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- W3113011773 abstract "To address the problem of keeping the formation for multiple vehicles, this paper proposes a novel algorithm based on non-dominated sorting genetic algorithm II (NSGA- II) and deep convolutional neural network(DCNN). Firstly, the problem of keeping the formation for multiple vehicles is translated into three objective functions. Secondly, NSGA- II is used to optimize and a strategy is designed to choose the guidance command from Pareto solution set. Thirdly, in order to improve the calculation speed, a 19-layer deep learning model is built based on DCNN, residual network and batch normalization layer, then a correction part is designed to avoid the phenomenon that the accumulation of generalization error will brings obvious error on keeping the formation. Finally, three sets of simulation demonstrate the effectiveness of this algorithm." @default.
- W3113011773 created "2020-12-21" @default.
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- W3113011773 date "2020-11-27" @default.
- W3113011773 modified "2023-10-18" @default.
- W3113011773 title "A novel algorithm to keep the formation for multiple vehicles based on NSGA and DCNN" @default.
- W3113011773 doi "https://doi.org/10.1109/icus50048.2020.9275022" @default.
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