart
… of various machine learning algorithms, non-intrusive load monitoring has aroused the …

… used in controls and machine learning applications. Interval … in decision-making and machine
learning, then introduces basic … applications in controls and machine learning. Finally, it …

… and scheduling task and achieve energy saving and economic operation of electric power
management system (EMS). In this paper, the periodic similarity of power load fluctuation cha…

… The results of this paper show that DNFS is a new deep learning method, which not only has
… His research interest covers machine learning, fuzzy systems and intelligent transportation …

… The feasibility of using the double-layer pseudo-spectral method to optimize the energy
management strategy of HEVs was discussed. Firstly, based on signal phases and timing, the …

… lay out the standards that China’s Industrial Control System cyber ranges should aspire to
meet. … Some researchers are using an AI technique, reinforcement learning, to determine and …

… Reform of the government administration system and the judicial system continued to …
We will implement the strategy for intellectual property rights. We will make the best use of …

To promote the organic integration of object detection and business knowledge in the electric
power field, alleviate the problem of long-tailed distribution among fitting samples, and …

… , intelligent sensing, cognitive computing, machine learning, and swarm intelligence.The
Ministry of Science and Technology has reportedly tasked a team of experts to draft a plan for …

… -machine teaming on target acquisition, there is also discussion of ‘autonomous planning
ability’ (自主规划能力) that suggests greater inclusion of machine learning and autonomy.…