The Study on Livestock Production Prediction in Heilongjiang Province Based on Support Vector Machine

DOI

10.2991/iccsee.2013.300How to use a DOI?

Keywords

livestock production, support vector machine, prediction

Abstract

This paper uses the support vector machine (SVM) algorithm to study the prediction of livestock production in Heilongjiang province, forms the sample set with the 1985-2010 data in Heilongjiang province, and set up the SVM model between factors and livestock production. Use SVM on the input and output data for training and learning, approximate the implied function relationship by historical data, complete the mapping of the new data series, in order to complete the livestock production prediction for future years, and compare the prediction effects with other methods. The results show that, the prediction accuracy of livestock production of the SVM model is superior to other prediction methods.

Copyright

© 2013, 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/).

Download article (PDF)

TY  - CONF
AU  - Yang Tang
AU  - Cuixia Li
PY  - 2013/03
DA  - 2013/03
TI  - The Study on Livestock Production Prediction in Heilongjiang Province Based on Support Vector Machine
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1192
EP  - 1195
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.300
DO  - 10.2991/iccsee.2013.300
ID  - Tang2013/03
ER  -