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

Method for improving the robustness of sales forecasts

A technology for forecasting results and robustness, applied in the field of big data, can solve the problems of poor robustness of sales forecast results, poor correction effect, and lack of general applicability, so as to avoid singularity, reduce volatility, and reduce accidental factors. effect of influence

Inactive Publication Date: 2018-12-18
SICHUAN CHANGHONG ELECTRIC CO LTD
View PDF16 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is: to propose a method for improving the robustness of sales forecast results, and to solve the problems of poor robustness of sales forecast results, lack of universal applicability and poor correction effect in traditional technologies

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
  • Method for improving the robustness of sales forecasts
  • Method for improving the robustness of sales forecasts
  • Method for improving the robustness of sales forecasts

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0073] In this embodiment, the month is used as the time dimension of the sales forecast, and the sales forecast of TV sets is taken as an example for illustration.

[0074] 1. Data preparation:

[0075] Collect historical order data (including time, sales volume, price, etc.), historical macroeconomic data and historical competitive product data

[0076] 2. Determine the predictive model:

[0077] Time series model: state space exponential smoothing model—ETS model;

[0078] Time series and regression analysis mixed model: dynamic regression ARIMA model;

[0079] Select the above two models for sales forecast.

[0080] 3. Hierarchy of historical sales data:

[0081] The historical sales data is stratified according to the size attributes of TVs, and a two-level hierarchical structure is obtained including the total sales of TVs and the sales of 30-50 size segments, 50-70 size segments, and 70-inch and above size segments.

[0082] 4. Data fusion and preprocessing:

[00...

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 the field of big data, and discloses a method for improving the robustness of the sales volume prediction result, which solves the problems of poor robustness of the sales volume prediction result in the traditional technology, non-universal applicability and poor correction effect. The method comprises the following steps: a. performing data preparation and selection of asales forecast model; B. stratifying that sales volume time series; C. fusing and preprocessing the data in the hierarchical structure; D. predicting the data value of the relevant factors in the time period for which prediction is required; E. training and testing the selected sales forecasting models and calculating test errors; F. predicting and outputting the sales volume forecast value corresponding to the corresponding time by using the trained sales forecast model; G. integrating the sales volume forecast values output by each model to obtain the integrated forecast values; H. adoptingtime series hierarchy algorithm to modify the ensemble prediction value. The invention is suitable for accurately predicting the sales volume of a product.

Description

technical field [0001] The invention relates to the field of big data, in particular to a method for improving the robustness of sales forecast results. Background technique [0002] Sales forecast refers to the estimation of the sales of all products or specific products within a certain period of time in the future. Sales forecast plays an important role in the production, management and sales of products, but it is not easy to make high-quality sales forecast. Sales forecasting technology mainly uses historical sales data and external influencing factor data, adopts time series analysis method or machine learning method, and establishes a model to predict sales. [0003] The sales forecast method in traditional technology has the following problems: [0004] 1) Due to the single forecast method used, unknown accidental factors will bring great volatility to the sales forecast results, and the robustness of the sales forecast results is poor; [0005] 2) Due to the use ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06F17/17
CPCG06F17/175G06Q30/0201G06Q30/0202
Inventor 邹文君杜科蒲文龙
Owner SICHUAN CHANGHONG ELECTRIC CO LTD
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