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基于神经网络的短电弧覆盖次数最优化模型研究

Research on Optimization Model of Short Arc Coverage Times Based on Neural Network

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【作者】 李杰孙炜范凯旋商庆清

【Author】 LI Jie;SUN Wei;FAN Kai-xuan;SHANG Qing-qing;College of Mechanical and Electronic Engineering, Nanjing Forestry University;

【通讯作者】 商庆清;

【机构】 南京林业大学机械电子工程学院

【摘要】 研究六边形覆盖模型,并基于六边形模型,对短电弧最少覆盖次数进行优化,最后利用BP神经网络对最少次数进行预测与验证,最后得出,BP神经网络对短电弧最少覆盖次数能够精准预测,预测误差小。

【Abstract】 The hexagonal coverage model was studied, and based on the hexagonal model, the minimum coverage times of short arcs were optimized.Finally, the BP neural networkwas used to predict and verify the minimum times.Finally, it was concluded that the BP neural network could accurately predict the minimum coverage times of short arcs, with small prediction errors.

  • 【文献出处】 林业机械与木工设备 ,Forestry Machinery & Woodworking Equipment , 编辑部邮箱 ,2022年03期
  • 【分类号】TG661;TP183
  • 【下载频次】242
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