KEYWORDS: Data transmission, Matrices, Antimony, Systems modeling, Power grids, Convex optimization, Fiber optic communications, Device simulation, Data modeling, Spectral density
To reduce the transmission latency of the grid differential protection scenario, a low-latency data transmission technique is proposed in this paper. A multi-path low latency routing optimization strategy based on task assignment is considered to find the optimal and sub-optimal transmission paths in the current network environment with the transmission latency as the weight, and then jointly assign the number of tasks to be transmitted on both paths according to their link bandwidth, node queue length, and other network resources to achieve multi-path task transmission and minimize the task transmission latency. The simulation results show that the proposed multi-path task transmission has lower transmission delay and higher network resource utilization than single-path task transmission and evenly split task transmission.
KEYWORDS: Education and training, Detection and tracking algorithms, Convolutional neural networks, Perceptual learning, Visualization, RGB color model, Decision making, Mathematical optimization, Deep convolutional neural networks, Control systems
For the path planning problem of overhead transmission net sealing robot in the process of sealing network, a visual perception and decision method based on deep reinforcement learning is proposed. By combining the perceptual capability of convolutional neural networks with the decision-making capability of reinforcement learning, the method achieves direct output control from the visual perception input of the environment to the action through end-to-end learning, forming a closed loop between the system environment perception and decision control directly, and obtaining the optimal decision strategy by maximizing the cumulative reward return of the robot's interaction with the dynamical environment. Simulation experimental results prove that the method can meet the requirements of multi-task intelligent perception and decision making, and better solve the problems of traditional algorithms such as easily falling into local optimum, oscillating in narrow passages and unreachable targets near obstacles, which greatly improve the real-time and adaptability of trajectory tracking and dynamic obstacle avoidance of the net sealing robot and ensure the safe operation of the net sealing robot in transmission line sealing operations.
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