基于机器学习算法的区域地质环境承载力评价方法研究

随着国家对生态文明建设重视程度不断提高,人们对所住区域的地质环境承载能力越来越关心,也对地质环境承载力评价的方法提出了新的要求。本文引入机器学习方法 ,以地质环境承载力的评价理论为基础,提出了基于机器学习算法的地质环境承载力评价方法。通过梳理国内外地质环境评价相关成果,分析地质环境的各种评价要素,提炼出影响地质环境承载力的主控因素,在此基础上建立适合于机器学习的地质环境承载力评价指标体系,再结合机器学习方法,构建基于机器学习算法的地质环境承载力评价模型,对区域地质环境承载力进行评价,并以眉山市彭山区为例,进行承载力评价,为其他区域的地质环境承载力评价提供应用示范和评价方法。

Study on evaluation method of geological environment carrying capacity based on machine learning algorithm

With the increasing attention paid by the state to the construction of ecological civilization, people have been paying more attention to the bearing capacity of the geological environment in the area they live in, and new requirements have been put forward for the evaluation methods of bearing capacity of geological environment. This paper introduces machine learning method, and based on the evaluation theory of geological environment bearing capacity, puts forward the evaluation method of geological environment bearing capacity based on machine learning algorithm. By analyzing geological environment evaluation at home and abroad related results, analyzing various evaluation factors of geological environment and refining the main controlling factors that affect the bearing capacity of geological environment, based on this, the evaluation index system of the bearing capacity of geological environment suitable for machine learning is established , and combined with machine learning methods, build the bearing capacity of geological environment evaluation model based on machine learning algorithms, evaluate the regional geological environmental bearing capacity, Taking Pengshan district of Meishan city as an example, carrying capacity evaluation is carried out, which provides a demonstration and evaluation method for the evaluation of the bearing capacity of the geological environment in other regions.