Research on Application of Fuzzy Neural Networks for Logistics Forecasting

被引：0

作者：

Li, Jizi ^{[1
]}

Liu, Chunling ^{[1
]}

Zuo, Zhiping ^{[1
]}

机构：

[1] Wuhan Univ Sci & Engn, Sch Econ & Management, Wuhan, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 7, PROCEEDINGS | 2008年

关键词：

logistics demand; forecasting; fuzzy logic; wavelet neural networks;

D O I：

10.1109/ICNC.2008.484

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a fuzzy neural network system to estimate future logistics demand was proposed and trained The structure of neural network in the system is different from BP network, with the nonlinear sigmoid functions in the networks replaced by fuzzy reasoning process and wavelet functions respectively. Moreover, the trained network system is put into practical logistics demand forecasting. The experimental results show that it has good properties such as a fast convergence, high precision and strong function approximation ability and is good at predicting future logistics amount.

引用

页码：255 / 259

页数：5

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