CN110135878A - Method and device for firm sale price - Google Patents
Method and device for firm sale price Download PDFInfo
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Abstract
The application discloses a kind of method and device for firm sale price.It is related to computer information processing field, this method comprises: establishing prediction sales volume model according to the historic sales data of an article, the prediction sales volume model is function relevant to the following article price；Conventional sales volume model is established according to the historic sales data of the article, the routine sales volume model is function relevant to conventional item price；Optimization aim model is determined by the prediction sales volume model and the conventional sales volume model；And the following article price is determined by the optimal solution of the optimization aim model.Method and device disclosed in the present application for firm sale price, can obtain optimal article promotional price, so that the high sales volume of maintenance of the article within the long period.
Description
Technical field
This application involves computer information processing fields, in particular to a kind of method for firm sale price
And device.
Background technique
Existing promotion management system leads to the commodity for being difficult to manage substantial amounts there are great number of issues.It is promotion first
Usually only consider current promotion period, does not account in the influence for adjusting single SKU promotion period to the conventional sales after promotion.
Such as some durable commodity, promoting at a reduced price to some SKU will lead to consumer and largely collects goods in the phase of promoting at a reduced price, cause
Conventional sales sale after promotion sharply declines；If may result in the reduction of macromarketing volume promoting its price reduction excessively.Institute
It needs to optimize from whole with promotion, rather than only considers the sales volume of promotion period.Secondly because its promotional pricing method
It is only cursorily promoted, and is had ignored according to unified discount on the basis of its original cost according to some attributes of SKU
Promotional price is in depth studied to the sale of current promotion phase and the following non-promotion to its historic sales data using analytical technology
The influence of phase sale.
At present for extensive merchandise valuation management, commodity classification method is mainly utilized, the commodity of different classifications are distributed
The different pin personnel that adopt are managed.This mainly using commodity flow by commodity be respectively divided into key commodity with it is non-key
Commodity.To key commodity, it is more that pin personnel are adopted in the price control of distribution；The price control of non-key commodity, distribution is adopted
Pin personnel are fewer.In promotion period, price control adopts pin personnel and usually formulates key commodity the price lower than competitor, to guarantee to obtain
Obtain high sales volume；And maintain original price to non-key commodity, to guarantee to obtain high profit.
Existing extensive promotion all excessively relies on manual control, since SKU quantity is very big, a large amount of manpower is needed to provide
Source.Existing promotion usually only considers a following sales cycle, due to eating effect (such as the consumer of effect across the period
Collect goods behavior), it will cause the weakness of next cycle sale after the promotion in this period.If this period excessively promotes at a low price, though
The sales volume in this right period is very high, but the low profit of current period and next several periods countervail to sell and will cause the low of macromarketing
It produces.In addition, the prior art can not be associated expected promotion dynamics and expected promotion result, lack the assessment side of a system
Case, thus caused by the result is that none accurate inventory planning.For the promotion for preventing promotion bring out of stock, current
Method is usually excessive stock, therefore can generate huge inventory cost.
Therefore, it is necessary to a kind of new method and devices for firm sale price.
Above- mentioned information are only used for reinforcing the understanding to the background of the application, therefore it disclosed in the background technology part
It may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
In view of this, the application provides a kind of method and device for firm sale price, optimal object can be obtained
Product promotional price, so that the high sales volume of maintenance of the article within the long period.
Other characteristics and advantages of the application will be apparent from by the following detailed description, or partially by the application
Practice and acquistion.
According to the one side of the application, a kind of method for firm sale price is proposed, this method comprises: according to an object
The historic sales data of product establishes prediction sales volume model, and the prediction sales volume model is function relevant to the following article price；
Conventional sales volume model is established according to the historic sales data of the article, the routine sales volume model is and conventional item price phase
The function of pass；Optimization aim model is determined by the prediction sales volume model and the conventional sales volume model；And by described
The optimal solution of optimization aim model determines the following items sold price.
In a kind of exemplary embodiment of the disclosure, further includes: items sold data are carried out exceptional value filtering, to obtain
Take historic sales data.
It is described that items sold data are subjected to exceptional value filtering in a kind of exemplary embodiment of the disclosure, to obtain
Historic sales data, comprising: filter out the items sold for causing concluded price decline to be greater than a predetermined threshold due to discount
Data, to obtain the historic sales data.
It is described that items sold data are subjected to exceptional value filtering in a kind of exemplary embodiment of the disclosure, to obtain
Historic sales data, further includes: by robustness regression algorithm, historical data of the residual values outside a preset range is filtered out, with
Obtain the historic sales data.
It is described that prediction sales volume is established according to the historic sales data of an article in a kind of exemplary embodiment of the disclosure
Model, comprising: by ridge regression algorithm and the historic sales data, the Method for Sales Forecast model is established by data fitting；
And by lasso trick regression algorithm and the historic sales data, the Method for Sales Forecast model is established by data fitting.
It is described to pass through the prediction sales volume model and the conventional sales volume mould in a kind of exemplary embodiment of the disclosure
Type determines optimization aim model, comprising:
GMVSUM(xt)=GMVt(xt)+GMVt+1(x0)；
Wherein, GMVSUM(xt) it is the optimization aim model, GMVt(xt) it is the prediction sales volume model, GMVt+1(xt)
For the conventional sales volume model, xtFor the following article price, x0For conventional item price.
In a kind of exemplary embodiment of the disclosure, described in the optimal solution determination by the optimization aim model
The following article price, comprising: the optimal solution of the optimization aim model is sought by Newton Raphson method；And it will be described
Optimal solution determines the following article price.
It is described during seeking the optimal solution of optimization aim model in a kind of exemplary embodiment of the disclosure
The restrictive condition of optimal solution are as follows: the second dervative of the optimal solution is less than or equal to 0.
According to the one side of the application, propose that a kind of device for firm sale price, the device include: prediction sales volume
Module, for establishing prediction sales volume model according to the historic sales data of an article, the prediction sales volume model is and the following object
The relevant function of product price；Conventional sales volume module, for establishing conventional sales volume model according to the historic sales data of the article,
The routine sales volume model is function relevant to conventional item price；Optimization aim module, for passing through the prediction sales volume
Model and the conventional sales volume model determine optimization aim model；And optimal solution module, for passing through the optimization aim mould
The optimal solution of type determines the following items sold price.
In a kind of exemplary embodiment of the disclosure, further includes: data filtering module, for by items sold data into
Row exceptional value filtering, to obtain historic sales data.
According to the one side of the application, a kind of electronic equipment is proposed, which includes: one or more processors；
Storage device, for storing one or more programs；When one or more programs are executed by one or more processors, so that one
A or multiple processors realize such as methodology above.
According to the one side of the application, proposes a kind of computer-readable medium, be stored thereon with computer program, the program
Method as mentioned in the above is realized when being executed by processor.
According to the method and device for firm sale price of the application, optimal article promotional price can be obtained,
So that the high sales volume of maintenance of the article within the long period.
It should be understood that the above general description and the following detailed description are merely exemplary, this can not be limited
Application.
Detailed description of the invention
Its example embodiment is described in detail by referring to accompanying drawing, above and other target, feature and the advantage of the application will
It becomes more fully apparent.Drawings discussed below is only some embodiments of the present application, for the ordinary skill of this field
For personnel, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of system block diagram of method for firm sale price shown according to an exemplary embodiment.
Fig. 2 is a kind of flow chart of method for firm sale price shown according to an exemplary embodiment.
Fig. 3 is a kind of block diagram of device for firm sale price shown according to an exemplary embodiment.
Fig. 4 is the block diagram of a kind of electronic equipment shown according to an exemplary embodiment.
Fig. 5 is that a kind of computer readable storage medium schematic diagram is shown according to an exemplary embodiment.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be real in a variety of forms
It applies, and is not understood as limited to embodiment set forth herein；On the contrary, thesing embodiments are provided so that the application will be comprehensively and complete
It is whole, and the design of example embodiment is comprehensively communicated to those skilled in the art.Identical appended drawing reference indicates in figure
Same or similar part, thus repetition thereof will be omitted.
In addition, described feature, structure or characteristic can be incorporated in one or more implementations in any suitable manner
In example.In the following description, many details are provided to provide and fully understand to embodiments herein.However,
It will be appreciated by persons skilled in the art that the technical solution of the application can be practiced without one or more in specific detail,
Or it can be using other methods, constituent element, device, step etc..In other cases, it is not shown in detail or describes known side
Method, device, realization or operation to avoid fuzzy the application various aspects.
Block diagram shown in the drawings is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or realized in one or more hardware modules or integrated circuit
These functional entitys, or these functional entitys are realized in heterogeneous networks and/or processor device and/or microcontroller device.
Flow chart shown in the drawings is merely illustrative, it is not necessary to including all content and operation/step,
It is not required to execute by described sequence.For example, some operation/steps can also decompose, and some operation/steps can close
And or part merge, therefore the sequence actually executed is possible to change according to the actual situation.
It should be understood that although herein various assemblies may be described using term first, second, third, etc., these groups
Part should not be limited by these terms.These terms are to distinguish a component and another component.Therefore, first group be discussed herein below
Part can be described as the second component without departing from the teaching of disclosure concept.As used herein, term " and/or " include associated
All combinations for listing any of project and one or more.
It will be understood by those skilled in the art that attached drawing is the schematic diagram of example embodiment, module or process in attached drawing
Necessary to not necessarily implementing the application, therefore it cannot be used for the protection scope of limitation the application.
Fig. 1 is a kind of system block diagram of method for firm sale price shown according to an exemplary embodiment.
As shown in Figure 1, system architecture 100 may include terminal device 101,102,103, network 104 and server 105.
Network 104 between terminal device 101,102,103 and server 105 to provide the medium of communication link.Network 104 can be with
Including various connection types, such as wired, wireless communication link or fiber optic cables etc..
User can be used terminal device 101,102,103 and be interacted by network 104 with server 105, to receive or send out
Send message etc..Various telecommunication customer end applications, such as the application of shopping class, net can be installed on terminal device 101,102,103
The application of page browsing device, searching class application, instant messaging tools, mailbox client, social platform software etc..
Terminal device 101,102,103 can be the various electronic equipments with display screen and supported web page browsing, packet
Include but be not limited to smart phone, tablet computer, pocket computer on knee and desktop computer etc..
Server 105 can be to provide the server of various services, such as utilize terminal device 101,102,103 to user
The shopping class website browsed provides the back-stage management server supported.Back-stage management server can believe the product received
The data such as breath purchase carry out the processing such as analyzing, and processing result (such as target push information, Item Information) is fed back to terminal
Equipment.
It should be noted that for carrying out the method for sales volume prediction generally by server provided by the embodiment of the present application
105 execute, and correspondingly, the auto-building html files device of auxiliary user's browsing is generally positioned in client 101.
Fig. 2 is a kind of flow chart of method for firm sale price shown according to an exemplary embodiment.
As shown in Fig. 2, establishing prediction sales volume model, the prediction according to the historic sales data of an article in S202
Sales volume model is function relevant to the following article price.For example, obtaining the historic sales data of an article, the historical sales
Data include article historical price and the sales data corresponding to the historical price.Historical time is divided into different sale
In the period, the future anticipation parameter extracted according to sales cycle can be shown in such as table 1.
| Variable name | Data |
| X5 | Does this sales cycle contain shopping section? |
| X6 | Will lower sales cycle contain shopping section? |
| X7 | Does this sales cycle contain festivals or holidays? |
| X8 | Will lower sales cycle contain festivals or holidays? |
| X9 | Does this sales cycle contain the Spring Festival? |
| Xt | The price of this sales cycle |
By the above parameter and historic sales data, Method for Sales Forecast is established in the way of data fitting by regression algorithm
Model.It can be for example, establishing the Method for Sales Forecast mould by data fitting by ridge regression algorithm and the historic sales data
Type；And by lasso trick regression algorithm and the historic sales data, the Method for Sales Forecast model is established by data fitting.
In some embodiments, ridge regression is a kind of Biased estimator homing method for being exclusively used in the analysis of synteny data, real
It is a kind of least squares estimate of improvement in matter, by abandoning the unbiasedness of least square method, to lose partial information, reduce
Precision is that cost acquisition regression coefficient more meets practical, more reliable homing method, is better than most to the fitting of ill data
Small square law.In this application, it is preferred that using the ridge regression model of penalty coefficient λ=1e-1 as the Method for Sales Forecast mould
Type.
In some embodiments, lasso trick returns the L1 regularization for being sometimes referred to as linear regression, and Lasso recurrence is L1
Regularization.Lasso is returned so that some coefficients become smaller or even the lesser coefficient of some absolute values directly becomes 0, therefore spy
Not Shi Yongyu number of parameters reduction and the selection of parameter, thus be used to estimate the linear model of Sparse parameter.
In S204, conventional sales volume model, the routine sales volume model are established according to the historic sales data of the article
It is function relevant to conventional item price.For example, obtaining the historic sales data of an article, the historic sales data includes
Article historical price and sales data corresponding to the historical price.Historical time is divided into different sales cycles, root
It can be for example shown in table 2 according to the historical forecast parameter that sales cycle extracts.
| Variable name | Data |
| X1 | The sales volume mean value of 5 sales cycles of past |
| X2 | The sales volume of sales cycle last year |
| X3 | The one before month YOY growth rate * same period last year sales volume |
| X4 | Nearest month YOY growth rate * same period last year sales volume |
| Xt-1 | The price of last sales cycle |
Conventional sales volume model is established according to historical forecast parameter.Method for building up can be for example with reference to the content in S204, herein
It repeats no more.
In S206, optimization aim model is determined by the prediction sales volume model and the conventional sales volume model.At this
It is described to determine with the conventional sales volume model by the prediction sales volume model and optimize mesh in a kind of disclosed exemplary embodiment
Mark model, comprising:
GMVSUM(xt)=GMVt(xt)+GMVt+1(x0)；
Wherein, GMVSUM(xt) it is the optimization aim model, GMVt(xt) it is the prediction sales volume model, GMVt+1(xt)
For the conventional sales volume model, xtFor the following article price, x0For conventional item price.
In S208, the following items sold price is determined by the optimal solution of the optimization aim model.In this public affairs
In a kind of exemplary embodiment opened, the optimal solution by the optimization aim model determines the following article price,
It include: the optimal solution that the optimization aim model is sought by Newton Raphson method；And it will be described in optimal solution determination
The following article price.
Wherein, Dun-La Fu Senn process is also known as Newton iteration method (Newton's method), is that newton is proposed in the 17th century
A kind of approximate solution equation in real number field and complex field method.Radical formula is not present in most equations, therefore refinement is true
Root is extremely difficult, or even can not, so that the approximation root for finding equation just seems especially important.Method uses the Thailand of function f (x)
Several are strangled before series to find the root of Equation f (x)=0.Newton iteration method is to seek one of important method of equattion root, most
Big advantage is that nearby have quadratic convergence in the single of Equation f (x)=0, and the method can also be used to seek the repeated root of equation, answer
Root, linear convergence at this time, but superlinear convergence can be become by certain methods.
In some embodiments, during seeking the optimal solution of optimization aim model, the limitation item of the optimal solution
Part are as follows: the second dervative of the optimal solution is less than or equal to 0.
According to the method for firm sale price of the application, promotional price pair is obtained by establishing prediction marketing model
The prediction sales volume answered obtains the corresponding conventional sales amount of regular price by conventional sales model, and then will predict sales volume
Optimal article promotion is obtained by seeking the optimal solution of this objective function as objective function with the summation of conventional sales amount
The mode of price can obtain optimal promotional price so that the high sales volume of maintenance of the article within the long period.
According to the method for firm sale price of the application, the effect of self eating that can prevent promotion from generating is to pin
The negative effect sold, and then more reasonable promotion plan is formulated, realize the improvement of integrated marketing.
According to the method for firm sale price of the application, it can help sales force preferably to the promotion of product
The relationship of phase and conventional sales phase are understood, to provide better data basis to formulate promotion plan.It can be effectively
Human resources are saved, and quickly price adjustment result can be analyzed and summarized.
It will be clearly understood that This application describes how to form and use particular example, but the principle of the application is not limited to
These exemplary any details.On the contrary, the introduction based on present disclosure, these principles can be applied to many other
Embodiment.
In a kind of exemplary embodiment of the disclosure, further includes: items sold data are carried out exceptional value filtering, to obtain
Take historic sales data.It include: the article pin for filtering out and causing concluded price decline to be greater than a predetermined threshold due to discount
Data are sold, to obtain the historic sales data.The historical data is subjected to exceptional value filtering, exceptional value (Outliers) is
Referring to individual values in sample, numerical value deviates considerably from remaining observation of sample belonging to its (or them), also referred to as abnormal data, from
Group's value.In carrying out price-volume relation regression process, the presence of exceptional value can influence the effect of demand function fitting to a certain extent.
Exceptional value filtering principle may be, for example:
1. filtering out the record that discount causes the decline of new deal price to be greater than 50%；
2. carrying out robustness regression (log (sales volume)=log (price)+C), residual error is then weeded out in 2 times of standard deviations of mean value
Except record.Wherein log, which refers to, takes Logarithmic calculation, and C refers to regression constant item.
3. retaining the SKU for being more than 30 sales datas.
In some embodiments, further includes: by robustness regression algorithm, filter out residual values going through outside a preset range
History data, to obtain the historic sales data.Robustness regression (robust regression) is in statistics robust iterative
A kind of method, main thought are to repair the objective function in the classical least square regression very sensitive to exceptional value
Change.Classical least square regression is so that error sum of squares reaches its minimum objective function.Because variance is a unstable statistics
Amount, therefore least square regression is a kind of unstable method.Different objective functions defines different robustness regression methods.Often
The robustness regression method seen has: position square (least median square in minimum；LMS) method, M estimation technique etc., the application is not
As limit.
In some embodiments, whole non-promotional discount variables is indicated with vector x, i.e.,
X=(x1, x2, x3, x4, x5, x6, x7, x8, x9, xt-1, xt)；
Its sales volume discount model of fit are as follows:
WithIndicate regression coefficient vector.
Use xtIndicate the price of following promotion period,Indicate the feature of promotion period, QtIndicate the pre- of promotion period
Survey sales volume.Use x0The original cost of conventional sales phase after expression promotion period,The conventional sales phase after expression promotion period
Feature, Qt+1The prediction sales volume of conventional sales phase after expression promotion period.System receives sale according to obtained fit equation
Enter (GMV) and carries out regression forecasting.
Since decision variable only has (xt), therefore GMV fit equation can simplify for
WhereinSystem
Target be to optimize the GMV summation of promotion period and non-promotion period, therefore the target equation of system is
To GMVSUM(xt) first derivative is sought, system obtains optimal discount levelThe condition that should meet
System obtains optimal discount levelIt should meetSecond dervative condition is
In conjunction with first-order condition as a result, optimal discount levelThe second dervative condition that should meet can abbreviation be
In this application, equation (1) is solved using Newton Raphson method, constraint condition needs to meet equation (2).
The optimal solution sought out can be used as best price.
It will be appreciated by those skilled in the art that realizing that all or part of the steps of above-described embodiment is implemented as being executed by CPU
Computer program.When the computer program is executed by CPU, above-mentioned function defined by the above method provided by the present application is executed
Energy.The program can store in a kind of computer readable storage medium, which can be read-only memory, magnetic
Disk or CD etc..
Further, it should be noted that above-mentioned attached drawing is only the place according to included by the method for the application exemplary embodiment
Reason schematically illustrates, rather than limits purpose.It can be readily appreciated that above-mentioned processing shown in the drawings is not indicated or is limited at these
The time sequencing of reason.In addition, be also easy to understand, these processing, which can be, for example either synchronously or asynchronously to be executed in multiple modules.
Following is the application Installation practice, can be used for executing the application embodiment of the method.It is real for the application device
Undisclosed details in example is applied, the application embodiment of the method is please referred to.
Fig. 3 is a kind of block diagram of device for firm sale price shown according to an exemplary embodiment.For true
The device 30 for determining selling price includes: prediction sales volume module 302, conventional sales volume module 304, optimization aim module 306, optimal solution
Module 308.
Wherein, prediction sales volume module 302 is used to establish prediction sales volume model according to the historic sales data of an article, described
Predict that sales volume model is function relevant to the following article price.For example, obtaining the historic sales data of an article, the history
Sales data includes article historical price and the sales data corresponding to the historical price.Historical time is divided into different
Sales cycle, the future anticipation parameter extracted according to sales cycle.By the above parameter and historic sales data, calculated by returning
Method establishes Method for Sales Forecast model in the way of data fitting.
Conventional sales volume module 304 is used to establish conventional sales volume model according to the historic sales data of the article, described normal
Advising sales volume model is function relevant to conventional item price.For example, obtaining the historic sales data of an article, the history pin
Selling data includes article historical price and the sales data corresponding to the historical price.Historical time is divided into different pins
The period is sold, according to the historical forecast parameter that sales cycle extracts, conventional sales volume model is established according to historical forecast parameter.
Optimization aim module 306 is used to determine optimization aim by the prediction sales volume model and the conventional sales volume model
Model., described that optimization aim model is determined by the prediction sales volume model and the conventional sales volume model, comprising:
GMVSUM(xt)=GMVt(xt)+GMVt+1(x0)；
Wherein, GMVSUM(xt) it is the optimization aim model, GMVt(xt) it is the prediction sales volume model, GMVt+1(xt)
For the conventional sales volume model, xtFor the following article price, x0For conventional item price.
Optimal solution module 308 is used to determine the following article price by the optimal solution of the optimization aim model.Example
Such as, the optimal solution of the optimization aim model is sought by Newton Raphson method；And it is optimal solution determination is described not
Carry out article price.
In a kind of exemplary embodiment of the disclosure, further includes: data filtering module (not shown) is used for object
Product sales data carries out exceptional value filtering, to obtain historic sales data.
According to the device for firm sale price of the application, promotional price pair is obtained by establishing prediction marketing model
The prediction sales volume answered obtains the corresponding conventional sales amount of regular price by conventional sales model, and then will predict sales volume
Optimal article promotion is obtained by seeking the optimal solution of this objective function as objective function with the summation of conventional sales amount
The mode of price can obtain optimal promotional price so that the high sales volume of maintenance of the article within the long period.
Fig. 4 is the block diagram of a kind of electronic equipment shown according to an exemplary embodiment.
The electronic equipment 200 of this embodiment according to the application is described referring to Fig. 4.The electronics that Fig. 4 is shown
Equipment 200 is only an example, should not function to the embodiment of the present application and use scope bring any restrictions.
As shown in figure 4, electronic equipment 200 is showed in the form of universal computing device.The component of electronic equipment 200 can wrap
It includes but is not limited to: at least one processing unit 210, at least one storage unit 220, (including the storage of the different system components of connection
Unit 220 and processing unit 210) bus 230, display unit 240 etc..
Wherein, the storage unit is stored with program code, and said program code can be held by the processing unit 210
Row, so that the processing unit 210 executes described in this specification above-mentioned electronic prescription circulation processing method part according to this
The step of applying for various illustrative embodiments.For example, the processing unit 210 can execute step as shown in Figure 2.
The storage unit 220 may include the readable medium of volatile memory cell form, such as random access memory
Unit (RAM) 2201 and/or cache memory unit 2202 can further include read-only memory unit (ROM) 2203.
The storage unit 220 can also include program/practical work with one group of (at least one) program module 2205
Tool 2204, such program module 2205 includes but is not limited to: operating system, one or more application program, other programs
It may include the realization of network environment in module and program data, each of these examples or certain combination.
Bus 230 can be to indicate one of a few class bus structures or a variety of, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 200 can also be with one or more external equipments 300 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 200 communicate, and/or with make
Any equipment (such as the router, modulation /demodulation that the electronic equipment 200 can be communicated with one or more of the other calculating equipment
Device etc.) communication.This communication can be carried out by input/output (I/O) interface 250.Also, electronic equipment 200 can be with
By network adapter 260 and one or more network (such as local area network (LAN), wide area network (WAN) and/or public network,
Such as internet) communication.Network adapter 260 can be communicated by bus 230 with other modules of electronic equipment 200.It should
Understand, although not shown in the drawings, other hardware and/or software module can be used in conjunction with electronic equipment 200, including but unlimited
In: microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive and number
According to backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server or network equipment etc.) executes the above method according to disclosure embodiment.
Fig. 5 schematically shows a kind of computer readable storage medium schematic diagram in disclosure exemplary embodiment.
Refering to what is shown in Fig. 5, describing the program product for realizing the above method according to presently filed embodiment
500, can using portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as it is run on PC.However, the program product of the application is without being limited thereto, in this document, readable storage medium storing program for executing can be with
To be any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
It is in connection.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include: electrical connection with one or more conducting wires, portable disc, hard disk, random access memory (RAM), read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
The computer readable storage medium may include in a base band or the data as the propagation of carrier wave a part are believed
Number, wherein carrying readable program code.The data-signal of this propagation can take various forms, including but not limited to electromagnetism
Signal, optical signal or above-mentioned any appropriate combination.Readable storage medium storing program for executing can also be any other than readable storage medium storing program for executing
Readable medium, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or
Person's program in connection.The program code for including on readable storage medium storing program for executing can transmit with any suitable medium, packet
Include but be not limited to wireless, wired, optical cable, RF etc. or above-mentioned any appropriate combination.
Can with any combination of one or more programming languages come write for execute the application operation program
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind, including local area network (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
Above-mentioned computer-readable medium carries one or more program, when said one or multiple programs are by one
When the equipment executes, so that the computer-readable medium implements function such as: being established according to the historic sales data of an article pre-
Sales volume model is surveyed, the prediction sales volume model is function relevant to the following article price；According to the historical sales of the article
Data establish conventional sales volume model, and the routine sales volume model is function relevant to conventional item price；Pass through the prediction
Sales volume model and the conventional sales volume model determine optimization aim model；And it is true by the optimal solution of the optimization aim model
The fixed following article price.
It will be appreciated by those skilled in the art that above-mentioned each module can be distributed in device according to the description of embodiment, it can also
Uniquely it is different from one or more devices of the present embodiment with carrying out corresponding change.The module of above-described embodiment can be merged into
One module, can also be further split into multiple submodule.
By the description of above embodiment, those skilled in the art is it can be readily appreciated that example embodiment described herein
It can also be realized in such a way that software is in conjunction with necessary hardware by software realization.Therefore, implemented according to the application
The technical solution of example can be embodied in the form of software products, which can store in a non-volatile memories
In medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) or on network, including some instructions are so that a calculating equipment (can
To be personal computer, server, mobile terminal or network equipment etc.) it executes according to the method for the embodiment of the present application.
It is particularly shown and described the exemplary embodiment of the application above.It should be appreciated that the application is not limited to
Detailed construction, set-up mode or implementation method described herein；On the contrary, it is intended to cover to be included in appended claims
Various modifications and equivalence setting in spirit and scope.
In addition, structure shown by this specification Figure of description, ratio, size etc., only to cooperate specification institute
Disclosure, for skilled in the art realises that be not limited to the enforceable qualifications of the disclosure with reading, therefore
Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the disclosure
Under the technical effect and achieved purpose that can be generated, it should all still fall in technology contents disclosed in the disclosure and obtain and can cover
In the range of.Meanwhile cited such as "upper" in this specification, " first ", " second " and " one " term, be also only and be convenient for
Narration is illustrated, rather than to limit the enforceable range of the disclosure, relativeness is altered or modified, without substantive change
Under technology contents, when being also considered as the enforceable scope of the application.
Claims (12)
1. a kind of method for firm sale price characterized by comprising
Prediction sales volume model is established according to the historic sales data of an article, the prediction sales volume model is and the following article price
Relevant function；
Conventional sales volume model is established according to the historic sales data of the article, the routine sales volume model is sold with conventional item
The relevant function of valence；
Optimization aim model is determined by the prediction sales volume model and the conventional sales volume model；And
The following items sold price is determined by the optimal solution of the optimization aim model.
2. the method as described in claim 1, which is characterized in that further include:
Items sold data are subjected to exceptional value filtering, to obtain historic sales data.
3. method according to claim 2, which is characterized in that it is described that items sold data are subjected to exceptional value filtering, to obtain
Take historic sales data, comprising:
The items sold data for causing concluded price decline to be greater than a predetermined threshold due to discount are filtered out, described in obtaining
Historic sales data.
4. method according to claim 2, which is characterized in that it is described that items sold data are subjected to exceptional value filtering, to obtain
Take historic sales data, further includes:
By robustness regression algorithm, historical data of the residual values outside a preset range is filtered out, to obtain the historical sales
Data.
5. the method as described in claim 1, which is characterized in that described to establish prediction pin according to the historic sales data of an article
Measure model, comprising:
By ridge regression algorithm and the historic sales data, the Method for Sales Forecast model is established by data fitting；And
By lasso trick regression algorithm and the historic sales data, the Method for Sales Forecast model is established by data fitting.
6. the method as described in claim 1, which is characterized in that described to pass through the prediction sales volume model and the conventional sales volume
Model determines optimization aim model, comprising:
GMVSUM(xt)=GMVt(xt)+GMVt+1(x0)；
Wherein, GMVSUM(xt) it is the optimization aim model, GMVt(xt) it is the prediction sales volume model, GMVt+1(xt) it is described
Conventional sales volume model, xtFor the following article price, x0For conventional item price.
7. the method as described in claim 1, which is characterized in that the optimal solution by the optimization aim model determines institute
State the following items sold price, comprising:
The optimal solution of the optimization aim model is sought by Newton Raphson method；And
The optimal solution is determined into the following items sold price.
8. the method for claim 7, which is characterized in that in the process for the optimal solution for seeking the optimization aim model
In, the restrictive condition of the optimal solution are as follows:
The second dervative of the optimal solution is less than or equal to 0.
9. a kind of device for firm sale price characterized by comprising
Sales volume module is predicted, for establishing prediction sales volume model, the prediction sales volume mould according to the historic sales data of an article
Type is function relevant to the following article price；
Conventional sales volume module, for establishing conventional sales volume model, the routine sales volume according to the historic sales data of the article
Model is function relevant to conventional item price；
Optimization aim module, for determining optimization aim model by the prediction sales volume model and the conventional sales volume model；
And
Optimal solution module, for determining the following items sold price by the optimal solution of the optimization aim model.
10. device as claimed in claim 9, which is characterized in that further include:
Data filtering module, for items sold data to be carried out exceptional value filtering, to obtain historic sales data.
11. a kind of electronic equipment characterized by comprising
One or more processors；
Storage device, for storing one or more programs；
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
Now such as method described in any one of claims 1-8.
12. a kind of computer-readable medium, is stored thereon with computer program, which is characterized in that described program is held by processor
Such as method described in any one of claims 1-8 is realized when row.
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