Analysis of Regional Logistics Demand Prediction Based on Support Vector Non-Linear Multiple Regression

This paper indicates the implications and characteristics of the regional logistics demand, and the key prediction indicator system in the course of regional logistics demand prediction is established and proposes an approach that support vector multiple regression (SVR) and principal component anal...

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Bibliographic Details
Published in2009 International Conference on Management and Service Science pp. 1 - 4
Main Authors Zhi-cheng Zheng, Xin Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2009
Subjects
Business
Communication standards
Economic forecasting
Equations
Linear regression
Logistics
Measurement standards
Principal component analysis
Production
Vectors
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Summary:This paper indicates the implications and characteristics of the regional logistics demand, and the key prediction indicator system in the course of regional logistics demand prediction is established and proposes an approach that support vector multiple regression (SVR) and principal component analysis (PCA) can solve the prediction problem of regional logistics demand. A numerical example based on Heilongjiang province of China is given to demonstrate the effectiveness and practicality of the proposed approach.
ISBN:1424446384
9781424446384
DOI:10.1109/ICMSS.2009.5302556