Optimal BP Arithmetic in Moisture Content Measurement

Author

Jiang, Yu ; Yang, Guohui ; Chen, Zhigong

Author_Institution

Inf. & Commun. Eng. Coll., Harbin Eng. Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3090

Lastpage

3093

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

arithmetic; backpropagation; chemistry computing; computerised instrumentation; convergence; genetic algorithms; measurement systems; microwave measurement; moisture measurement; neural nets; regression analysis; resonators; BP algorithm; artificial neural network training; genetic algorithm; linear regression; microwave transmission; open microwave resonant; tea moisture content measurement; Antenna measurements; Arithmetic; Attenuation; Convergence; Extraterrestrial measurements; Linear regression; Measurement errors; Microwave measurements; Moisture measurement; Neural networks; BP algorithm; Moisture content; genetic algorithm(GA); open microwave resonant;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712935

Filename

1712935