DocumentCode :
3418413
Title :
A Temporal Bayesian Network based on uncertain time interval
Author :
Wang, Jian ; Tu, Chuanfei ; Wang, Hongwei
Author_Institution :
Inst. of Syst. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2011
fDate :
19-21 Oct. 2011
Firstpage :
605
Lastpage :
611
Abstract :
In the real world, the start time and the end time of many events have uncertainty and can not be accurately represented as time interval. In order to express the uncertainty of time interval uncertainty and its state, the traditional time interval is transformed into an uncertain time interval, and a Temporal Bayesian Network based on uncertain time interval is proposed in this paper. Different from traditional Bayesian Network, such Temporal Bayesian Network takes precedence relationship into account besides causal relationship. The corresponding constructing procedure and reasoning algorithm are also given. Furthermore, the Temporal Bayesian Network based on uncertain time interval is applied to the risk analysis of dam overtopped. The results show that the proposed Temporal Bayesian Network has a better ability in expressing two kinds of uncertainty at the same time: the time interval uncertainty and the state uncertainty. It also demonstrates that the uncertainty of start time and end time has an obvious effect on the posterior probability which directly influences the decision-making.
Keywords :
belief networks; dams; geotechnical engineering; inference mechanisms; probability; risk analysis; structural engineering computing; causal relationship; dam; decision making; event end time; event start time; posterior probability; precedence relationship; reasoning algorithm; risk analysis; temporal Bayesian network; uncertain time interval; Bayesian methods; Cognition; Educational institutions; Random variables; Risk analysis; Simulation; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
Type :
conf
DOI :
10.1109/IWACI.2011.6160080
Filename :
6160080
Link To Document :
بازگشت