Meteorological forecast based on image recognition technology

Wang Yi; Cui Sitian; Cao Yu; Cheng Xu

doi:10.1117/12.2681700

1 June 2023 Meteorological forecast based on image recognition technology

Wang Yi, Cui Sitian, Cao Yu, Cheng Xu

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 1271818 (2023) https://doi.org/10.1117/12.2681700
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

In real life, whether it is in the fields of weather forecast at airports, traffic control, weather services at ports, or industries such as agriculture, aquaculture, and transportation, all need to know the real situation of the weather. If it cannot be accurately identified and judged in time, will lead to threats to human life and property safety. In order to reduce the impact of weather on people's production and life in various industries and improve the accuracy of weather recognition, this paper establishes an improved convolutional neural network model based on the AdaBoost algorithm to identify three types of weather: rainy, snowy, and foggy. First, the convolutional neural network is trained and iterated many times, and then each convolutional neural network is used as a weak classifier, and multiple weak classifiers are weighted and combined based on the AdaBoost algorithm to form the final strong classifier model. Experiments show that the strong classifier optimized by the AdaBoost algorithm has a stronger ability to identify misclassified data and can realize dynamic reinforcement learning of data.

Citation Download Citation

Wang Yi, Cui Sitian, Cao Yu, and Cheng Xu "Meteorological forecast based on image recognition technology", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 1271818 (1 June 2023); https://doi.org/10.1117/12.2681700

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