Regional Logistics Demand Forecast Based on Least Square and Radial Basis Function

魏乐琴; 张安国

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Regional Logistics Demand Forecast Based on Least Square and Radial Basis Function

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Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the traditional prediction method can not guarantee the accuracy of prediction.Taking Xiamen City as an example,this paper selects the primary industry,the secondary industry,the tertiary industry,the total amount of investment in fixed assets,total import and export volume,per capita consumption expenditure,and the total retail sales of social consumer goods as the influencing factors,and uses a combining model least square and radial basis function(LS-RBF)neural network to analyze the related data from years 2000 to 2019,so as to predict the logistics demand from years 2020 to 2024.The model can well fit the training data,and the experimental results obtained from the comparison between the predicted value and the actual value in 2019 show that the error rate is very small.Therefore,the prediction results are reasonable and reliable.This method has high prediction accuracy,and it is suitable for irregular regional logistics demand forecast.

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《东华大学学报：英文版》 |2020年第5期|446-454|共9页
作者
魏乐琴; 张安国;
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作者单位

School of Humanities and Teachers'Education;

Wuyi University;

Wuyishan 354300;

China;

College of Physics and Information Engineering;

Fuzhou University;

Fuzhou 350108;

China;

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原文格式 PDF
正文语种 chi
中图分类交通工程与交通管理;
关键词
regional logistics; demand forecast; least square and radial basis function(LS-RBF);

Regional Logistics Demand Forecast Based on Least Square and Radial Basis Function

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