摘要
针对传统分析方法的不足,研究了大坝安全监测的粗集模型方法.首先对原始监测信息进行粗糙集处理,提取主要影响因素和决策规则集,然后用粗糙隶属度分析各主要因素的重要性指标及其在效应量中所占的分量比例,并且通过对规则集的不确定性推理建立了大坝监测的粗集预报模型.实例分析表明,粗集模型在大坝影响因素重要性评价和非确定性测值预报方面取得了满意的结果.
The rough set model used in dam safety monitoring was studied aiming at the deficiency of conventional methods such statistical model , neural networks and genetic algorithms method etc.. Firstly, the main factors and decision rules were extracted from monitoring data. Then, the main factors' importance value and their percentage in effect quantity were computed based on rough membership. And then, rough prediction model were upbuilt through reasoning under uncertainty. A case in seepage analysis was illustrated that the rough set model is successful in estimation of factors' effect and rough prediction under uncertainty.
出处
《武汉大学学报（工学版）》
CAS
CSCD
北大核心
2005年第3期45-49,共5页
Engineering Journal of Wuhan University
基金
国家自然科学基金重点资助项目(编号:50139030).
关键词
大坝安全监测
粗糙理论
粗糙隶属度
决策规则
不确定性推理
预报模型
dam safety monitoring
rough set
rough membership
decision rules
reasoning under uncertainty
prediction model
