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

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.

The Cooperation of Industrial Clusters and Regional Logistics of Shaanxi Province: An Evaluation Research

As a middle organization between enterprise organization which gains the competition advantage and eration of industrial clusters and regional logistics refers development of modern regional logistics. On the basis and market, industrial cluster is now the space industrial innovation advantage for a nation or a region. The coop- to improvement of industrial clusters＇ competitiveness and of reviewing the recent years＇ situation of Shaanxi Prov- ince＇s regional logistics and its industrial clusters, this paper analyzes positively about the supporting role of the regional logistics, builds gray relational model by choosing corresponding indicators, and carries out test of signif- icance. Finally it brings out strategic recommendations to and regional logistics enhance the level of cooperation of industrial clusters

Prediction Method for Regional Logistics

Currently applied prediction methods of regional freight traffic and freight ton-kilometer forecasting were analyzed using typical Chinese regional goods transportation characteristics. The review of prediction methods showes that practical planning experts tend to apply the traditional methods which are easier to implement. The comparison also demonstrates that a combination of traditional methods is more effective than the simple models for practical planning. Research using the statistical data for the Yangtze Delta, Pearl River Delta, and Bohai Rim areas shows that ignoring differences between transport modes impacts the prediction accuracy. The four main transport modes suit different methods. The results show that the power model is better for railways, and the linear model is better for highways and waterways. Thus a combined model gives better results for all modes. The results for regional systems can be generalized to national transportation systems.