Predicting K/S Value of the Reactive Dyes Based on RBF Neural Network

Author

Jiang, HuiYu ; Dong, Min ; Li, Wei

Author_Institution

Inst. of Chem. & Eng., Wuhan Univ. of Sci. & Eng., Wuhan, China

Volume

1

fYear

2009

fDate

18-19 July 2009

Firstpage

91

Lastpage

93

Abstract

The traditional determination method of K/S value is testing the CIEL*a*b* value of each dyeing fabric fistly by the color chromatic aberration SC-80, and then, based on the CIEL*a*b* value, they calculate the K/S value scoping 10 nm within 400 nm-700 nm the visible region. These are finished with the help of the software Hyper Choshoku-Senka TX.The RBF neural network is used in this paper to estimate the K/S value. The correlation coefficient reaches 1.000 between the estimated value and tested one. Prediction error´s biggest absolute value is 0.004, the rest is under 0.002. It shows the feasibility of the artificial neural network applied to the reactive dyes dyeing. It is a good forecast mode of K/S value of the reactive dyes.

Keywords

aberrations; chemical engineering computing; dyes; radial basis function networks; CIEL*a*b* value; K/S value; RBF neural network; SC-80; artificial neural network; color chromatic aberration; correlation coefficient; dyeing fabric; prediction error; reactive dyes; software hyper Choshoku-Senka TX; Artificial neural networks; Chemical engineering; Chemical processes; Educational institutions; Fabrics; Information processing; Network topology; Neural networks; Radial basis function networks; Testing; K/S value; RBF neural network; predicting; reactive dyes;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on

Conference_Location

Shenzhen

Print_ISBN

978-0-7695-3699-6

Type

conf

DOI

10.1109/APCIP.2009.31

Filename

5197003