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作 者:邓乐乐 郭生练[1] 王俊[1] 向鑫 DENG Lele;GUO Shenglian;WANG Jun;XIANG Xin(State Key Laboratory of Water Resources Engineering and Management,Wuhan University,Wuhan 430072,China)
机构地区:[1]武汉大学水资源工程与调度全国重点实验室,湖北武汉430072
出 处:《水资源保护》2025年第2期200-208,共9页Water Resources Protection
基 金:国家自然科学基金项目(U20A20317)。
摘 要:针对现有水资源承载力评价方法单一赋权和主观选择不确定性的局限,构建了水资源承载力综合评价指标体系,考虑到水资源承载力评价的不确定性,采用博弈论融合单一赋权法生成指标权重,基于灰色关联-TOPSIS法获取贴近度,并对云模型进行优化,提出了基于博弈论-云模型的评价方法,综合评价了湖北省汉江中下游地区8市2010—2020年水资源承载力时空变化。结果表明:水资源承载力水平上游高于下游,具有较强的聚集特征,空间分异性明显;2011年水资源承载力水平最低,2020年最高,总体呈波动上升趋势;各市水资源承载力水平以中等为主,部分年份达警戒水平。To address the limitations of conventional individual weighting methods and subjective selection uncertainties in water resources carrying capacity assessment,a comprehensive evaluation indicator system was established.In consideration of the inherent uncertainties in water resources carrying capacity evaluation,an innovative methodology integrating game theory was developed to optimize individual weighting methods for indicator weighting determination.The improved grey correlation-TOPSIS method was employed to calculate closeness degree,coupled with an enhanced cloud model algorithm.This proposed game theory-cloud model hybrid approach was applied to assess the spatiotemporal evolution of water resources carrying capacity in eight cities within the middle-lower reaches of the Hanjiang River in Hubei Province from 2010 to 2020.The results indicate that the water resources carrying capacity was higher in the upstream areas compared to the downstream areas,exhibiting strong clustering characteristics and significant spatial heterogeneity.The water resources carrying capacity was at its lowest level in 2011 and reached its highest level in 2020,showing an overall fluctuating upward trend.The water resources carrying capacity of each city was primarily at a moderate level,with occasional alert-level occurring in specific years.
关 键 词:水资源承载力 博弈论 云模型 汉江中下游 湖北省
分 类 号:X143[环境科学与工程—环境科学]
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