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Combined warehouse-in amount and warehouse-out amount prediction method

A forecasting method and technology of in-stock quantity, applied in the field of inventory management, to achieve the effect of high-precision forecasting results

Active Publication Date: 2017-09-01
XIAMEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, few studies have focused on this aspect—predicting the motion of related time-series datasets

Method used

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  • Combined warehouse-in amount and warehouse-out amount prediction method
  • Combined warehouse-in amount and warehouse-out amount prediction method
  • Combined warehouse-in amount and warehouse-out amount prediction method

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Experimental program
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Embodiment Construction

[0031] Embodiments of the present invention will be described in detail below.

[0032] A flow chart of a joint forecasting method for a storage-in quantity and a storage-out quantity based on data mining technology provided by the present invention, the method includes;

[0033] Step 1: Obtain the time series data of inbound and outbound quantities within a predetermined period of time, and perform data cleaning on these two types of time series data;

[0034] Step 2: Use data mining technology to establish a time series forecasting model;

[0035] Step 3: Considering the background knowledge that the in-stock and out-stock quantities in the inventory are interdependent, establish a model for the interdependence of the time-series data of the in-stock and out-stock quantities;

[0036] Step 4: Apply the relationship-dependent model established above to inventory forecasting, that is, establish the requirements of inventory forecasting under constraints, and obtain the final ...

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PUM

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Abstract

The invention relates to a combined warehouse-in amount and warehouse-out amount prediction method and relates to inventory management. According to the method, a prediction model based on multi-time-sequence data prediction is established, the prediction model is applied to the inventory management field, and the high precision prediction result can be realized on the condition that dependence relationships of warehouse-out and warehouse-in time sequences can be satisfied; the warehouse-in amount and warehouse-out amount time sequence data within a pre-determined time segment is acquired, and data cleaning of the two types of time sequence data is carried out; a time sequence prediction model is established through utilizing the data mining technology; background knowledge of mutual dependence of warehouse-in amount and warehouse-out amount of the inventory is considered, and a mutual dependence relationship model of the warehouse-in amount and warehouse-out amount time sequence data is established; the mutual dependence relationship model is applied to inventory prediction, so inventory prediction requirements are established to constraints, and the final prediction result is acquired.

Description

technical field [0001] The present invention relates to inventory management, in particular to a combined forecasting method for storage-in and out-stock quantities based on data mining technology. Background technique [0002] Inventory management is the general process of effectively monitoring fluctuations in incoming and outgoing goods from existing stocks [1]. This process generally includes two types of operations: (1) moving goods into the warehouse to ensure smooth sales (also known as storage); (2) handing over goods from the warehouse for sale (also known as outbound). These two types of operations produce two types of time-series data, each representing the volume of the corresponding operation over time. To achieve good inventory management, that is, trying to control the consumption of each operation and maintain the inventory status. [0003] In the existing inventory management system [2], the stock-in quantity and the stock-out quantity are usually forecast...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08
CPCG06Q10/087
Inventor 周绮凤李涛韩如愿郑理李磊
Owner XIAMEN UNIV