Sales Growth Rate Forecasting Using Improved PSO and SVM
Joint Authors
Zeng, Jun
Wen, Junhao
Jiang, Zhuo
Wang, Xibin
Gao, Xiang
Alam, Shafiq
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-24
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Accurate forecast of the sales growth rate plays a decisive role in determining the amount of advertising investment.
In this study, we present a preclassification and later regression based method optimized by improved particle swarm optimization (IPSO) for sales growth rate forecasting.
We use support vector machine (SVM) as a classification model.
The nonlinear relationship in sales growth rate forecasting is efficiently represented by SVM, while IPSO is optimizing the training parameters of SVM.
IPSO addresses issues of traditional PSO, such as relapsing into local optimum, slow convergence speed, and low convergence precision in the later evolution.
We performed two experiments; firstly, three classic benchmark functions are used to verify the validity of the IPSO algorithm against PSO.
Having shown IPSO outperform PSO in convergence speed, precision, and escaping local optima, in our second experiment, we apply IPSO to the proposed model.
The sales growth rate forecasting cases are used to testify the forecasting performance of proposed model.
According to the requirements and industry knowledge, the sample data was first classified to obtain types of the test samples.
Next, the values of the test samples were forecast using the SVM regression algorithm.
The experimental results demonstrate that the proposed model has good forecasting performance.
American Psychological Association (APA)
Wang, Xibin& Wen, Junhao& Alam, Shafiq& Gao, Xiang& Jiang, Zhuo& Zeng, Jun. 2014. Sales Growth Rate Forecasting Using Improved PSO and SVM. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-472305
Modern Language Association (MLA)
Wang, Xibin…[et al.]. Sales Growth Rate Forecasting Using Improved PSO and SVM. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-472305
American Medical Association (AMA)
Wang, Xibin& Wen, Junhao& Alam, Shafiq& Gao, Xiang& Jiang, Zhuo& Zeng, Jun. Sales Growth Rate Forecasting Using Improved PSO and SVM. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-472305
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472305