Application of An Improved Grey Neural Network in Grain Yield Prediction
Authors
H. Lv, T. Lei, X. L Huang, Y. K Zhang
Corresponding Author
H. Lv
Available Online June 2015.
- DOI
- 10.2991/cisia-15.2015.153How to use a DOI?
- Keywords
- grey neural network; grey model; grain yield prediction
- Abstract
Grain yield presents a complex nonlinear relationship with variables, and takes on randomness and mutability. It is hard to describe the prediction model with traditional linear model. Grey model can be used to process samples with great stochastic volatility. In this paper, we propose to use the grey neural network to predict the grain yield. Experiments are carried out on the beans yield, rice yield and corn yield respectively to evaluate the prediction performance. The promising experimental results validate the effectiveness of our prediction model.
- Copyright
- © 2015, 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 - H. Lv AU - T. Lei AU - X. L Huang AU - Y. K Zhang PY - 2015/06 DA - 2015/06 TI - Application of An Improved Grey Neural Network in Grain Yield Prediction BT - Proceedings of the International Conference on Computer Information Systems and Industrial Applications PB - Atlantis Press SP - 560 EP - 564 SN - 2352-538X UR - https://doi.org/10.2991/cisia-15.2015.153 DO - 10.2991/cisia-15.2015.153 ID - Lv2015/06 ER -