基于案例推理的黄河流域水资源优化调配  

Case-based reasoning for water resource optimal allocation in the Yellow River Basin

作　　者：彭少明[1,2] 张春生[1] 

机构地区：[1]黄河勘测规划设计有限公司,河南郑州450003 [2]中国水利水电科学研究院水资源研究所,北京100044

出　　处：《水利水电科技进展》2012年第2期46-49,94,共5页Advances in Science and Technology of Water Resources

基　　金：国家"十一五"科技支撑计划(2006BAB06B06);国家自然科学基金(50479024)

摘　　要：利用水文要素的周期性、重现性、相似性等特征,将嵌套案例推理技术引入到黄河流域水资源调配方案决策中,建立K-D树定性搜索与相似度精确定位相结合的基于案例推理的黄河流域水资源调配决策模型。对黄河流域水资源调配中的水文要素进行定性识别,以关键水文要素的相似度作为检索指标,通过K-D树结构实现快速搜索定位与水文要素的相似性匹配,可搜索出与决策问题高度相似的方案,实现水资源的优化调配。Using the characteristics of periodicity,repeatability and comparability of hydrology element,the method of case-based reasoning is introduced into the water resource allocation,and a model for water resource allocation decision in the Yellow River Basin is established based on case-based reasoning,combined K-D tree qualitative searching technology with analogical degree pinpoint technology.Taking the water resource allocation in the Yellow River Basin as an example,the hydrology elements are identified qualitatively and the analogical degree is regarded as a searching index,then the highly analogical case is searched out based on comparability matching of hydrology elements through K-D tree structure.

关 键 词：水资源调配 案例推理 相似度 K-D树检索 黄河流域 

分 类 号：TV213.4[水利工程—水文学及水资源]