This article predicts Southeast Asia’s logistics needs from a Southeast Asian logistics development perspective. This is not only an important prerequisite for supporting Southeast Asia’s trade policy, but also prom...This article predicts Southeast Asia’s logistics needs from a Southeast Asian logistics development perspective. This is not only an important prerequisite for supporting Southeast Asia’s trade policy, but also promoting the development of Southeast Asia’s logistics industry, building logistics infrastructure and improving the level of logistics services. Due to differences in economic development levels, trade structures, infrastructure construction and logistics development levels of Southeast Asian countries. Therefore, considering the actual situation of Southeast Asian countries, this article selected 21 cities in Southeast Asia as the research object. Use L-OD logistics demand forecasting method to forecast logistics demand in Southeast Asia. Obtain the amount of logistics occurrence and attraction in 21 cities in Southeast Asia in the future. And construct a double constrained gravity model to predict logistics distribution in Southeast Asia. The forecast results provide scientific data support for future logistics development planning in Southeast Asia.展开更多
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 trad...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.展开更多
Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales ...Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning.展开更多
With the rapid economic development and the increasing speed and scale of grid construction, material procurement and management, cost control is facing new demands and challenges.This paper proposes on innovative man...With the rapid economic development and the increasing speed and scale of grid construction, material procurement and management, cost control is facing new demands and challenges.This paper proposes on innovative management and forecasting methods, from inventory management and demand forecasting perspective supplies,through these two key nodes in-depth research and analysis, this paper provides a theoretical support for the realization of effective materials management.展开更多
文摘This article predicts Southeast Asia’s logistics needs from a Southeast Asian logistics development perspective. This is not only an important prerequisite for supporting Southeast Asia’s trade policy, but also promoting the development of Southeast Asia’s logistics industry, building logistics infrastructure and improving the level of logistics services. Due to differences in economic development levels, trade structures, infrastructure construction and logistics development levels of Southeast Asian countries. Therefore, considering the actual situation of Southeast Asian countries, this article selected 21 cities in Southeast Asia as the research object. Use L-OD logistics demand forecasting method to forecast logistics demand in Southeast Asia. Obtain the amount of logistics occurrence and attraction in 21 cities in Southeast Asia in the future. And construct a double constrained gravity model to predict logistics distribution in Southeast Asia. The forecast results provide scientific data support for future logistics development planning in Southeast Asia.
基金Social Science Research Project of Education Department of Fujian Province,China(No.JAS160571)Key Project of Education and Teaching Reform of Undergraduate Universities in Fujian Province,China(No.FBJG20190130)Educational Research Project of Social Science for Young and Middle Aged Teachers in Fujian Province,China(No.JAS19371)。
文摘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.
文摘Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning.
文摘With the rapid economic development and the increasing speed and scale of grid construction, material procurement and management, cost control is facing new demands and challenges.This paper proposes on innovative management and forecasting methods, from inventory management and demand forecasting perspective supplies,through these two key nodes in-depth research and analysis, this paper provides a theoretical support for the realization of effective materials management.
