A Multi-factor Correlation Analysis Method for Typhoon Moving Track Based on NMI and HSIC0

doi:10.12068/j.issn.1005-3026.2023.09.003

Abstract

Abstract: The existing nonlinear correlation analysis methods have low accuracy and high computational cost， making them unsuitable for the correlation analysis of large-scale and high-dimensional typhoon track data.To solve this problem，the Hilbert-Schmidt independent criterion empirical estimation (HSIC0) is introduced into typhoon track correlation study for the first time， and a multi-factor correlation analysis method based on normalized mutual information (NMI) and HSIC0 is proposed. The method first uses NMI to filter out redundant factors with low correlation in typhoon data， and then uses XGBoost to eliminate invalid factors， thus reducing the subsequent computational costs.On this basis， a multi-factor correlation analysis method based on HSIC0 is used to analyze typhoon data， and a combination of factors affecting typhoon moving track with strong correlation is mined， thereby improving the prediction accuracy of typhoon moving track.A series of experimental results on real typhoon data sets show that the proposed method outperforms the correlation analysis methods such as NMI， Pearson correlation coefficient， and distance correlation coefficient in indicators such as MSE， MAE， R^○2.

Key words: typhoon moving track; correlation analysis; multi-factor; HSIC0; XGBoost

CLC Number:

TP301
P444

QIAO Bai-you， HAO Yuan-qing， TANG Zhong， WANG Rui. A Multi-factor Correlation Analysis Method for Typhoon Moving Track Based on NMI and HSIC0[J]. Journal of Northeastern University(Natural Science), 2023, 44(9): 1234-1244.

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