4 results about "Average path length" patented technology

This invention discloses a method and system for three-dimensional optimization of pedestrian networks with the goal of improving traffic efficiency. The method includes: acquiring image data of the road system; preprocessing and simplifying the image data to construct a road network dataset containing multiple road nodes; establishing an optimization objective function based on the average path length of the three-dimensional pedestrian passage and the number of turns in the underpass; performing simulation optimization on the objective function according to preset constraints and the road network dataset to obtain the optimal solution composed of road nodes; optimizing the pedestrian network based on the optimal solution, calculating the optimized traffic efficiency index, and optimizing the simulation optimization process based on the traffic efficiency index. This invention not only improves the accuracy and flexibility of three-dimensional pedestrian network optimization but also enhances user comfort and satisfaction, providing a more scientific and flexible solution for urban planning and construction.

This invention belongs to the field of machine tool cutting state monitoring and intelligent control technology, specifically relating to a method for controlling the cutting state of a tool during the boring process of a space frame member. The method includes: real-time acquisition and preprocessing of multi-dimensional cutting data during the boring process to obtain a basic feature sequence; calculation of the ratio of the average effective cutting power of the sliding window to the instantaneous material removal rate, and obtaining a steady-state cutting energy index after deducting the initial cutting energy benchmark; calculation of the time-dependent decay weight of historical samples using an exponential decay function, and then obtaining the drift compensation boundary probability through root mean square fusion to dynamically correct the isolation forest model's decision boundary; further fusion of the average path length and normalization constant, and obtaining an anti-baseline drift correction anomaly score through the product of the exponential term and the logarithmic suppression term; setting a safety threshold, and performing anti-chipping closed-loop control based on the comparison result between the anomaly score and the threshold. This invention improves the accuracy of tool control during the boring process of space frame members.

The application relates to the technical field of distributed computing, and discloses an information collaborative processing method and system in a distributed environment, which comprises the following steps: acquiring node connection relations to form a global connection dataset, calculating node connection degrees, average path lengths and comprehensive load scores; screening high-stability nodes as candidate backbones, and selecting a minimum backbone set to cover all non-backbones; periodically collecting local state characteristic vectors of the non-backbones, collecting global state information, and redundantly storing the global state information in the non-backbones after encoding by using a Vandermonde matrix; monitoring backbone abnormalities to trigger reconstruction, and acquiring encoded blocks from the non-backbones by a new backbone node to recover the global state information through error correction code decoding; and publishing an updated task list and routing instruction according to the recovered information to complete collaborative relationship reconstruction. The method can realize reliable storage and rapid recovery of global state information, and significantly improves the self-adaptability, fault tolerance and collaborative efficiency of a distributed system.

The application discloses a kind of local environment driving-based deep reinforcement learning path planning method, belong to mobile robot technical field, for the autonomous navigation and obstacle avoidance of mobile robot in complex environment.The method first constructs obstacle profile model according to the obstacle point information in local environment;Then local environment graph structure between obstacle and robot is constructed using undirected graph, spatial features and deep feature information in local environment are extracted using graph attention network;Then the optimal local target point is obtained using local target driving mechanism;Finally, the optimal path planning strategy is trained by fusing deep reinforcement learning.The application guides local target point and enhances the key features in local environment by graph attention network reinforcement learning, improves the local environment perception ability of robot, enhances the path planning ability of robot in complex environment, can significantly shorten the average path length while improving the navigation success rate, enhances trajectory smoothness.