Paper Info
Title
The grey generalized Verhulst model and its application for forecasting Chinese pig price index
Abstract
The Verhulst model is used in many natural and social systems. When simulating and predicting system sequences with an inverted U shape or a signal peak feature by the grey Verhulst model (abbreviated as GVM), such as the pig price index, a drift phenomenon happens sometimes. We introduce a grey generalized Verhulst model named as GGVM to address this problem. Compared with the GVM, the GGVM contains a constant as the grey action quantity. Besides, the multivariable grey generalized Verhulst model is also given. Three cases containing Glipizide tablets blood drug concentration series, the number of traffic deaths, and consumer price index (abbreviated as CPI) sequences are utilized to demonstrate that GGVM can eliminate the drift phenomenon effectively. Given that the pork is the most consumed meat for Chinese residents and the fluctuation of its price is closely related to the interests of residents and pig-breeding enterprises, it is important to predict the pork price. So the prediction of pork price index whose time series possesses an inverted U shape is carried out by GGVM, GVM, and intelligent algorithm models, including LSSVR, $$\varepsilon $$-SVR, and RBF in the empirical part. The results show that GGVM produces higher accurate simulation and prediction than the models as given above.
Year
DOI
Venue
2020
10.1007/s00500-019-04248-0
Soft Computing
Keywords
Field
DocType
Grey Verhulst model, Grey generalized Verhulst model, Pig price index, Intelligent algorithm models
Econometrics,Blood drug concentration,Mathematical optimization,Multivariable calculus,Computer science,Price index,Consumer price index,Gray (horse)
Journal
Volume
Issue
ISSN
24
7
1432-7643
Citations 
PageRank 
References 
1
0.36
0
Authors
2
Name
Order
Citations
PageRank
Weijie Zhou110.36
Lingling Pei231.08