计算机科学
人工神经网络
人工智能
培训(气象学)
操作员(生物学)
样品(材料)
质量(理念)
机器学习
深度学习
专家系统
基因
认识论
物理
哲学
气象学
转录因子
抑制因子
化学
生物化学
色谱法
作者
Lei Zhang,Shengtao Liu,Jiaojiao Li
出处
期刊:2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC)
日期:2020-06-01
标识
DOI:10.1109/itoec49072.2020.9141716
摘要
It is necessary to evaluate operation level of drivers while training them through a driving simulator. In order to avoid the one-sidedness of evaluation only based on vehicle driving conditions or operating logic, a deep learning method is proposed to train the LSTM network using driving data and manual evaluation results to obtain an intelligent evaluation system. In order to generate sample data for training, an expert system based on production rules is constructed. By training the neural network, the evaluation method is more flexible and adaptable than traditional expert systems, which can intelligently evaluate the driver's operation quality.
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