Titlebook: Advances in Smart Vehicular Technology, Transportation, Communication and Applications; Proceedings of VTCA Tsu-Yang Wu,Shaoquan Ni,Margar

乞丐

Collaborative Control of Unmanned Vehicle Matrix Formation Based on Autonomous Neighborhood Negotiatintenance of unmanned vehicle formation in the leader-slave mode with a single leader. This method can provide a low-cost and high-reliability cooperative control scheme for large-scale unmanned vehicle formation performance.

Generic-Drug

QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selectionning set of the sample, and then use the K Nearest Neighbor (KNN) algorithm for feature classification. In the optimization process, we use a threshold (.) for feature identification to select useful features. Finally, the 9 standard test data sets in UCI are used to verify the effectiveness of the QUATRE algorithm.

forecast

Serenity

Thomas Bladh,David A. Carr,Jeremiah Scholl optimization algorithms shows that this model has better prediction accuracy, stability, and robustness. GRU neural network has associative memory function, simple structure, small amount of calculation, and anti-noise ability, so it is worth popularizing in subway passenger flow prediction applications.

哥哥喷涌而出

Mortar

Łukasz Jeleń,Michał Kulus,Tomasz Jurekhich the packing module is designed by tree search algorithm combined with the deepest and leftmost algorithm. Finally, the real data of China Railway Express Chengdu branch are taken as a case to verify the feasibility of the model and algorithm. Combined with the results of the algorithm, some suggestions are put forward.

懒惰人民

Michal Czolombitko,Jaroslaw Stepaniukts. Therefore, we propose a reduction algorithm for removing the unwanted subsequence of .. Furthermore, we introduced a direct construction method to generate one-row test sequence, which satisfy t-way permutations coverage of n events.

吹牛需要艺术

debunk

Oration

Distribution Vehicle Routing Optimization Based on 3D Loadinghich the packing module is designed by tree search algorithm combined with the deepest and leftmost algorithm. Finally, the real data of China Railway Express Chengdu branch are taken as a case to verify the feasibility of the model and algorithm. Combined with the results of the algorithm, some suggestions are put forward.