自动化学报2012，Vol.38Issue(4)：666-672,7.DOI:10.3724/SP.J.1004.2012.00666
一种信度马尔科夫模型及应用
A Belief Markov Model and Its Application
摘要
Abstract
Markov chain is widely applied to the fields of natural science and engineering technology with its non-aftereffect property. However, the classical Markov chain is unable to handle the uncertainty of state description. Besides, the state's transition is unstable when the divide boundary of states is too clear. In order to overcome these limitations, a belief Markov model is proposed in this paper. Dempster-Shafer (DS) theory of evidence is introduced to new model to represent the uncertainty of states. Firstly, the states are reduced to form a frame of discernment, and a basic probability assignment function is established. Then, as an intermediate result, a matrix of propositions! Transition probability is calculated. Finally, the future state can be obtained according to the current state. The proposed belief Markov model is a generalization of classical Markov chain and downward compatible with its properties. A case study shows that the limitations above mentioned are overcame and the proposed model is more effective and practicable.关键词
马尔科夫链/Dempster-Shafer证据理论/预测/转移概率Key words
Markov chain, Dempster-Shafer (DS) theory of evidence, forecasting, transition probability引用本文复制引用
邓鑫洋,邓勇,章雅娟,刘琪..一种信度马尔科夫模型及应用[J].自动化学报,2012,38(4):666-672,7.基金项目
国家自然科学基金(60874105,61174022),教育部新世纪优秀人才支持计划(NCET-08-0345),上海市青年科技启明星计划(09QA1402900),重庆市自然科学基金(CSCT,2010BA2003),航空科学基金(20090557004),上海交通大学“晨星学者计划”(T241460612)资助 （60874105,61174022）
