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Prediction of multidimensional time series based on GS-RSR-SVR and its application in agricultural economy

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成果类型:
期刊论文
作者:
Y.G. Xie;H.Y. Zhang;H.Y. Wang;L.F. Wang;Z.M. Yuan
通讯作者:
Zhang, H. Y.
作者机构:
Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization, Changsha 410128, China
Hunan Agricultural University, College of Information Science and Technology, Changsha 410128, China
Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, Changsha 410128, China
[Wang H.Y.] Kansas State University, Department of Statistics, Manhattan, KS 66506, United States
[Yuan Z.M.; Wang L.F.] Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization, Changsha 410128, China, Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, Changsha 410128, China
通讯机构:
[Zhang, H. Y.] H
Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization, Changsha 410128, China
语种:
英文
关键词:
Geo-statistics tool;Multidimensional time series;Prediction;Reasonable sample rejection;Support vector machine regression
期刊:
Bulgarian Journal of Agricultural Science
ISSN:
1310-0351
年:
2013
卷:
19
期:
6
页码:
1327-1336
机构署名:
本校为第一且通讯机构
院系归属:
信息科学技术学院
摘要:
This paper proposes a method that creatively applies a Geo-statistics tool (GS) to complete fast and adequate order determination and introduces a novel algorithm, named Reasonable Sample Rejection (RSR) to realize rational sample selection. Then, combined with Support Vector Machine Regression (SVR), a high precision non-linear prediction method named GSRSR- SVR is proposed for multidimensional time series. The main steps of the novel method includes: 1) determine the order for the dependent variable of the training samples based on one-dimensional GS aftereffect duration (range), 2) screen t...

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