Short Paper:
Prediction and Demonstration of Coupling Development for Regional Logistics Economic Environment System
Jinxin Yao* and Man Ye**
*Rongcheng College, Harbin University of Science and Technology
No.2006 College Road, Rongcheng, Shandong 264300, China
**School of Management, Harbin Institute of Technology
No.92 Dongdazhi Street, Harbin, Heilongjiang 150001, China
The constitution of regional logistics economic environment system has been defined. The concepts of system coupling, coupling development and coupling development degree have been explained. Nonlinear autoregressive model of BP Neural Network is selected as the prediction model for coupling development degree. Coupling development degree of RLEES from 2003 to 2020 has been calculated and predicted by using the data of the Northeastern Region. The programming implementation is in MATLAB. The simulation result shows the logistics delay effect is 2 years. The prediction results showed that the coupling development degree of Northeast LEES is gradually improving with the improvement of economic growth and structural development.
- [1] Y. Zhang, J. Shang, and X. Yu, “Study on the coupling mechanism of urban economy and environment,” Acta Scientiae Circumstantiate, No.1, pp. 109-114, 2013.
- [2] Z. Zhang, S. Yang, and M. Sun, “The Construction and Application of Interaction Modeling about Urban Rural Coupling Region’s System – A Case Study of Nanjing,” Human Geography, Vol.4, pp. 90-94, 2010.
- [3] D. Wang, “Research on Development Model of Regional Logistics Based on Pole-Axis System Theory,” Master’s Thesis of Beijing Jiaotong University, Vol.6, p. 38, 2010.
- [4] H. Haken, “Synergetics – Successful natural wonders,” Shanghai Popular Science Press, p. 234, 1998.
- [5] J. Fite, G. Taylor, J. Usher, and J. Roberts, “Forecasting freight demand using economic indices,” Int. J. of Physical Distribution & Logistics Management, Vol.31, No.4, p. 299, 2011.
- [6] H. Zhou and J. Zang, “Nonlinear predictive functional control based on hybrid neural network,” Control Theory & Applications, Vol.1, pp. 110-113, 2012.
- [7] M. Su, “Research on Regional Logistics Demand Forecast Based on BP Neural network and Evidence Theory,” Master’s Thesis of Beijing Jiaotong University, Vol.5, pp. 22-23, 2010.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.