Corn Drying Process Variables Screening and Its Moisture Content Forecast
Wang Kefei, Lu Ming, Ke Hongdi
Available Online June 2016.
- 10.2991/icemc-17.2017.113How to use a DOI?
- Moisture Content; Corn Drying; BP Neural Network; Variables Screening
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.
- © 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/).
Cite this article
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 -