摘要
为了提高水资源承载力评价的效率和准确性,提出了一种基于主成分分析(PCA)、遗传算法(GA)和极限梯度提升树(XGBoost)的指标评价模型。定义了以水资源、社会经济、生态环境为子系统的14项评价指标;采用主成分分析法对评价指标进行降维处理;基于梯度提升决策树对吉林省2011—2021年的水资源承载力进行评价分析,并利用遗传算法对极限梯度提升树中4个参数进行优化。结果表明:经主成分分析简化评价指标后,PCA-GA-XGBoost模型的相关系数等指标均优于GA-BP、GA-SVM、GA-XGBoost和XGBoost;2011—2021年吉林省水资源承载力位于0.192~0.724,为先上升后下降再上升趋势,承载力状况逐年改善;利用模型内置的特征值重要度排序功能,识别得出重要度最大的指标为每公顷化肥施用量(0.5307),是影响吉林省水资源承载力的关键因素。
To improve the efficiency and accuracy of carrying capacity evaluation in water resources,this paper proposes an indicator evaluation model based on principal component analysis(PCA),genetic algorithm(GA),and eXtreme gradient boosting tree(XGBoost).Meanwhile,fourteen evaluation indicators are defined with water resources,socio-economics,and ecological environment employed as subsystems.PCA is adopted to reduce the dimensionality of the evaluation indicators.Additionally,based on XGBoost,this paper conducts an evaluation analysis on the carrying capacity of water resources from 2011 to 2021 and utilizes GA to optimize four parameters in XGBoost.The results show that after simplifying the evaluation indicators by PCA,the correlation coefficient of the PCA-GA-XGBoost model is better than GA-B,GA-SVM,GA-XGBoost,and XGBoost.The carrying capacity of water resources in Jilin Province from 2011 to 2021 is between 0.192 and 0.724,presenting a trend of first increasing,then decreasing,and finally increasing with improved carrying capacity situation.Meanwhile,the built-in function of eigenvalue importance ranking in the model is leveraged to conclude the fact that the indicator with the largest importance is identified as the applied fertilizer amount per hectare(0.5307).
作者
庞博文
李治军
PANG Bowen;LI Zhijun(College of Hydraulic and Electrical Engineering,Heilongjiang University,Harbin 150080,China;Institute of Cold Groundwater Research,Heilongjiang University,Harbin 150050,China)
出处
《人民珠江》
2024年第4期98-106,共9页
Pearl River
基金
国家科技支撑计划项目(2014BAD12B01-03)。
关键词
主成分分析
遗传算法
极限梯度提升树
水资源承载力
吉林省
principal component analysis
genetic algorithm
extreme gradient boosting tree
carrying capacity of water resources
Jilin Province
