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Commodity demand prediction information prediction system and method under multiple influence factors

A technology of influencing factors and demand forecasting, applied in market forecasting, commerce, instruments, etc., can solve problems such as different demand levels, weak data market reference, misjudgment of commodity demand forecasting, etc.

Pending Publication Date: 2020-07-10
中储南京智慧物流科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] At present, the demand forecast for commodities only judges the sales volume of commodities in previous years, but this is only limited to old products with high market acceptance. For new products or products that have just been sold in the market, a single data market reference Not strong, and the different annual economy will lead to different demand of users, which will cause misjudgment of commodity demand forecast. This application aims to refer to different data of commodities sold. Different data include sales volume of similar products, annual economy, Market pre-sale data can better predict the current commodity demand and intelligently formulate commodity demand plans

Method used

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  • Commodity demand prediction information prediction system and method under multiple influence factors
  • Commodity demand prediction information prediction system and method under multiple influence factors
  • Commodity demand prediction information prediction system and method under multiple influence factors

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] Example 1: Restricted conditions, the commodity pre-sale delivery sub-module puts N commodities on the network for network acceptance sampling, in which the network user acceptance is 63%, the historical influence probability of different factors is set to 7%, and the market share of similar products The proportion is 14%. Set the pre-market quantity of this batch of products to 60,000, the inventory of the product to 12,000, and set the predicted sales volume of the product to C. According to the formula:

[0051] C=(1-14%)*[(1-7%)*63%*60000)]-12000

[0052] = 30232.4-12000 = 18232.4

[0053] It is calculated that the current commodity market forecast sales volume is 18232.4, and the data collected by all modules are tabulated and summarized before the purchase plan is pre-formulated, and the plan formulation is sent to manual reference.

Embodiment 2

[0054] Example 2: Restricted conditions, the commodity pre-sale delivery sub-module puts N commodities on the network for network acceptance sampling, wherein the network user acceptance is 78%, the historical influence probability of different factors is set to 13%, and the market share of similar products The proportion is 20%. Set the pre-market quantity of this batch of products to 123,000, the inventory of the product to 10,000, and set the predicted sales volume of the product to C. According to the formula:

[0055] C=(1-20%)*[(1-13%)*78%*123000)]-10000=56774.24

[0056] It is calculated that the current commodity market forecast sales volume is 56,774.24, and the data collected by all modules are tabulated and summarized, and then the purchase plan is pre-formulated, and the plan formulation is sent to manual reference.

Embodiment 3

[0057] Example 3: limited conditions, the commodity pre-sale delivery sub-module puts N commodities on the network for network acceptance sampling, wherein the network user acceptance is 66%, the historical influence probability of different factors is set to 40%, and the market share of similar products The proportion is 40%. Set the pre-release quantity of this batch of products on the market as 41,000, the product inventory as 2000, and set the predicted sales volume of the product as C. According to the formula:

[0058] C=(1-40%)*[(1-40%)*66%*41000)]-2000=7741.6

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Abstract

The invention discloses a commodity demand prediction information prediction system and method under multiple influence factors. The system comprises a commodity influence factor point comprehensive statistics module, a commodity annual periodic rate analysis module, a commodity data change trend feature extraction module, an index comparison processing module and a purchase scheme prefabricationmodule. The commodity influence factor point comprehensive statistics module is used for carrying out statistics on influence factors influencing commodity sales; the commodity annual periodic rate analysis module is used for analyzing the sales volume of the commodities in the past years and predicting the sales volume of the commodities in the current year; the commodity data change trend feature extraction module is used for carrying out market user portraying on commodities and then judging acceptability of users at different age stages in the market, wherein the index comparison processing module is used for market selling conditions of different types of products, and the purchase scheme pre-making module is used for making a scheme according to data collected by all modules, so thedemand of a current commodity is predicted more perfectly, and a commodity demand scheme is made intelligently.

Description

technical field [0001] The invention relates to the field of commodity demand forecasting, in particular to a commodity demand forecasting information forecasting system and method under multiple influencing factors. Background technique [0002] Demand forecasting refers to the detailed analysis and research on the future market demand changes of the products of the proposed project based on the relevant survey data, mastering the internal laws of demand, and making correct estimates and judgments on its development trends, so as to ensure that the products of the proposed project are on the right track after they are put into production. , The variety meets the market demand and has strong competitiveness. The demand forecast of the proposed project is the precondition and foundation of the feasibility study. It is divided into domestic demand forecast and international demand forecast. Demand forecasting is based on market research data. Determine the content of the ma...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q10/08
CPCG06Q30/0203G06Q30/0284G06Q10/087Y02P90/30
Inventor 李敬泉
Owner 中储南京智慧物流科技有限公司
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