The Short-term Forecasting Model of Sandstorms Based on SMOTE and Decision Tree Learning Algorithm
ZHANG Zhenhua
XU Jinhui
LI Longxin
MA Chao
HUANG Jiangnan
XIE Zhenghong
Abstract：As the traditional algorithms are defective in forecasting the accuracy of sandstorm disaster , this paper established a forecasting model combined SMOTE algorithm with decision tree learning algo‐rithm .Using meteorological observation data of six provinces in Northwest China ,the classification of rare class is well solved ,and the predictive accuracy rate reaches 76 .25% .The results showed that the model can be used for the actual sandstorm warning with good classification accuracy ,generalization performance , robustness and anti‐noise properties in solving the classification problems of the unbalanced samples in the sandstorm forecasting .
Keywords：sandstorms forecastingrare classesSMOTEdecision tree learning algorithm
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 40-46 )