摘要
分析了目前复杂大系统建模方法存在的优缺点,旨在研究一种适用于我国行政递阶管理机制的建模方法。这种方法能够很好地解决系统问题中的不确定性,尤其是人为主观造成的模糊性与采样数据随机性并存的问题。鉴于以上研究目标,探讨了多层状态空间模型,并引用图论诠释了其横向关系模型,同时融合正态云发生器的原理提出了一种"分解-集结"式的不确定性智能建模方法———多层云建模方法。最后将该方法用于我国能源系统分析研究中,取得了较好的结果,证明了该方法的简单性和有效性。
The paper studied many complex large system modeling method,and analysed their advantages and disadvantages.Furtherly,its research purposes were put forward,and it is a new complex large system modeling method suitable for China＇s administrative hierarchy mechanism,and is able to effectively solve uncertainty of system information,especially coexistence of fuzziness and randomness.According to the research target,the paper discussed multi-layer state space model,described specification of its latitude model,and combined with the principle of the normal cloud generator,proposesd a ＂decomposition-collection＂ type of uncertainty intelligence modeling method：multi-layer cloud modeling method.Finally,it was used to analyse China＇s energy system,and got a active result,which shows the method is simple and effective.
出处
《计算机科学》
CSCD
北大核心
2012年第1期162-166,共5页
Computer Science
基金
"十一.五"国家科技支撑计划重点项目(2006BAJ04B07-2)
863国家高技术研究发展计划项目基金(2009AA012119)资助
关键词
多层状态空间模型
云模型
不确定性
复杂大系统
Multi-layer state space model
Cloud model
Uncertainty
Complex large system
