水力发电2025，Vol.51Issue(1)：5-10,6.
基于RF-TOPSIS-MCS的水库水质综合评价方法及应用
RF-TOPSIS-MCS-Based Comprehensive Evaluation Method for Reservoir Water Quality and Its Application
摘要
Abstract
In the management of reservoirs,accurate assessment of water quality is crucial.However,uncertainties in data collection and limitations in the allocation of weights to water quality factors can both impact the evaluation results.To address these issues,a novel method which integrates Random Forest(RF)classification prediction,Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),and Monte Carlo Simulation(MCS)is developed for comprehensive water quality evaluation using the Dahuofang Reservoir as a study case.Initially,a dataset with a normal distribution is generated using MCS based on the actual monthly average water quality data.Subsequently,the RF is utilized for weight assignment in the TOPSIS method and a membership function is employed for the comprehensive evaluation of water quality.The results of case study are consistent with the water quality grades provided in the monthly water environmental quality reports of Liaoning Province,indicating that the proposed approach can provide robust technical support for the water quality assessment of large reservoirs.关键词
随机森林赋权/优劣解距离法/蒙特卡罗模拟/水库水质评价Key words
random forest weighting/TOPSIS/Monte Carlo simulation/reservoir water quality assessment分类
环境科学引用本文复制引用
张冲,陈末..基于RF-TOPSIS-MCS的水库水质综合评价方法及应用[J].水力发电,2025,51(1):5-10,6.基金项目
黑龙江省普通本科高等学校青年创新人才培养计划(UNPYSCT-2020012) （UNPYSCT-2020012）
