Du Zhi-Guo
Department of Information Management, Southwest University, Rongchang, Chongqing, 402460, China
Hu Da-Hui
Department of Information Management, Southwest University, Rongchang, Chongqing, 402460, China
ABSTRACT
The fluctuations in pork prices not only affect our daily life but also the development of social economy. Therefore, it is particularly important to reasonably predict the pork prices within a period in the future. The common price prediction models have different defects and application limitation. Summarizing advantages and disadvantages of each prediction model, this study, based on the grey theory, improves the unreasonable solution procedures of the original methods and proposes an improved grey theory model. And it makes use of simulation instruments to validate the model. The simulation experiments show that the error between the predicted pork price and the actual pork price is within 10% and the improved model can reasonably predict the pork price trend within a period in the future.
PDF References Citation
How to cite this article
Du Zhi-Guo and Hu Da-Hui, 2013. Application Study on Improved Grey Theory Model in the Pork Price Prediction. Information Technology Journal, 12: 4153-4157.
DOI: 10.3923/itj.2013.4153.4157
URL: https://scialert.net/abstract/?doi=itj.2013.4153.4157
DOI: 10.3923/itj.2013.4153.4157
URL: https://scialert.net/abstract/?doi=itj.2013.4153.4157
REFERENCES
- Huang, G.B., H. Zhou, X. Ding and R. Zhang, 2012. Extreme learning machine for regression and multiclass classification. IEEE Trans. Syst. Man Cybern. Part B (Cybern.), 42: 513-529.
CrossRefDirect Link - Suykens, J.A.K. and J. Vandewalle, 1999. Least squares support vector machine classifiers. Neural Process. Lett., 9: 293-300.
CrossRefDirect Link - Wu, C.H., J.M. Ho and D.T. Lee, 2004. Travel-time prediction with support vector regression. Trans. Intell. Trans., 5: 276-281.
CrossRefDirect Link