DocumentCode :
442159
Title :
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
Link To Document :
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