BP NEURAL NETWORK-BASED SMOG ENVIRONMENT AND THE RISK MODEL OF MOOD DRIVING

作者：You, Z.; Liu, J.^*; Dai, J.; Liu, W.; Song, W.; Wang, X.; Zhang, C.

来源：Applied Ecology and Environmental Research, 2017, 15(3): 1753-1763.

DOI：10.15666/aeer/1503_17531763

• environmental engineering
• driving safety
• smog
• human factor
• profile of mood state

In order to evaluate and study the influence of smog environment on driving safety, this paper utilizes the measurability of mood states, adopts back propagation (BP) artificial neural network instrument to establish a smog-risky mood network model. Six pictures in different smog levels were used as emotional stimuli to verify the BPM neural network-based smog-risky mood relation model. The result shows that the smog is a main factor affecting the driver's mood. The method of estimating moods based on the smog environment of BP network is able to predict 70% of the danger. It was proved to be an effective means for the safety management and self-detection of drivers, especially professional drivers.

• 出版日期2017
• 单位北京邮电大学; 武汉工程大学; 北京工业大学; 华侨大学; 北京师范大学