DocumentCode :
506743
Title :
Demand forecast of the Logistic park based on the Curve of growth theory
Author :
Wang, Fuhua
Author_Institution :
Sch. of Manage., Shandong Univ. of Finance, Jinan, China
Volume :
3
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
57
Lastpage :
61
Abstract :
According to current logistics forecast research both at home and abroad, regression analysis and exponential smoothing are of easy computation but unsatisfactory computational accuracy. Gray forecast, grey Markov model and neural network etc. are of high computational accuracy but the course of computation is comparatively complicated. Herein, the author introduce the curve of growth theory, a new quantitative method, to make demand forecast of the logistics parks. High-computation accuracy can be obtained through rather simple computation. After analysis to application of the forecasting model of logistic curve in logistic demand forecast is made, it has been brought forward that growth variation of the logistic park is in accordance with the logistic curve. Therefore, it is feasible to make demand forecast of the logistic park with logistic curve model, which has also been verified by computation examples. Finally, objective evaluation on application of logistic curve in demand forecast of logistic park was made in the text.
Keywords :
demand forecasting; logistics; curve of growth theory; logistic curve model; logistic demand forecasting; logistic park; quantitative method; Biological neural networks; Computer networks; Demand forecasting; Finance; Financial management; Home computing; Logistics; Predictive models; Regression analysis; Smoothing methods; Curve of growth theory; Demand of logistic park; Forecast; Logistic Curve;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5358233
Filename :
5358233
Link To Document :
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