主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Journal of Meteorology and Environment ›› 2021, Vol. 37 ›› Issue (1): 106-112.doi: 10.3969/j.issn.1673-503X.2021.01.014

• Bulletins • Previous Articles    

Identification of the fog image features on the Yangtze River waterways in Chongqing based on machine learning

Yuan-mou WANG1(),Jia-qi LI1,*(),Shi-ji CHEN1,Jia-ping TANG1,Bai-cheng XIA1,Shi-gang HAN1,2   

  1. 1. Chongqing Meteorological Service Center, Chongqing 401147, China
    2. Meteorological Service at Kaizhou District of Chongqing, Chongqing 405400, China
  • Received:2019-10-28 Online:2021-02-28 Published:2021-01-21
  • Contact: Jia-qi LI E-mail:501242840@qq.com;475499221@qq.com

Abstract:

Based on the image data of fog events taken by radar stations on the Yangtze River waterways in Chongqing, images without fog events and with five types of fog events were trained using algorithms including K-nearest neighbor, support vector machine, back propagation neural network, and random forest.According to the training results, a fog image identification model was built, and the identification accuracy was tested.The results show that machine learning can effectively identify fog images, and random forest performances better than the other three algorithms.The model has a recognition accuracy of 100% for non-fog recognition, over 90% for light fog and strong dense fog events, and over 70% for fog, heavy fog, and dense fog events.

Key words: Fog, Machine learning, Pattern recognition, Graphical user interface

CLC Number: