Corn Drying Process Variables Screening and Its Moisture Content Forecast

DOI

10.2991/icemc-17.2017.113How to use a DOI?

Keywords

Moisture Content; Corn Drying; BP Neural Network; Variables Screening

Abstract

This study is based on BP neural network technology, through the MATLAB programmed processing, analyzed the factors which influenced the corn moisture content.Finally,through the MATLAB ,designed a method of online moisture content of corn. Through the comparison of predictive value and the true value of the corn. The prediction accuracy of this method could run up to 95% under the same batches. This method provide a reliable theoretical basis for the online determination of moisture content of corn.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wang Kefei
AU  - Lu Ming
AU  - Ke Hongdi
PY  - 2016/06
DA  - 2016/06
TI  - Corn Drying Process Variables Screening and Its Moisture Content Forecast
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Computer Science (ICEMC 2017)
PB  - Atlantis Press
SP  - 566
EP  - 570
SN  - 2352-538X
UR  - https://doi.org/10.2991/icemc-17.2017.113
DO  - 10.2991/icemc-17.2017.113
ID  - Kefei2016/06
ER  -