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.