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Commodity inventory risk early warning method and system based on statistical quartile distance and computer readable storage medium

An interquartile range and risk early warning technology, applied in computing, data processing applications, instruments, etc., can solve the problems of missing outliers, high computational overhead, large data volume, etc., to avoid differences, reduce workload, and calculate Efficient effect

Active Publication Date: 2020-02-04
SUNING CLOUD COMPUTING CO LTD
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AI Technical Summary

Problems solved by technology

[0006] Based on the above-mentioned defects of the prior art, the purpose of the present invention is to provide a method and system for early warning of commodity inventory risk based on the statistical interquartile range, so as to overcome the problems in the prior art, such as the large calculation cost and the large amount of data. Issues such as low timeliness

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  • Commodity inventory risk early warning method and system based on statistical quartile distance and computer readable storage medium
  • Commodity inventory risk early warning method and system based on statistical quartile distance and computer readable storage medium
  • Commodity inventory risk early warning method and system based on statistical quartile distance and computer readable storage medium

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Embodiment Construction

[0042] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] refer to Figure 1 ~ Figure 3 As shown, the embodiment of the present invention discloses a commodity inventory risk early warning method based on the statistical interquartile range, which includes the following steps:

[0044] Obtain the original commodity inventory data of all stores in a certain historical period;

[0045]Specifically, the commodity inventory data of all stores from the current date to a period of time before the current date is obtained from the commodity inventory database. The data in the database can be synchronously transmitted to the HDFS (distributed file storage) system of the HADOOP cluster at regular intervals, so that it can be obtained directly from the HDFS platform.

[0046] Inv...

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Abstract

The invention discloses a commodity inventory risk early warning method based on statistics of quartile distances. The method comprises the steps of obtaining original commodity inventory data of allstores in a certain historical time period; calculating according to the original commodity inventory data to obtain inventory incremental data; calculating an upper quartile and a lower quartile of the inventory incremental data, and calculating a quartile distance and an anomaly detection threshold according to the upper quartile and the lower quartile; and detecting whether the new inventory increment exceeds an abnormality detection threshold, and if so, judging the new inventory increment as abnormal data and pushing the abnormal data to a front-end early warning. The invention also provides a commodity inventory risk early warning system based on the statistical quartile distance, and a computer readable storage medium containing the method. According to the invention, the problems of large calculation overhead, abnormal value missed judgment when the data volume is large, low timeliness and the like in the prior art are solved.

Description

technical field [0001] The invention belongs to the application of big data in the field of retail risk control, and in particular relates to a method, system, and computer-readable storage medium for commodity inventory risk warning based on statistical interquartile ranges. Background technique [0002] At present, the physical stores of large retail enterprises are growing at an extremely fast rate. At the same time, due to the limitations of management, store managers may conduct illegal operations for their own self-interest and cause major economic losses to the enterprises. At present, they often rely more on post-event financial audits, Inventory and other methods to check the problem, the timeliness is very low, and it is often difficult to fully recover the financial loss after the problem is found, so we need to find an efficient and accurate method to detect suspicious in time through the monitoring and analysis of sales and financial indicators risk and notify r...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/08
CPCG06Q10/0635G06Q10/087
Inventor 欧文祥徐亮蒋旭曦
Owner SUNING CLOUD COMPUTING CO LTD
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