A machine learning algorithm for expert system based on subjective Bayesian method

Author

WenBin, Chen ; XiaoLing, Liu ; Yijun, Liu ; Yu, Fang

Author_Institution

Sch. of Comput. Sci., Southwest Pet. Univ., Chengdu, China

Volume

2

fYear

2010

fDate

16-18 April 2010

Abstract

Based on subjective Bayesian method, knowledge representation model and inference method were analyzed, and the formula for certainty in reasoning process was given, and what lead to the inaccurate sufficient factor and necessary factor were discussed, and a correction algorithm to adjust the sufficient factor and the necessary factor to the true one based on case studies was given in this paper. Experiments proved that even the sufficient factor and necessary factor were inaccurate at the beginning, by using the correction algorithm, the sufficient factor and necessary factor could converge at actual values after adequate number of case studies.

Keywords

Bayes methods; expert systems; inference mechanisms; knowledge representation; learning (artificial intelligence); correction algorithm; expert system; inference method; knowledge representation model; machine learning; necessary factor; reasoning process; subjective Bayesian method; sufficient factor; Algorithm design and analysis; Bayesian methods; Computer science; Expert systems; Inference algorithms; Knowledge representation; Machine learning algorithms; Petroleum; Probability; Uncertainty; expert system; machine learning; necessary factor; subjective Bayesian method; sufficient factor;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology (ICCET), 2010 2nd International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6347-3

Type

conf

DOI

10.1109/ICCET.2010.5485423

Filename

5485423