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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45

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相关实验视频

Updated: Jun 13, 2025

Operation of the Collaborative Composite Manufacturing CCM System
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一种基于代理的方法,用于特征识别和路径优化计算机数控加工轨迹.

Purui Li1,2, Meng Chen1,2, Chuanhao Ji1,2

  • 1Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
概括

本研究介绍了一种基于智能代理的方法,用于优化CNC加工路径. 该方法使用深度学习来识别特征和高级算法来平滑工具路径,减少智能制造中的缺陷.

关键词:
这个系统是CNC系统.深度学习是一种深度学习.功能识别 功能识别功能识别智能元素是一个智能元素.路径优化路径优化过程分析 流程分析

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科学领域:

  • 制造业 工程 制造工程
  • 人工智能的人工智能
  • 计算机辅助制造 计算机辅助制造

背景情况:

  • 传统的CNC加工通常会产生缺陷,原因是G01对线运动命令导致路径曲率不连续性.
  • 智能制造越来越多地利用人工智能,特别是深度学习,用于几何形状的特征识别.

研究的目的:

  • 用智能代理提出CNC加工轨迹特征识别和路径优化的新方法.
  • 解决和减轻因工具路径不连续而引起的加工缺陷.

主要方法:

  • 智能代理用于G码分析和几何信息提取.
  • 用线性注意力和多个神经网络的MCRL深度学习模型用于识别和分类.
  • 路径优化通过平均选,贝齐尔曲线拟合和一种新的自适应性coati优化算法 (NACOA) 来实现.

主要成果:

  • 拟议的方法显著提高了CNC加工路径的流性.
  • 通过优化工具轨迹,加工缺陷被大大减少.
  • 验证是在轮,五角形老板和叶模型上进行的.

结论:

  • 基于智能代理的方法为提高CNC加工质量提供了可行的解决方案.
  • 该方法通过提高路径平滑性和减少缺陷,在智能制造中展示了实质性的应用价值.