Logistics node layout optimization method and system based on agricultural product cold-chain logistics requirements

A technology of cold chain logistics and agricultural products, applied in logistics, neural learning methods, biological neural network models, etc., can solve inaccurate prediction results, failure to meet the agricultural product market, and scientific and reasonable solution to the logistics node selection of agricultural product cold chain logistics The location problem logistics node scale optimization problem and other problems, to achieve the effect of solving the location problem

Pending Publication Date: 2021-01-08
SHANDONG UNIV OF FINANCE & ECONOMICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional transportation and circulation of agricultural products can no longer satisfy the modern agricultural product market, nor can it satisfy the people's pursuit of the quality of agricultural products
[0004] The rapid development of cold chain logistics caters to people's growing demand for products such as eggs, milk, fresh products, fruits and vegetables. However, as far as the inventor knows, the existing cold chain logistics demand forecasting lacks a reasonable forecasting method, and the forecasting results are inaccurate , cannot effectively guide the production and development of the logistics industry, especially cannot scientifically and rationally solve the problem of location selection of logistics nodes for cold chain logistics of agricultural products and the problem of scale optimization of existing logistics nodes

Method used

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  • Logistics node layout optimization method and system based on agricultural product cold-chain logistics requirements
  • Logistics node layout optimization method and system based on agricultural product cold-chain logistics requirements
  • Logistics node layout optimization method and system based on agricultural product cold-chain logistics requirements

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Experimental program
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Embodiment 1

[0031] This embodiment provides a logistics node layout optimization method based on agricultural product cold chain logistics requirements;

[0032] like figure 1 As shown, the logistics node layout optimization method based on the cold chain logistics demand of agricultural products includes:

[0033] S101: Perform variable screening on the obtained basic data of agricultural product cold chain logistics in the historical time range of the region to be predicted, and select several variables;

[0034] S102: Predict each variable to obtain predicted values ​​of all variables;

[0035] S103: Based on the predicted values ​​of all variables and the multiple linear regression model, obtain the predicted value of the first agricultural product cold chain logistics demand;

[0036] Based on the predicted values ​​of all variables and the pre-trained BP neural network, the predicted value of the second agricultural product cold chain logistics demand is obtained;

[0037] S104: ...

Embodiment 2

[0114] This embodiment provides a logistics node layout optimization system based on agricultural product cold chain logistics requirements;

[0115] Logistics node layout optimization system based on agricultural product cold chain logistics demand, including:

[0116] The variable screening module is configured to: perform variable screening on the acquired agricultural product cold chain logistics basic data within the historical time range of the area to be predicted, and select several variables;

[0117] A variable prediction module configured to: predict each variable to obtain predicted values ​​of all variables;

[0118] The demand prediction module is configured to: obtain the first agricultural product cold chain logistics demand prediction value based on all variable prediction values ​​and multiple linear regression models; obtain the second agricultural product cold chain logistics demand prediction value based on all variable prediction values ​​and a pre-traine...

Embodiment 3

[0125] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are programmed Stored in the memory, when the electronic device is running, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in Embodiment 1 above.

[0126] It should be understood that in this embodiment, the processor can be a central processing unit CPU, and the processor can also be other general-purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, o...

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PUM

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Abstract

The invention discloses a logistics node layout optimization method and system based on agricultural product cold-chain logistics demands. The method comprises steps of carrying out the variable screening of the obtained agricultural product cold-chain logistics basic data in a historical time range of a to-be-predicted region, and screening a plurality of variables; predicting each variable to obtain predicted values of all the variables; obtaining a first agricultural product cold-chain logistics demand prediction value based on all variable prediction values and the multiple linear regression model; obtaining a second agricultural product cold-chain logistics demand prediction value based on all variable prediction values and a pre-trained BP neural network; performing weighted summation on the first agricultural product cold-chain logistics demand prediction value and the second agricultural product cold-chain logistics demand prediction value to obtain a final agricultural productcold-chain logistics demand prediction value; and based on the final agricultural product cold-chain logistics demand prediction value of the to-be-predicted area, the scale of the existing logisticsnode and the distance between the existing logistics node and the to-be-predicted area, obtaining a scale optimization scheme of the logistics node.

Description

technical field [0001] The present application relates to the technical field of logistics demand forecasting, in particular to a logistics node layout optimization method and system based on cold chain logistics demand of agricultural products. Background technique [0002] The statements in this section merely mention the background art related to this application, and do not necessarily constitute the prior art. [0003] In today's 21st century, changes in people's ideas and a prosperous market economy have gradually promoted a new agricultural product circulation system. An agricultural product market that focuses on high-quality agricultural products, efficient agricultural product transportation, and benign economies of scale has gradually formed. The traditional transportation and circulation of agricultural products can no longer satisfy the modern agricultural product market, nor can it satisfy the people's pursuit of the quality of agricultural products. [0004] ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/08G06Q50/02G06N3/08
CPCG06Q10/06315G06Q10/083G06Q50/02G06N3/08
Inventor 王睿闻思源
Owner SHANDONG UNIV OF FINANCE & ECONOMICS
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