Research on moisture content measurement based on improved BP arithmetic

Author

Jiang, Yu ; Ding, Xue-Mei ; Yang, Guo-hui

Author_Institution

Inst. of Ultra-Precision Opt. & Electron. Instrum. Eng., Harbin Inst. of Technol., China

Volume

8

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

4749

Abstract

How to reduce the measurement error caused by linear regression is the key in measuring tea moisture content with microwave transmission techniques. In this paper, an improved BP algorithm, which combines the genetic algorithm, is given for training artificial neural network to get the range of weights and thresholds. The method makes BP algorithm avoid getting into infinitesimal locally and has the merits of high prediction precision and rapid convergence. The results show that the mean squared error is 0.0116, the mean absolute error is 0.0738, the mean relative error is 0.1182 and the certain coefficient is 0.9863 between the predicted value and the real one.

Keywords

backpropagation; beverage industry; genetic algorithms; mean square error methods; microwaves; moisture measurement; neural nets; regression analysis; BP algorithm; BP arithmetic; artificial neural network; linear regression; mean absolute error; mean relative error; mean squared error; measurement error; microwave transmission technique; prediction precision; tea moisture content measurement; Antenna measurements; Arithmetic; Attenuation; Convergence; Linear regression; Measurement errors; Microwave measurements; Moisture measurement; Neural networks; Permittivity; BP algorithm; Moisture content; genetic algorithm(GA); open microwave resonant;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527777

Filename

1527777