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Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization

Geoscience Frontiers 2021年第5期12卷 355-373页

作者： Xinzhi Zhou Haijia Wen Yalan Zhang Jiahui Xu Wengang Zhang School of Civil Engineering Chongqing UniversityChongqing 400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing 400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Ministry of EducationChongqing UniversityChongqing 400045China Key Laboratory of GIS Application Research Chongqing Normal UniversityChongqing 401331China

The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility *** this,a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points,which was randomly divided into two datasets for model training(70%)and model testing(30%).22 factors were initially selected to establish a landslide factor *** applied the GeoDetector and recursive feature elimination method(RFE)to address factor optimization to reduce information redundancy and collinearity in the ***,the frequency ratio method,multicollinearity test,and interactive detector were used to analyze and evaluate the optimized ***,the random forest(RF)model was used to create a landslide susceptibility map with original and optimized *** resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve(AUC)and *** accuracy of the two hybrid models(0.868 for GeoDetector-RF and 0.869 for RFE-RF)were higher than that of the RF model(0.860),indicating that the hybrid models with factor optimization have high reliability and *** RFE-RF GeoDetector-RF had higher AUC values,respectively 0.863 and 0.860,than RF(0.853).These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.

关键词： Landslide susceptibility mapping GeoDetector Recursive feature elimination Random forest factor optimization

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New Developments in Structural Health Monitoring Based on Diagnostic Lamb Wave

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Journal of Materials Science & Technology 2004年第5期20卷 490-496页

作者： Shenfang YUAN, Yingdi XU and Ge PENGThe Smart Materials & Structures Aeronautic Key Laboratory, Nanjing University of Aeronautic and Astronautic, Nanjing 210016, China Smart Mat. and Structures Aero. Lab. Nanjing Univ. of Aero. and Astron. Nanjing 210016 China

Structure health monitoring based on diagnostic Lamb waves has been found to be one of the most promising techniques recently. This paper has a brief review of the new developments on this method including the basic novel of the method, fundamentals and mathematics of Lamb wave propagation, narrowband and wideband Lamb wave excitation methods, optimization of excitation factors and diagnostic Lamb wave interpretation methods.

关键词： Structural health monitoring Lamb wave methods factor optimization Damage localization

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