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使用机器学习和一组可解释的AI技术来预测速度和对附近道路的影响分析

Meherun Nesa1, Young Yoon2

  • 1Department of Computer Engineering, Hongik University, Seoul, 04066, South Korea.

Scientific reports
|October 25, 2024
PubMed
概括

这项研究使用先进的人工智能来预测交通速度,并确定了关键的贡献道路. 这些发现使得有针对性的交通控制能够有效地缓解城市网络的拥堵.

关键词:
可解释的人工智能智能运输系统 智能运输系统公路速度预测预测.

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
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