CN113592532A - Method and device for restoring historical demand of commodity - Google Patents
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Abstract
The invention relates to the technical field of industrial prediction, in particular to a method and a device for restoring historical demand of commodities, wherein the method comprises the following steps: the method comprises the steps of determining the category of a commodity based on the historical sales volume condition of the commodity, determining the out-of-stock time of the commodity based on the category, obtaining the sales volume of the commodity on a non-out-of-stock date, interpolating the sales volume of the out-of-stock time based on the sales volume of the non-out-of-stock date, obtaining the historical demand volume of the commodity based on the interpolated sales volume of the out-of-stock date and the sales volume of the non-out-of-stock date, interpolating the sales volume of the out-of-stock date in an interpolation mode to make up the demand loss caused by the shortage of the stock, summing all demands to obtain the historical demand volume of the commodity, restoring the historical demand of the commodity, and providing an accurate basis for prediction of future demands.
Description
Technical Field
The invention relates to the technical field of industrial prediction, in particular to a method and a device for restoring historical demand of commodities.
Background
In the process of predicting the market demand, the future demand is usually predicted based on the historical market demand, and the historical market demand is not the real demand of the history, for example, 100 units of goods are required within a preset time period according to the historical sales data, but the historical demand is only 20 because the stock quantity is only 20 units of goods, so that the future demand is predicted according to the historical market demand, and the result is inaccurate.
Therefore, how to improve the prediction accuracy of future demands is a technical problem to be solved urgently at present.
Disclosure of Invention
In view of the above, the present invention has been made to provide a method and apparatus for restoring a historical demand for goods that overcomes or at least partially solves the above-mentioned problems.
In a first aspect, the present invention provides a method for restoring a historical demand of a commodity, including:
determining the category of the commodity based on the historical sales condition of the commodity;
determining an out-of-stock date for the item based on the category;
acquiring the sales volume of the non-backorder date of the commodity based on the category;
interpolating the sales of the backorder date based on the sales of the non-backorder date;
and obtaining the historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
Further, the obtaining the category of the commodity based on the historical sales volume condition of the commodity comprises:
judging whether the sales volume of the commodity changes seasonally or not;
if yes, determining that the commodity is a seasonal commodity;
if not, determining that the commodity is a non-seasonal commodity;
for the seasonal commodities, when the ratio of the sales days of which the sales volume is 0 to the sales days in the busy sales season is lower than a preset value, determining that the category of the commodities is a seasonal conventional product;
for the seasonal commodities, when the percentage of the sales days of which the sales volume is 0 in the high sales season is higher than the preset value, determining that the category of the commodities is a seasonal long-tail commodity;
for non-seasonal commodities, when the proportion of the sales days of which the sales are 0 in the whole year is lower than the preset value, determining that the category of the commodities is non-seasonal conventional commodities;
and for non-seasonal commodities, when the proportion of the sale days of the commodities with the sale of 0 in the whole year is higher than the preset value, determining that the commodities are classified as non-seasonal long-tailed commodities.
Further, the determining the backorder date of the item based on the category includes:
determining the time for getting on and off the shelf of the commodity;
determining a backorder date of the goods from the time of getting on and off the shelf based on the category.
Further, the determining the time for getting on and off the shelf of the commodity comprises:
when the commodity shelf loading and unloading data exist, determining the shelf loading and unloading time of the commodity based on the shelf loading and unloading data; or
When the commodity shelf loading and unloading data do not exist, acquiring initial sales volume dates and final sales volume dates in historical sales volume data of the commodities in the whole year;
and determining the time for getting on and off the shelves of the commodity based on the initial sales volume date and the final sales volume date.
Further, the determining the out-of-stock date of the commodity from the shelf loading and unloading time based on the category comprises:
when the category of the commodity is seasonal conventional goods or non-seasonal conventional goods, determining the date when the stock quantity of the commodity is 0 from the shelf loading and unloading time as the out-of-stock date;
and when the category of the commodity is seasonal long-tail products or non-seasonal long-tail products, determining the date when the stock quantity and the sales volume of the commodity are both 0 from the shelf loading and unloading time as the stock out date.
Further, based on the category, the obtaining the sales amount of the non-backorder date of the commodity comprises:
when the category of the commodity is a seasonal conventional product or a seasonal long-tail product, acquiring the sales volume of a non-backorder date in the same month as the backorder date of the commodity; or
And when the type of the commodity is a non-seasonal conventional product or a non-seasonal long-tail product, acquiring the sales volume of the non-backorder date of the commodity in the shelf loading and unloading time.
Further, the interpolating the sales on the out-of-stock date based on the sales on the out-of-stock date includes:
when the category of the commodity is a seasonal conventional commodity or a seasonal long-tail commodity, interpolating the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date in the same month as the out-of-stock date of the commodity;
and when the type of the commodity is a non-seasonal conventional commodity or a non-seasonal long-tail commodity, interpolating the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date of the commodity in the shelf loading and unloading time.
In a second aspect, the present invention further provides a device for restoring historical demand of a commodity, including:
the first determination module is used for determining the category of the commodity based on the sales volume condition of the commodity;
a second determining module for determining the backorder date of the goods based on the category;
the acquisition module is used for acquiring the sales volume of the non-backorder date of the commodity;
the interpolation module is used for interpolating the sales volume of the backorder date based on the sales volume of the non-backorder date;
and the obtaining module is used for obtaining the historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
In a third aspect, the present invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above-mentioned method steps when executing the program.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the above-mentioned method steps.
One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:
the invention provides a method for restoring historical demand of commodities, which comprises the following steps: the method comprises the steps of determining the category of a commodity based on the historical sales volume condition of the commodity, determining the out-of-stock time of the commodity based on the category, obtaining the sales volume of the commodity on a non-out-of-stock date, interpolating the sales volume of the out-of-stock time based on the sales volume of the non-out-of-stock date, obtaining the historical demand volume of the commodity based on the interpolated sales volume of the out-of-stock date and the sales volume of the non-out-of-stock date, interpolating the sales volume of the out-of-stock date in an interpolation mode to make up the demand loss caused by the shortage of the stock, summing all demands to obtain the historical demand volume of the commodity, restoring the historical demand of the commodity, and providing an accurate basis for prediction of future demands.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart illustrating steps of a method for restoring historical demand of a commodity according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an apparatus for restoring historical demand of a commodity according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer device for implementing the method for restoring the historical demand of the commodity according to the embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Example one
A first embodiment of the present invention provides a method for restoring historical demand of a commodity, which is applied to forecasting demand of the commodity, and as shown in fig. 1, the method includes:
s101, determining the category of the commodity based on the historical sales condition of the commodity;
s102, determining the stock out date of the commodity based on the category;
s103, acquiring the sales volume of the non-backorder date of the commodity based on the category;
s104, interpolating the sales of the backorder date based on the sales of the non-backorder date;
and S105, obtaining the historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
Firstly, when a type of commodity is obtained and the historical demand of the type of commodity needs to be reduced, the type of the commodity is determined.
S101, based on the historical sales volume condition of the commodity, the category of the commodity is determined.
Judging whether the sales volume of the commodity changes seasonally or not; if yes, determining that the commodity is a seasonal commodity; if not, determining that the commodity is a non-seasonal commodity. Seasonal goods such as ice cream, or fur and the like have seasonal characteristics.
For seasonal commodities, when the proportion of the sales days of which the sales volume is 0 in the busy season is lower than a preset value, the class of the commodity is determined to be a seasonal conventional product, and the preset value is 30%, of course, other proportions can be provided, and the method is not limited herein. And when the occupation ratio of the sales days with the sales volume of 0 in the peak sales season is higher than a preset value, determining that the category of the commodity is a seasonal long-tail product.
The long-tail product refers to a commodity which is very infrequent in demand and has large demand variation, and the seasonal long-tail product has the characteristic of changing along with seasons, and the demand variation is large in the seasonal variation trend.
Aiming at non-seasonal commodities, when the proportion of sales days with the sales volume of 0 of the commodities in the whole year is lower than a preset value, determining that the commodity is a non-seasonal conventional commodity; and if the percentage of the sales days of which the sales volume is 0 in the whole year is higher than the preset value, determining that the category of the commodity is the non-seasonal long-tail commodity. Such as biscuits, washing products, etc.
Therefore, the categories of the commodities are divided into four categories, namely seasonal regular products, seasonal long-tailed products, non-seasonal regular products and non-seasonal regular products.
After the category of the product is determined, the date of stock out of the product is determined according to the category of the product, that is, S102 is executed, and the date of stock out of the product is determined based on the category.
Determining the time for getting on and off the shelves of the commodity; based on the category, the out-of-stock date of the product is determined from the time of getting on and off the shelf.
On the other hand, when there is the commodity shelving data, the shelving time of the commodity is determined based on the shelving data, that is, the shelving time of the commodity is determined according to the shelving data in the history data.
On the other hand, when there is no commodity shelving data, the initial sales date in the historical sales data of commodities in the whole year is acquired, for example, from 1 month to 12 months, the initial sales date is 2 months and 3 days, and the final sales date is 5 months and 4 days.
Next, the time to put the commodity on or off the shelf is determined based on the initial sales date and the final sales date.
Specifically, the initial sales date may be moved forward by a preset time to obtain the time to put on the shelf, and the end sales date may be delayed backward by the preset time to obtain the time to put off the shelf, so as to determine the time to put on the shelf and put off the shelf of the commodity.
The preset time period is determined based on market rules, and is not limited herein.
In an alternative embodiment, the initial sales date is moved forward by 15 days to obtain 1 month and 19 days, the first day of the month in which the 1 month and 19 days are located, i.e. 1 month and 1 day, is the time for putting the commodity on shelf, the final sales date is 5 months and 4 days plus 15 days to obtain 5 months and 19 days, and the last day of the month in which the 5 months and 19 days are located: and 5, 31 months and 5 days are taken as the shelf-off time, so that the shelf-off time of the commodity is determined.
After the time for putting the product on or off the shelf is determined, the date of shortage of the product is determined from the time for putting the product on or off the shelf based on the category of the product.
The determination of the out-of-stock date is related to the category of the goods, and the time except the time of going up and down is first eliminated by determining the time of going up and down because the out-of-stock time of the goods is determined within the time of going up and down.
When the category of the commodity is seasonal regular products or non-seasonal regular products, the date when the stock quantity of the commodity is 0 is determined from the time of getting on and off the shelf as the out-of-stock date.
When the category of the commodity is seasonal long-tail products or non-seasonal long-tail products, the date when the stock quantity and the sales volume of the commodity are both 0 is determined as the stock out date from the time of getting on and off the shelf.
In the case of long-tailed goods, since the demand amount greatly varies, when the stock quantity and the sales amount are both 0, it is necessary to determine the stock out date, and neither the stock quantity nor the sales amount is 0 can be regarded as the stock out date.
At the same time, in S103, the sales volume of the non-stock-out date of the product is acquired based on the category of the product.
Specifically, the sales amount of the non-stock-out date of the commodity is acquired based on the category of the commodity during the shelf ascending and descending time.
And when the category of the commodity is seasonal regular commodities or seasonal long-tail commodities, acquiring the sales volume of the non-backorder date in the same month as the backorder date of the commodity.
For the seasonal regular product or the seasonal long-tail product, since the actual sales volume of the out-of-stock date of the product is close to the sales volume of the non-out-of-stock date in the same month, the sales volume of the non-out-of-stock date in the same month as the out-of-stock date of the product needs to be acquired as a basis for interpolating the sales volume of the out-of-stock date.
And when the category of the commodity is non-seasonal conventional goods or non-seasonal long-tail goods, acquiring the sales volume of the non-shortage date of the commodity in the shelf loading and unloading time.
For non-seasonal regular products or non-seasonal long-tail products, the actual sales volume of the out-of-stock dates of the products is similar to the sales volume of the non-out-of-stock dates of the products in the on-off shelf time, so the sales volume of the non-out-of-stock dates of the products in the on-off shelf time is taken as a basis for interpolating the sales volume of the out-of-stock dates.
Therefore, S104 is executed to interpolate the sales amount on the out-of-stock date based on the sales amount on the out-of-stock date.
In an alternative embodiment, when the category of the commodity is seasonal regular commodity or seasonal long-tail commodity, the sales amount of the backorder date is interpolated based on the sales amount of the non-backorder date in the same month as the backorder date of the commodity;
in another alternative embodiment, when the category of the commodity is non-seasonal regular commodity or non-seasonal long-tail commodity, the sales amount of the out-of-stock date is interpolated based on the sales amount of the non-out-of-stock date of the commodity in the on-off shelf time.
Specifically, for seasonal type conventional products, because the date with the stock quantity of 0 is determined as the stock out date, when the stock out date is interpolated, any sales volume of the stock out date which is not the stock out date in the same month as the stock out date is selected as a first target sales volume, whether the sales volume of the stock out date is larger than the first target sales volume needs to be judged, and if yes, the sales volume of the stock out date is recorded; if not, the first target sales amount is interpolated with the sales amount of the backorder date.
For example, for seasonal conventional article a, the out-of-stock dates are 3 months 13 days and 3 months 19 days. And the sales for 3 month and 13 days is 17, the sales for 3 month and 19 days is 5, wherein 15 is the sales for one non-stock out date in 3 months, so the sales for 3 month and 13 days are kept recorded, and the sales for 3 month and 19 days are interpolated to be 15.
Specifically, in the case of the seasonal type long-tail product, since the date on which the stock quantity and the sales volume are both 0 is determined as the stock out date, when the stock out date is interpolated, the sales volume of any non-stock out date in the same month as the stock out date is directly interpolated with the sales volume of the stock out date.
For example, for the season type long-tail article B, the stock out date is 4 months and 1 day, and the sales volume for one non-stock out date in 4 months is 20, so the sales volume for 4 months and 1 day is interpolated to 20.
Specifically, for non-seasonal type conventional goods, because the date with the stock quantity of 0 is determined as the stock out date, when the stock out date is interpolated, the sales volume of any non-stock out date is acquired as a second target sales volume, whether the sales volume of the stock out date is larger than the second target sales volume in the non-stock out date in the shelf loading and unloading time needs to be judged, and if so, the sales volume of the stock out date is recorded; if not, the second target sales amount is interpolated with the sales amount of the backorder date.
The interpolation method of the non-seasonal conventional product is similar to that of the seasonal conventional product, and is not described herein again.
Specifically, in the non-seasonal type long-tail product, since the date when both the stock quantity and the sales volume are 0 is determined as the stock out date, when the stock out date is interpolated, the sales volume of any non-stock out date in the on-and-off shelf time is directly interpolated with the sales volume of the stock out date.
The interpolation mode of the non-seasonal long tail product is similar to that of the seasonal long tail product, and is not described herein again.
After the interpolation of the sales amount of the backorder date, S105 is executed to obtain the historical demand amount of the product based on the sales amount after the interpolation of the backorder date and the sales amount of the non-backorder date.
Before interpolation, the sales amount of the backorder date is unreal, the sales amount of the backorder date is corrected by interpolating the sales amount of the backorder date with the sales amount of the non-backorder date, and the sales amount of the backorder date after interpolation is added with the sales amount of the non-backorder date to obtain the historical demand of the commodity. The authenticity of the historical demand of the commodity is improved, and therefore the prediction accuracy of the future commodity demand is improved.
The following is a classification table of the backorder dates and interpolation schemes for the four categories of products described above:
one or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:
the invention provides a method for restoring historical demand of commodities, which comprises the following steps: the method comprises the steps of determining the category of a commodity based on the historical sales volume condition of the commodity, determining the out-of-stock time of the commodity based on the category, obtaining the sales volume of the commodity on a non-out-of-stock date, interpolating the sales volume of the out-of-stock time based on the sales volume of the non-out-of-stock date, obtaining the historical demand volume of the commodity based on the interpolated sales volume of the out-of-stock date and the sales volume of the non-out-of-stock date, interpolating the sales volume of the out-of-stock date in an interpolation mode to make up the demand loss caused by the shortage of the stock, summing all demands to obtain the historical demand volume of the commodity, restoring the historical demand of the commodity, and providing an accurate basis for prediction of future demands.
Example two
Based on the same inventive concept, an embodiment of the present invention provides an apparatus for restoring historical demand of a commodity, as shown in fig. 2, including:
a first determining module 201, configured to determine a category of a commodity based on a sales volume status of the commodity;
a second determining module 202, configured to determine, based on the category, a backorder date of the item;
the acquisition module 203 is used for acquiring the sales volume of the non-stock-out date of the commodity;
an interpolation module 204, configured to interpolate the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date;
an obtaining module 205, configured to obtain a historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
In an alternative embodiment, the first determining module 201 includes:
the judging unit is used for judging whether the sales volume of the commodity changes seasonally or not;
the first determining unit is used for determining that the commodity is a seasonal commodity if the commodity is a seasonal commodity;
the second determining unit is used for determining that the commodity is a non-seasonal commodity if the commodity is not the seasonal commodity;
the first determining subunit is used for determining that the category of the commodity is a seasonal conventional product when the proportion of the sales days of which the sales volume is 0 in the high sales season is lower than a preset value aiming at the seasonal commodity;
a second determining subunit, configured to determine, for the seasonal commodity, that the category of the commodity is a seasonal long-tail commodity when a percentage of sales days in which the sales volume of the commodity is 0 in the high-sales season is higher than the preset value;
the third determining subunit is used for determining that the category of the commodity is a non-seasonal conventional product when the proportion of the sales days of which the sales volume is 0 to the non-seasonal commodity in the whole year is lower than the preset value;
and the fourth determining subunit is used for determining that the category of the commodity is the non-seasonal long-tail commodity when the proportion of the sales days of which the sales volume is 0 to the non-seasonal commodity in the whole year is higher than the preset value.
In an alternative embodiment, the second determining module 202 includes:
a third determination unit for determining the time for getting on and off the shelf of the commodity;
and the fourth determining unit is used for determining the stock out date of the commodity from the shelf loading and unloading time based on the category.
In an optional implementation, the third determining unit includes:
a fourth determining subunit, configured to determine shelf loading and unloading time of the commodity based on the shelf loading and unloading data when the commodity shelf loading and unloading data exists; or
A first acquisition unit, configured to acquire an initial sales date and an end sales date in historical sales data of the commodity throughout the year when there is no commodity shelving/shelving data;
and the fifth determining subunit is used for determining the time of getting on and off the shelves of the commodities based on the initial sales volume date and the final sales volume date.
In an optional implementation, the fourth determining unit includes:
a sixth determining subunit, configured to determine, from the shelf loading and unloading time, that the date when the stock amount of the commodity is 0 is a stock out date when the category of the commodity is a seasonal regular product or a non-seasonal regular product;
and a seventh determining subunit, configured to determine, from the shelf loading and unloading time, that the date when the stock amount and the sales amount of the commodity are both 0 is the stock out date when the category of the commodity is a seasonal long tail or a non-seasonal long tail.
In an alternative embodiment, the obtaining module 203 includes:
a second acquisition unit configured to acquire a sales amount of a non-stock-out date in the same month as the stock-out date of the commodity when the category of the commodity is a seasonal regular commodity or a seasonal long-tail commodity; or
And the third acquisition unit is used for acquiring the sales volume of the non-shortage dates of the commodities in the shelf loading and unloading time when the categories of the commodities are non-seasonal conventional commodities or non-seasonal long-tailed commodities.
In an alternative embodiment, the inter-cut module 204 includes:
a first interpolation unit, configured to interpolate a sales amount of the out-of-stock date based on a sales amount of a non-out-of-stock date in the same month as the out-of-stock date of the commodity when the category of the commodity is a seasonal regular commodity or a seasonal long-tail commodity;
and a second interpolation unit, configured to interpolate the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date of the commodity in the on-off shelf time when the category of the commodity is a non-seasonal regular commodity or a non-seasonal long-tail commodity.
EXAMPLE III
Based on the same inventive concept, the third embodiment of the present invention provides a computer device, as shown in fig. 3, including a memory 304, a processor 302, and a computer program stored on the memory 304 and executable on the processor 302, where the processor 302 executes the computer program to implement the steps of the method for restoring the historical demand of the commodity.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
Example four
Based on the same inventive concept, a fourth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for restoring the historical demand of the commodity.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the apparatus, computer device, and/or method for restoring historical demand for goods in accordance with embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (10)
1. A method for restoring the historical demand of a commodity is characterized by comprising the following steps:
determining the category of the commodity based on the historical sales condition of the commodity;
determining an out-of-stock date for the item based on the category;
acquiring the sales volume of the non-backorder date of the commodity based on the category;
interpolating the sales of the backorder date based on the sales of the non-backorder date;
and obtaining the historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
2. The method of claim 1, wherein the obtaining a category of the item based on historical sales conditions of the item comprises:
judging whether the sales volume of the commodity changes seasonally or not;
if yes, determining that the commodity is a seasonal commodity;
if not, determining that the commodity is a non-seasonal commodity;
for the seasonal commodities, when the ratio of the sales days of which the sales volume is 0 to the sales days in the busy sales season is lower than a preset value, determining that the category of the commodities is a seasonal conventional product;
for the seasonal commodities, when the percentage of the sales days of which the sales volume is 0 in the high sales season is higher than the preset value, determining that the category of the commodities is a seasonal long-tail commodity;
for non-seasonal commodities, when the proportion of the sales days of which the sales are 0 in the whole year is lower than the preset value, determining that the category of the commodities is non-seasonal conventional commodities;
and for non-seasonal commodities, when the proportion of the sale days of the commodities with the sale of 0 in the whole year is higher than the preset value, determining that the commodities are classified as non-seasonal long-tailed commodities.
3. The method of claim 2, wherein said determining the backorder date of the item based on the category comprises:
determining the time for getting on and off the shelf of the commodity;
determining a backorder date of the goods from the time of getting on and off the shelf based on the category.
4. The method of claim 3, wherein said determining the time to put the item on or off the shelf comprises:
when the commodity shelf loading and unloading data exist, determining the shelf loading and unloading time of the commodity based on the shelf loading and unloading data; or
When the commodity shelf loading and unloading data do not exist, acquiring initial sales volume dates and final sales volume dates in historical sales volume data of the commodities in the whole year;
and determining the time for getting on and off the shelves of the commodity based on the initial sales volume date and the final sales volume date.
5. The method of claim 3, wherein said determining a backorder date for said item from said shelf in time based on said category comprises:
when the category of the commodity is seasonal conventional goods or non-seasonal conventional goods, determining the date when the stock quantity of the commodity is 0 from the shelf loading and unloading time as the out-of-stock date;
and when the category of the commodity is seasonal long-tail products or non-seasonal long-tail products, determining the date when the stock quantity and the sales volume of the commodity are both 0 from the shelf loading and unloading time as the stock out date.
6. The method of claim 5, wherein said obtaining a sales volume for a non-backorder date for the item based on the category comprises:
when the category of the commodity is a seasonal conventional product or a seasonal long-tail product, acquiring the sales volume of a non-backorder date in the same month as the backorder date of the commodity; or
And when the type of the commodity is a non-seasonal conventional product or a non-seasonal long-tail product, acquiring the sales volume of the non-backorder date of the commodity in the shelf loading and unloading time.
7. The method of claim 5, wherein interpolating the backorder date based on the non-backorder date sales comprises:
when the category of the commodity is a seasonal conventional commodity or a seasonal long-tail commodity, interpolating the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date in the same month as the out-of-stock date of the commodity;
and when the type of the commodity is a non-seasonal conventional commodity or a non-seasonal long-tail commodity, interpolating the sales amount of the out-of-stock date based on the sales amount of the non-out-of-stock date of the commodity in the shelf loading and unloading time.
8. An apparatus for restoring a historical demand for a commodity, comprising:
the first determination module is used for determining the category of the commodity based on the sales volume condition of the commodity;
a second determining module for determining the backorder date of the goods based on the category;
the acquisition module is used for acquiring the sales volume of the non-backorder date of the commodity;
the interpolation module is used for interpolating the sales volume of the backorder date based on the sales volume of the non-backorder date;
and the obtaining module is used for obtaining the historical demand of the commodity based on the sales volume after the backorder date interpolation and the sales volume of the non-backorder date.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method steps of any of claims 1-7 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method steps of any one of claims 1 to 7.
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Cited By (1)
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| CN117829740A (en) * | 2024-03-05 | 2024-04-05 | 深圳泽熙网络科技有限公司 | Inventory monitoring method, system, computer equipment and medium |
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