改进的大坝安全监控粗集推理预报模型  

Improved Rough Set Reasoning forecast model for Dam Safety Monitoring

作　　者：王甜[1,2,3] 包腾飞[1,2,3] 徐波 刘飞[1] 卢远富 

机构地区：[1]河海大学水利水电学院,江苏南京210098 [2]河海大学水文水资源与水利工程科学国家重点实验室,江苏南京210098 [3]河海大学水资源高效利用与工程安全国家工程研究中心,江苏南京210098 [4]扬州大学水利与能源动力工程学院,江苏扬州225127

出　　处：《人民黄河》2017年第2期139-142,共4页Yellow River

基　　金：国家自然科学基金资助项目(51379068;51139001);国家自然科学基金青年基金资助项目(51409227);江苏省杰出青年基金资助项目(BK20140039);高等学校博士学科点专项科研基金资助项目(20120094110005;20120094130003)

摘　　要：针对已有粗集推理预报模型的不足,提出了一种改进的大坝安全监控粗集推理预报模型。该预报模型通过粗集论约简影响因素,并且结合贝叶斯定理对规则的约简引入一致度和支持度。实际算例证明,改进后的粗集推理预报模型可以用于大坝效应量的预报,与一般粗集推理模型相比,其在一定程度上消除了噪声数据对预报的影响,提高了预报的精度,在样本基数大的情况下预报较准,可信度较高。Due to the defects of the original rough set reasoning forecast model,the authors proposed a forecast model using an improved rough set reasoning method for dam safety monitoring. The influence factors can be reduced based on the rough set theory in this model.Meanwhile,the authors induce the concept of the consistency ratio and support ratio based on the Bayes' theorem to the reduction of the rules.It can be proved that the improved rough set reasoning forecast model can be used in the forecast of dam's effect-quantity,and that comparing to the ordinary rough set reasoning model,the improved model reduces the influence of data noise to some extent,improves the accuracy of the forecast,and has a better credibility when the sample base is large enough.

关 键 词：大坝安全监测 粗集理论 贝叶斯定理 一致度 支持度 

分 类 号：TV698.1[水利工程—水利水电工程]