Application Research of Rainfall Prediction Based on Optimized Machine Learning Algorithm in Meteorological Data


Daoqing Gong, Cheng Yuan, Xinyan Gan, Xiang Gao, Guizhi Sun, Journal of Information Processing Systems Vol. 20, No. 6, pp. 718-730, Dec. 2024  

https://doi.org/10.3745/JIPS.04.0324
Keywords: Machine Learning, Data Mining, Optimization Model, meteorological data, Rainfall Forecast
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Abstract

In recent years, the rapid development of artificial intelligence technology has brought new opportunities to the meteorological field. Specifically, machine learning (ML) algorithms have proven valuable tools in rainfall retrievals, demonstrating the practicability of using ML algorithms when facing high-dimensional and complex data. By collecting data and using ML algorithms to mine and analyze the data, ML models can solve the problem of rainfall prediction in meteorology. Spurred by this advantage, this paper compared five ML algorithms for rainfall prediction using the National Population Health Science data from China, and the five ML algorithms were optimized appropriately. The data employed was first preprocessed to find and fill in the missing values, remove duplicate values, mine the correlation between data features, and generate visual results. Then, logistic regression, k-nearest neighbor algorithm, naive Bayes, decision tree algorithms, and random forest were used to mine and analyze the meteorological data for weather prediction. Finally, the performance of the models before and after optimization is compared to provide decision support for rainfall prediction.


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Cite this article
[APA Style]
Gong, D., Yuan, C., Gan, X., Gao, X., & Sun, G. (2024). Application Research of Rainfall Prediction Based on Optimized Machine Learning Algorithm in Meteorological Data. Journal of Information Processing Systems, 20(6), 718-730. DOI: 10.3745/JIPS.04.0324.

[IEEE Style]
D. Gong, C. Yuan, X. Gan, X. Gao, G. Sun, "Application Research of Rainfall Prediction Based on Optimized Machine Learning Algorithm in Meteorological Data," Journal of Information Processing Systems, vol. 20, no. 6, pp. 718-730, 2024. DOI: 10.3745/JIPS.04.0324.

[ACM Style]
Daoqing Gong, Cheng Yuan, Xinyan Gan, Xiang Gao, and Guizhi Sun. 2024. Application Research of Rainfall Prediction Based on Optimized Machine Learning Algorithm in Meteorological Data. Journal of Information Processing Systems, 20, 6, (2024), 718-730. DOI: 10.3745/JIPS.04.0324.