Shaoguan University Researcher Has Published New Study Findings on Support Vector Machines (Comparative models of supportvector machine, multilayer perceptron, and decision tree predication approaches for landslide susceptibility analysis)

韶关大学研究员发表了支持向量机(滑坡易感性分析的支持向量机、多层感知器和决策树预测方法的比较模型)的最新研究成果

Robotics & Machine Learning Daily News2024，Issue(Jun.14) ：51-52.

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Shaoguan University Researcher Has Published New Study Findings on Support Vector Machines (Comparative models of supportvector machine, multilayer perceptron, and decision tree predication approaches for landslide susceptibility analysis)

韶关大学研究员发表了支持向量机(滑坡易感性分析的支持向量机、多层感知器和决策树预测方法的比较模型)的最新研究成果

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-新的研究是一篇新的报道的主题。根据NewsRx编辑对中华人民共和国广东的新闻报道，研究表明：“Naqadeh地区(NR)是伊朗西北部地质灾害发生最敏感的地区之一，研究区域确定的LAN DSlide触发参数分为海拔、坡向、坡角、岩性、排水密度、河流距离、风化、土地覆盖、降水、植被、断层距离。”DI站在道路上，以及到城市的距离。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on is the subject of a ne w report. According to news reporting out of Guangdong, People’s Republic of Chi na, by NewsRx editors, research stated, “Naqadeh Region (NR) is one of the most sensitive regions regarding geo-hazards occurrence in Northwest of Iran. The lan dslides triggering parameters that identified for the studied region are classif ied as elevation, aspect, slope angle, lithology, drainage density, distance to river, weathering, land-cover, precipitation, vegetation, distance to faults, di stance to roads, and distance to the cities.”

Key words

Shaoguan University/Guangdong/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Perceptron/S upport Vector Machines/Vector Machines

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出版年

2024

Robotics & Machine Learning Daily News

ISSN：

段落导航