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Updated: Jun 25, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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可解释的机器学习用于评估高速公路撞车严重程度的风险因素

Seyed Alireza Samerei1, Kayvan Aghabayk1

  • 1School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.

International journal of injury control and safety promotion
|May 20, 2024
PubMed
概括

可解释机器学习揭示了影响碰撞严重性的因素. 轻量化交通,大型卡车,高速,年轻司机和夜间驾驶增加了伊朗高速公路上严重撞车的风险.

关键词:
可以解释性 解释性累积的局部效应.碰撞严重程度的严重程度.机器学习方法 机器学习方法

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