Robotics & Machine Learning Daily News2024,Issue(Dec.5) :41-42.

Study Findings on Machine Learning Discussed by Researchers at Southwest Jiaoton g University (Co-seismic landslide susceptibility mapping for the Luding earthqu ake area based on heterogeneous ensemble machine learning models)

西南交东大学研究人员讨论的机器学习研究成果(基于异构集成机器学习模型的泸定地震曲地区滑坡易感性同震绘图)

Robotics & Machine Learning Daily News2024,Issue(Dec.5) :41-42.

Study Findings on Machine Learning Discussed by Researchers at Southwest Jiaoton g University (Co-seismic landslide susceptibility mapping for the Luding earthqu ake area based on heterogeneous ensemble machine learning models)

西南交东大学研究人员讨论的机器学习研究成果(基于异构集成机器学习模型的泸定地震曲地区滑坡易感性同震绘图)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑新闻-关于人工智能的详细数据已经呈现。根据新闻报道来自中国人民日报成都的研究报告,由NewsRx记者报道,“考虑到”滑坡易感性图(LSM)在市级尺度上的多解性,对滑坡易感性图的编制有一定的指导意义假设空间的单机学习(ML)算法充分准确地反映了算法的内在在所有情况下,滑坡影响因素与实际灾难性事件之间的相关性。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Data detailed on artificial intelligence have bee n presented. According to news reporting originatingfrom Chengdu, People’s Repu blic of China, by NewsRx correspondents, research stated, “Consideringthe compl exity of landslide susceptibility mapping (LSM) at the municipal-scale, it is di fficult for theassumption space of a single machine learning (ML) algorithm to fully and accurately reflect the intrinsiccorrelation between the landslide inf luencing factors and the actual catastrophic events under all scenarios.”

Key words

Southwest Jiaotong University/Chengdu/People’s Republic of China/Asia/Algorithms/Cyborgs/Emerging Technologies/Ma chine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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