On parameter estimation of control chart patterns using RBF neural network

Author

Yang, Miin-Shen ; Yang, Jenn-Hwai

Author_Institution

Dept. of Appl. Math., Chung Yuan Christian Univ., Chungli

fYear

2009

fDate

25-27 May 2009

Firstpage

1498

Lastpage

1502

Abstract

Although pattern recognition techniques have been widely applied to identify abnormal patterns in control charts, abnormal parameter value is difficult to be estimated. A pattern recognition system should better have capability to estimate abnormal parameter. In this paper, we present radial basis function (RBF) neural networks for parameter estimation of abnormal control chart patterns. This created control chart pattern recognition system presents good abilities for the estimation of abnormal parameter. We use several examples to demonstrate its usefulness and effectiveness.

Keywords

control charts; neurocontrollers; parameter estimation; pattern recognition; radial basis function networks; RBF neural network; control chart patterns; parameter estimation; pattern recognition techniques; radial basis function; Control charts; Electronic mail; Industrial control; Mathematics; Neural networks; Parameter estimation; Pattern recognition; Process control; Prototypes; Radial basis function networks; RBF; control chart; neural network; parameter estimation; pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-2799-4

Electronic_ISBN

978-1-4244-2800-7

Type

conf

DOI

10.1109/ICIEA.2009.5138444

Filename

5138444