Title :
Error separation base on small sample Bayesian network
Author :
Hui Fan ; Liwen Yan ; Peng Qiao ; Liu Han
Author_Institution :
Tianjin Key Lab. of High Speed Cutting & Precision Machining, Tianjin Univ. of Technol. & Educ., Tianjin, China
Abstract :
Bayesian network (BN) method using in error separation is the hot issue of the current research. BN is a powerful tool for uncertainty reasoning and knowledge representation. When we use it combining with the statistical method, it shows a lot the advantage of data processing. This paper considers the many factors in measuring dynamic errors and of the complicated relationship, and brings the small sample BN into the measuring dynamic error separation. In view of the measurement error, we build the basic dependent relationships among variables and the basic construction among nodes and so on. Finally, we use simulation for experiment and analysis through the study of small sample BN.
Keywords :
Bayes methods; computerised instrumentation; error statistics; knowledge representation; measurement errors; statistical analysis; uncertainty handling; Bayesian network; data processing; error separation base; knowledge representation; measurement error; statistical method; uncertainty reasoning; Bayesian methods; Computer numerical control; Data models; Machine tools; Measurement uncertainty; Probability distribution; Bayesian network (BN); error separation; small sample;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6009925