Robotics & Machine Learning Daily News2024,Issue(Jan.12) :45-46.

Reports Outline Machine Learning Study Results from Chongqing University (Insights Into Landslide Susceptibility In Different Karst Erosion Landforms Based On Interpretable Machine Learning)

Robotics & Machine Learning Daily News2024,Issue(Jan.12) :45-46.

Reports Outline Machine Learning Study Results from Chongqing University (Insights Into Landslide Susceptibility In Different Karst Erosion Landforms Based On Interpretable Machine Learning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reporting fromChongqing, People’s Republic of China, by NewsRx journalists, research stated, “The aim of the presentstudy was to assess differences in the conditioning factors and the performance of landslide susceptibilitymapping (LSM), employing the SHapley Additive exPlanations (SHAP) model to gain profound insightsinto the intrinsic decision-making mechanism of LSM in diverse landforms. Two typical karst erosionlandforms were selected as the research areas.”

Key words

Chongqing/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Chongqing University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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