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Generating consistent fuzzy belief rule base from sample data

Jun Liu, Luis Martínez, Da Ruan UGent and Hui Wang (2010) World Scientific Proceedings Series on Computer Engineering and Information Science. In World Scientific Proceedings Series on Computer Engineering and Information Science 2. p.167-172
abstract
A fuzzy rule-based evidential reasoning approach and it corresponding optimization algorithm have been proposed recently, where a fuzzy rule-base with a belief structure, called a fuzzy belief rule base (FBRB), forms a basis in the inference mechanism. In this paper, a new learning method for optimally generating a consistent FBRB based on the given data is proposed. The main focus is given on the consistency of FBRB knowing that the consistency conditions are often violated if the system is generated from real world data. The measurement of inconsistency of FBRB is provided and finally is incorporated in the objective function of the optimization algorithm. This process is formulated as a nonlinear constraint optimization problem and solved using the optimization tool provided in MATLAB. A numerical example is provided to demonstrate the effectiveness of the proposed algorithm.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
SETS, SYSTEMS, METHODOLOGY, INFERENCE
in
World Scientific Proceedings Series on Computer Engineering and Information Science
editor
Koen Vanhoof, Da Ruan UGent, Tianrui Li and Geert Wets
series title
World Scientific Proceedings Series on Computer Engineering and Information Science
volume
2
issue title
Intelligent decision making systems
pages
167 - 172
publisher
World Scientific and Engineering Academy and Society
place of publication
Athens, Greece
conference name
4th International conference on Intelligent Systems and Knowledge Engineering (ISKE 2009)
conference location
Hasselt, Belgium
conference start
2009-11-27
conference end
2009-11-28
Web of Science type
Proceedings Paper
Web of Science id
000277046000026
ISBN
9789814295055
DOI
10.1142/9789814295062_0026
language
English
UGent publication?
no
classification
P1
id
2918707
handle
http://hdl.handle.net/1854/LU-2918707
date created
2012-06-25 15:04:52
date last changed
2017-01-02 09:53:24
@inproceedings{2918707,
  abstract     = {A fuzzy rule-based evidential reasoning approach and it corresponding optimization algorithm have been proposed recently, where a fuzzy rule-base with a belief structure, called a fuzzy belief rule base (FBRB), forms a basis in the inference mechanism. In this paper, a new learning method for optimally generating a consistent FBRB based on the given data is proposed. The main focus is given on the consistency of FBRB knowing that the consistency conditions are often violated if the system is generated from real world data. The measurement of inconsistency of FBRB is provided and finally is incorporated in the objective function of the optimization algorithm. This process is formulated as a nonlinear constraint optimization problem and solved using the optimization tool provided in MATLAB. A numerical example is provided to demonstrate the effectiveness of the proposed algorithm.},
  author       = {Liu, Jun and Mart{\'i}nez, Luis and Ruan, Da and Wang, Hui},
  booktitle    = {World Scientific Proceedings Series on Computer Engineering and Information Science},
  editor       = {Vanhoof, Koen and Ruan, Da and Li, Tianrui and Wets, Geert},
  isbn         = {9789814295055},
  keyword      = {SETS,SYSTEMS,METHODOLOGY,INFERENCE},
  language     = {eng},
  location     = {Hasselt, Belgium},
  pages        = {167--172},
  publisher    = {World Scientific and Engineering Academy and Society},
  title        = {Generating consistent fuzzy belief rule base from sample data},
  url          = {http://dx.doi.org/10.1142/9789814295062\_0026},
  volume       = {2},
  year         = {2010},
}

Chicago
Liu, Jun, Luis Martínez, Da Ruan, and Hui Wang. 2010. “Generating Consistent Fuzzy Belief Rule Base from Sample Data.” In World Scientific Proceedings Series on Computer Engineering and Information Science, ed. Koen Vanhoof, Da Ruan, Tianrui Li, and Geert Wets, 2:167–172. Athens, Greece: World Scientific and Engineering Academy and Society.
APA
Liu, Jun, Martínez, L., Ruan, D., & Wang, H. (2010). Generating consistent fuzzy belief rule base from sample data. In K. Vanhoof, D. Ruan, T. Li, & G. Wets (Eds.), World Scientific Proceedings Series on Computer Engineering and Information Science (Vol. 2, pp. 167–172). Presented at the 4th International conference on Intelligent Systems and Knowledge Engineering (ISKE 2009), Athens, Greece: World Scientific and Engineering Academy and Society.
Vancouver
1.
Liu J, Martínez L, Ruan D, Wang H. Generating consistent fuzzy belief rule base from sample data. In: Vanhoof K, Ruan D, Li T, Wets G, editors. World Scientific Proceedings Series on Computer Engineering and Information Science. Athens, Greece: World Scientific and Engineering Academy and Society; 2010. p. 167–72.
MLA
Liu, Jun, Luis Martínez, Da Ruan, et al. “Generating Consistent Fuzzy Belief Rule Base from Sample Data.” World Scientific Proceedings Series on Computer Engineering and Information Science. Ed. Koen Vanhoof et al. Vol. 2. Athens, Greece: World Scientific and Engineering Academy and Society, 2010. 167–172. Print.