Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Retail field supply chain inventory optimization method based on sales volume prediction

A technology for inventory optimization and supply chain, applied in the field of big data application and deep learning

Pending Publication Date: 2021-09-14
HUNAN UNIV
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention aims to solve the problem of accurate forecasting of commodity sales and provide a supply chain inventory optimization method for the retail field

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Retail field supply chain inventory optimization method based on sales volume prediction
  • Retail field supply chain inventory optimization method based on sales volume prediction
  • Retail field supply chain inventory optimization method based on sales volume prediction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] combined with figure 1 Technical framework diagram, the steps of the accurate forecasting method of commodity sales based on polymorphic feature fusion are as follows:

[0039] Step 1: Data Preprocessing

[0040] Obtain commodity basic data, historical sales data, promotional activity data, weather data, etc. Mark and remove products with negative historical sales volume, and perform data preprocessing operations such as completion for the historical sales data of a single product with discontinuous dates.

[0041] Step 2: Extract multi-type features

[0042] Extraction of the daily sales length and time statistical features of the product, including: the data features of the product on a certain day, the data features of the next 3 days, the data features of the next 18 days, the data features of the next 39 days, the data features of the past day, the data features of the past 3 days Data characteristics of the day, data characteristics of the past 7 days, data cha...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a retail field supply chain inventory optimization method based on sales volume prediction. The content of the invention mainly comprises (1) a commodity sales volume accurate prediction method based on polymorphic feature fusion; and (2) a supply chain inventory optimization method under logistics constraint based on commodity activeness classification. On the basis of the method, the polymorphic feature data of the commodities are extracted and fused, and the supply chain inventory optimization model is constructed by performing activeness classification according to the predicted sales volume of the commodities, so that the sales volume prediction-based retail field supply chain inventory optimization method is realized, and fund turnover is accelerated.

Description

technical field [0001] The invention relates to the field of big data application and deep learning, and is a method for optimizing supply chain inventory in the retail field based on sales forecast. Background technique [0002] Commodity supply chain technology will have a very important impact on the competition of any retail enterprise in the market. Traditional stores rely on the personal experience of the store manager to judge the quantity of inventory in the supply chain, and there will be problems such as inventory accumulation or insufficient inventory. For traditional sales forecasting methods, there are mainly time series analysis methods, such as simple average method, weighted average method or moving average method, etc. For abnormal sales data, there will be problems such as insufficient prediction accuracy. In recent years, with the rapid development of artificial intelligence technology represented by machine learning, methods such as artificial neural netw...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/04G06Q10/08G06Q30/02G06F30/27G06K9/62G06N3/04G06N3/08G06F111/04
CPCG06Q10/04G06Q10/087G06Q30/0201G06Q30/0202G06F30/27G06N3/08G06F2111/04G06N3/044G06F18/24G06F18/214
Inventor 肖源成秦拯张吉昕尹键溶
Owner HUNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com