DocumentCode :
1791003
Title :
Logistic Growth Prediction of B2C E-Commerce Based on Nonlinear Integral
Author :
Li Fang-Min ; Huang You-Wen
Author_Institution :
Guangzhou Vocational Coll. of Sci. & Technol., Guangzhou, China
fYear :
2014
fDate :
25-26 Oct. 2014
Firstpage :
341
Lastpage :
344
Abstract :
The precise logistics growth prediction can provide important reference for economic growth and consumer groups. According to the traditional logistics growth prediction method, the ordinary time prediction method was used to predict large deviations, and the result was unstable. So an improved logistic growth prediction of B2C e-commerce was proposed based on nonlinear integral. Firstly, the old data of logistic was analyzed, and then the nonlinear integral approach was used to predict growth of the B2C e-commerce step by step, the accurate logistics growth was achieved. Finally, B2C platform was used to do predict experiment, the result shows that nonlinear integral method can be used in the application, the prediction outcome is stable and reliable, and it has good predictive significance and application value in practice.
Keywords :
electronic commerce; logistics; B2C e-commerce; business to customer e-commerce model; electronic commerce; logistics growth prediction; nonlinear integral method; Algorithm design and analysis; Computational modeling; Electronic commerce; Estimation; Logistics; Prediction algorithms; Predictive models; B2C; E-Commerce; Logistics; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-6635-6
Type :
conf
DOI :
10.1109/ICICTA.2014.89
Filename :
7003552
Link To Document :
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