机器学习方法用于识别影响伊朗中部Gavkhouni盆地粉尘敏感性的因素

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Z. Ebrahimi-Khusfi, A. R. Nafarzadegan, M. Ebrahimi-Khusfi, A. H. Mosavai
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引用次数: 0

摘要

利用三种特征选择算法和感知神经网络模型,研究了影响伊朗中部地区Gavkhouni盆地粉尘易感性的关键因素。采用精度评估统计量对模型的预测能力进行评价。气溶胶光学深度数据集利用排列特征重要性方法对控制沙尘事件的因素进行优先排序,验证了产生沙尘的区域图。使用遗传算法选择的变量,解释系数比relief算法提高31%,比ElasticNet算法提高19%。遗传算法在识别变量方面被证明是有效的,在高风险区域显著提高了模型的准确性(precision = 0.75, recall = 0.71, F1 = 0.73)。研究发现,地形多样性、地质、土壤含沙量、降水、风速、土壤盐度、土壤沉降、植被覆盖、坡度和土壤湿度是关键环境因素。这些发现对于制定改善空气质量和限制与粉尘有关的影响的具体措施非常重要,这是脆弱生态系统可持续管理的关键因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning approaches for identifying factors influencing dust sensitivity in the Gavkhouni Basin, Central Iran

This study identifies key factors affecting dust susceptibility in Gavkhouni Basin, central Iran, using three feature selection algorithms and a perceptual neural network model. Accuracy assessment statistics were used to evaluate the prediction capabilities of the models. The aerosol optical depth dataset validated the dust-generating area map, with the permutation feature importance method prioritizing factors controlling dust events. Using the variables selected by the genetic algorithm improved the coefficient of explanation by 31% compared to relief, and 19% compared to ElasticNet algorithm. The genetic algorithm proved effective in identifying variables that significantly enhanced model accuracy in high-risk zones (precision = 0.75, recall = 0.71, and F1 = 0.73). The study found that topographic diversity, geology, soil sand content, precipitation, wind speed, soil salinity, soil subsidence, vegetation cover, slope, and soil moisture were key environmental factors. These findings are very important for the formulation of specific measures for improving air quality and limiting dust-related effects as a key factor in the sustainable management of vulnerable ecosystems.

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来源期刊
CiteScore
5.60
自引率
6.50%
发文量
806
审稿时长
10.8 months
期刊介绍: International Journal of Environmental Science and Technology (IJEST) is an international scholarly refereed research journal which aims to promote the theory and practice of environmental science and technology, innovation, engineering and management. A broad outline of the journal''s scope includes: peer reviewed original research articles, case and technical reports, reviews and analyses papers, short communications and notes to the editor, in interdisciplinary information on the practice and status of research in environmental science and technology, both natural and man made. The main aspects of research areas include, but are not exclusive to; environmental chemistry and biology, environments pollution control and abatement technology, transport and fate of pollutants in the environment, concentrations and dispersion of wastes in air, water, and soil, point and non-point sources pollution, heavy metals and organic compounds in the environment, atmospheric pollutants and trace gases, solid and hazardous waste management; soil biodegradation and bioremediation of contaminated sites; environmental impact assessment, industrial ecology, ecological and human risk assessment; improved energy management and auditing efficiency and environmental standards and criteria.
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