Automatic payment method, device, electronic equipment, medium and product

Abstract

The present application discloses a method, device, electronic device, medium and product for automatic payment, which can be applied to the blockchain field or the financial field. In the method for automatic payment provided by the embodiment of the present application, during the process of executing automatic payment, it can be found whether there is a problem with the first total number of targets used in the first time period to be paid. If there is a problem, the automatic payment is not executed, and the appeal operation is automatically executed. If there is no problem, the automatic payment can be executed. Since the appeal is made immediately and automatically when the problem is found, no human intervention is required, so it is easy to find evidence, saving time in finding evidence. Moreover, in the process of manual appeal, the user needs to find the corresponding appeal interface and fill in the reason, which makes the operation cumbersome. The present application can automatically appeal without human intervention, making the user operation simple.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and more specifically, to methods, devices, electronic equipment, media and products for automatic payment. Background Art

[0002] You can pay for daily expenses on the app, such as water bills, electricity bills, and mobile phone bills. In the process of paying bills, there may be overpayments. For example, in the process of paying water bills, the meter reader may record incorrect numbers on the water meter, resulting in overpayment of water bills.

[0003] If the user has deposited the corresponding amount in his / her payment account in advance, the corresponding payment amount can be directly deducted from the payment account, and the user may not know that he / she has overpaid. By the time the user finds out, it may be a long time, and if he / she files an appeal, it will take a long time to find evidence, or even impossible to find evidence. Summary of the invention

[0004] In view of this, the present application provides a method, device, electronic device, medium and product for automatic payment.

[0005] To achieve the above objectives, this application provides the following technical solutions:

[0006] According to a first aspect of an embodiment of the present disclosure, there is provided a method for automatic payment, comprising:

[0007] Monitoring a payment request, the payment request including a first time period to be paid, a first total amount of an object used in the first time period, and a payment account, the object being electricity, water, or mobile phone charges;

[0008] Obtaining a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper bound and lower bound as the first time period;

[0009] Obtain multiple discrete points by using the first quantity corresponding to each day in the second time period, where the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date;

[0010] Obtaining a regression analysis equation based on the multiple discrete points, wherein the independent variable of the regression analysis equation is the date, and the dependent variable of the regression analysis equation is the first quantity;

[0011] Derivative the regression analysis equation to obtain a growth exponential trend equation;

[0012] For any date in the first time period, the date is substituted into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation;

[0013] For any date in the first time period, the date is substituted into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation;

[0014] For any date in the first time period, determine that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date;

[0015] Determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period;

[0016] Determine the quotient of the total growth amount of the predicted usage target and the total amount of actual usage targets corresponding to the second time period as the expected growth rate;

[0017] Determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period;

[0018] If the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value, executing a complaint operation;

[0019] If the difference between the actual growth rate and the expected growth rate is less than the first preset value, respond to the payment request.

[0020] According to a second aspect of an embodiment of the present disclosure, there is provided an automatic payment device, comprising:

[0021] A monitoring module, configured to monitor a payment request, wherein the payment request includes a first time period to be paid, a first total number of objects used in the first time period, and a payment account, wherein the object is electricity, water, or mobile phone charges;

[0022] A first acquisition module is used to acquire a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper and lower bounds as the first time period;

[0023] A second acquisition module is used to obtain a plurality of discrete points according to the first quantity corresponding to each day in the second time period, wherein the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date;

[0024] A third acquisition module is used to obtain a regression analysis equation based on the multiple discrete points, where the independent variable of the regression analysis equation is the date and the dependent variable of the regression analysis equation is the first quantity;

[0025] A derivation module, used for derivation of the regression analysis equation to obtain a growth exponential trend equation;

[0026] A fourth acquisition module is used to, for any date in the first time period, substitute the date into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation;

[0027] A fifth acquisition module, for any date in the first time period, substituting the date into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation;

[0028] A first determining module, configured to determine, for any date in the first time period, that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date;

[0029] A second determination module is used to determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period;

[0030] A third determination module is used to determine the quotient of the total growth amount of the predicted usage target and the total amount of actual usage targets corresponding to the second time period as the expected growth rate;

[0031] A fourth determining module is used to determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period;

[0032] A first execution module, configured to execute a complaint operation if the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value;

[0033] The second execution module is used to respond to the payment request if the difference between the actual growth rate and the expected growth rate is less than the first preset value.

[0034] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0035] processor;

[0036] a memory for storing instructions executable by the processor;

[0037] The processor is configured to execute the instructions to implement the automatic payment method as described in the first aspect.

[0038] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the automatic payment method as described in the first aspect.

[0039] According to the fifth aspect of the embodiment of the present disclosure, a computer program product is provided, which can be directly loaded into the internal memory of a computer. The memory is the memory included in the electronic device shown in the third aspect and contains software code. After the computer program is loaded and executed, it can implement the automatic payment method as described in the first aspect.

[0040] It can be known from the above technical solution that in the method for automatic payment provided by the embodiment of the present application, during the process of executing automatic payment, it can be found whether there is a problem with the first total number of targets used in the first time period to be paid. If there is a problem, the automatic payment will not be executed, and the appeal operation will be automatically executed. If there is no problem, the automatic payment can be executed. Since the appeal is made immediately and automatically when the problem is found, no human intervention is required, so it is easy to find evidence, saving time in finding evidence. Moreover, in the process of manual appeal, the user needs to find the corresponding appeal interface and fill in the reason, which makes the operation cumbersome. The present application can automatically appeal without human intervention, making the user operation simple. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0042] Figure 1 A schematic diagram of the hardware architecture involved in the embodiments of the present application;

[0043] Figure 2 A flowchart of the automatic payment method provided in the embodiment of the present application;

[0044] Figure 3 A structural diagram of an automatic payment device provided in an embodiment of the present application;

[0045] Figure 4 It is a block diagram showing a device used in an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] The embodiment of the present application provides a method, device, electronic device, medium and product for automatic payment. Before introducing the technical solution provided by the embodiment of the present application, the hardware architecture involved in the embodiment of the present application is first described.

[0048] like Figure 1 FIG. 1 is a schematic diagram of a hardware architecture involved in an embodiment of the present application. The hardware architecture includes: a terminal device 11 and a server 12 .

[0049] Exemplarily, the terminal device 11 may be any electronic product that can perform human-computer interaction with a user through one or more methods such as a keyboard, a touch pad, a touch screen, a remote controller, voice interaction, or a handwriting device, such as a mobile phone, a laptop computer, a tablet computer, a PDA, a personal computer, a wearable device, a smart TV, a PAD, etc. For example, a third-party software is running in the terminal device 11.

[0050] Exemplarily, the server 12 may be a single server, or a server cluster consisting of multiple servers, or a cloud computing server center. The server 12 may include a processor, a memory, a network interface, and the like.

[0051] It should be noted that Figure 1 This is just an example. The terminal device 11 may be of various types, not limited to Figure 1 Smartphone in the.

[0052] A client may be running in the terminal device 11. Exemplarily, the client may be an application client, a web client, or a small program.

[0053] The user can pay for daily living expenses through the client on the terminal device 11.

[0054] In an optional implementation, the terminal device 11 can execute the automatic payment method provided in the embodiment of the present application.

[0055] In an optional implementation, the terminal device 11 sends a payment request to the server 12, and the server 12 executes the automatic payment method provided in the embodiment of the present application.

[0056] Exemplarily, the server 12 may be a server of a bank, or a server of a third party, wherein the third party is a supplier that provides water charges, electricity charges, or call services to users.

[0057] Those skilled in the art should understand that the above-mentioned terminal devices and servers are only examples, and other existing or future terminal devices or servers that are applicable to the present disclosure should also be included in the protection scope of the present disclosure and are included here by reference.

[0058] The following describes the automatic payment method provided in the embodiment of the present application in combination with the above-mentioned hardware architecture.

[0059] like Figure 2 As shown, it is a flow chart of the automatic payment method provided in the embodiment of the present application, and the method can be applied to Figure 1 In the terminal device 11 or server 12 shown, the method involves the following steps S201 to S213 during implementation.

[0060] Step S201: monitoring payment requests, the payment requests including a first time period to be paid, a first total number of objects used in the first time period, and a payment account, the objects being electricity, water, or mobile phone charges.

[0061] In an optional implementation, a payment request may be generated in the following manner.

[0062] The first method: the user clicks a payment button through the client displayed by the terminal device 11 to generate a payment request.

[0063] The second type: the user sets a designated date for payment each month, and if the current time reaches the designated date, a payment request is generated.

[0064] For example, if payment is made on the 11th of every month, a payment request will be generated when the current time reaches the 11th.

[0065] If the present application is applied to the terminal device 11, the payment request can be monitored after the payment request is generated. If the present application is applied to the server 12, the terminal device 11 can send the generated payment request to the server 12, so that the server 12 can monitor the payment request.

[0066] Exemplarily, the first time period is one month, then the first time period is [1st of month n, 31st of month n or 30th of month n or 28th of month n], and the values ​​of n are 1, 2, 3, 4, 56, 7, 8, 9, 10, 11, 12 respectively. If n is 1, 3, 5, 7, 8, 10, 12, the latest date of the first time period is the 31st; if n is 4, 6, 9, 11, the latest date of the first time period is the 30th; if n is 2, the latest date of the first time period is the 28th.

[0067] In the embodiments of the present application, the 1st, 2nd, ..., 31st are referred to as dates; and January, February, March, ..., December are referred to as months.

[0068] Exemplarily, the first time period may be a set time period, for example, [nth month p1, mth month p2], wherein p2 may be greater than, equal to, or less than p1, and m may be greater than or equal to n.

[0069] The length of the set time period can be any number of days.

[0070] The first time period is the time period of the year to which the current time belongs. For example, if the current time is November 10, 2021, the first time period is the time period in 2021.

[0071] Step S202: Obtain a first quantity of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time that has the same upper and lower bounds as the first time period.

[0072] Exemplarily, relative to the year to which the current time belongs, the historical time is last year. For example, if the current time belongs to the year 2021, the historical time is 2020.

[0073] The upper and lower bounds of the first time period are explained below. Assume that the first time period is [October 1, October 31] in 2021, the upper bound of the first time period is October 1, and the lower bound is October 31. Then the second time period is [October 1, October 31] in 2020.

[0074] If the second time period is [October 1st, October 31st] in 2020, the first quantities of usage targets corresponding to each day in the second time period are: the first quantity corresponding to October 1st, 2021, the first quantity corresponding to October 2nd, 2021,…, the first quantity corresponding to October 31st, 2021.

[0075] It is understandable that the usage targets are different in different seasons. Take electricity as an example. For example, air conditioning is used more frequently and for longer periods of time in summer. Therefore, the amount of electricity used in summer is higher than that in spring or autumn. Therefore, it is more accurate to compare the same time periods in different years.

[0076] Step S203: obtaining a plurality of discrete points through the first quantity corresponding to each day in the second time period, wherein the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date.

[0077] Still taking the second time period of [October 1, October 31] in 2020 as an example, 31 discrete points can be obtained. The 31 discrete points are: (No. 1, first quantity 1), (No. 2, first quantity 2), (No. 3, first quantity 3), ..., (No. 31, first quantity 31).

[0078] Step S204: obtaining a regression analysis equation based on the fitting of the multiple discrete points, wherein the independent variable of the regression analysis equation is the date, and the dependent variable of the regression analysis equation is the first quantity.

[0079] In an optional implementation, the implementation of step S204 may include the following steps A1 to A6.

[0080] Step A1: Preliminarily set the regression analysis equation based on the relationship between the dependent variable and the independent variable in multiple discrete points in the coordinate system.

[0081] Exemplarily, the regression analysis equation is a nonlinear regression analysis equation, such as: P0 = A0*t n0 +B0*t+C0*Sin(Q0*t m0 )+d0; where A0, B0, C0, Q0 are equation parameters, n0 and m0 represent equation orders, d0 represents the error caused by other influencing factors, t represents the date, and P0 represents the first quantity.

[0082] Exemplarily, d0 may be a preset value or may be obtained through calculation.

[0083] Exemplarily, the regression analysis equation is a linear regression equation.

[0084] Step A2: Divide the plurality of discrete points into a training set and a test set; the discrete points included in the training set and the test set are different from each other.

[0085] Exemplarily, the discrete points included in the training set and the test set are randomly assigned.

[0086] Step A3: Substitute the multiple discrete points contained in the training set into the regression analysis equation respectively to obtain the coefficients in the regression analysis equation: A0, B0, C0, Q0, n0, m0.

[0087] Exemplarily, if d0 is not preset, it can be calculated through step A3.

[0088] Assume that the training set contains multiple discrete points, namely (t11, first number 11), (t12, first number 12), (t13, first number 13), (t14, first number 14), ... (t1M, first number 1M). M is a positive integer. Then, after substituting multiple discrete points into the above regression analysis equation, the following formula can be obtained. The following nonlinear regression analysis equation is used, such as: P0 = A0*t n0 +B0*t+C0*Sin(Q0*t m0 )+d0 is used as an example for explanation.

[0089]

[0090] Solve the above formula to obtain the coefficients in the regression analysis equation: A0, B0, C0, Q0, n0, m0.

[0091] Step A4: Substitute the horizontal coordinates of the multiple discrete points included in the test set into the regression analysis equation obtained in step A3 to obtain multiple predicted first quantities.

[0092] The nonlinear regression analysis equation is P0=A0*t n0 +B0*t+C0*Sin(Q0*t m0 )+d0 is used as an example. Assume that the test set contains multiple discrete points (t21, first number 21), (t22, first number 22), (t23, first number 23), (t24, first number 24), ... (t2N, first number 2N). N is a positive integer. Then the following formula can be obtained:

[0093]

[0094] Step A5: Obtain an error value based on a plurality of predicted first quantities and a plurality of actual first quantities.

[0095] Exemplarily, the error value g is expressed as variance, then:

[0096] g = (preset first quantity 1 - first quantity 21) 2 +…+(preset first quantity N-first quantity 2N) 2 .

[0097] Step A6: If the error value is less than or equal to the set error threshold, the final regression analysis equation is obtained; otherwise, the plurality of discrete points are randomly re-divided into a training set or a test set to obtain a test set and a training set, and the process returns to step A3.

[0098] Assume that after training, the coefficients of the final regression analysis equation are A0=A, B0=B, C0=C, Q0=Q, n0=n, m0=m, d0=d. Then the final regression analysis equation is: P0=A*t n +B*t+C*Sin(Q*t m )+d.

[0099] Step S205: deriving the regression analysis equation to obtain a growth exponential trend equation.

[0100] For example, if the regression analysis equation is: P0 = A*t n +B*t+C*Sin(Q*t m )+d, and taking its derivative we can get the growth exponential trend equation: P1=A*n*t n-1 +B+Q*C*m*t m-1 *Cos(Q*t m ).

[0101] Step S206: for any date in the first time period, the date is substituted into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation.

[0102] For example, if the first time period includes 10 dates, namely the 1st, 2nd, ..., 10th, then the date is substituted into the regression analysis equation as t to obtain the second quantity corresponding to each date. The nonlinear regression analysis equation is P0 = A*t n +B*t+C*Sin(Q*t m )+d as an example, we can get:

[0103]

[0104] Step S207: For any date in the first time period, the date is substituted into the growth index trend equation to obtain the growth rate of the usage target corresponding to the date output by the growth index trend equation.

[0105] For example, if the first time period includes 10 dates, namely, the 1st, the 2nd, ..., the 10th, then the date is substituted into the growth index trend equation as t to obtain the growth rate corresponding to each date. The growth index trend equation is P1 = A*n*t n-1 +B+Q*C*m*tm-1 *Cos(Q*t m ) as an example, we can get:

[0106]

[0107] Step S208: For any date in the first time period, determine that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date.

[0108] For example, for No. 1 in the first time period, the growth amount = (A*n*1 n-1 +B+Q*C*m*1 m-1 *Cos(Q*1 m ))*(A*1 n +B*1+C*Sin(Q*1 m )+d).

[0109] Step S209: Determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period.

[0110] Step S210: Determine the quotient of the total number of increases in the predicted usage targets and the total number of actual usage targets corresponding to the second time period as the expected growth rate.

[0111] Exemplarily, the total number of actual usage targets corresponding to the second time period is the sum of the first numbers corresponding to each date in the second time period.

[0112] Step S211: Determine the quotient of the first difference and the total number of actual usage targets corresponding to the second time period as the actual growth rate, wherein the first difference is the difference between the first total number and the total number of actual usage targets corresponding to the second time period.

[0113] Step S212: If the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value, a complaint operation is performed.

[0114] Exemplarily, the terminal device may prompt the user whether to file an appeal, and if the user clicks yes, the appeal operation is performed.

[0115] For example, the appeal operation can be directly executed without the user's consent.

[0116] In an optional implementation, the steps of executing the appeal operation include step B1 and step B2.

[0117] Step B1: Generate an appeal request, which includes the payment account, the first time period and the first total amount.

[0118] For example, since the appeal request is automatically generated, there is no need to manually add the reason for the appeal and the corresponding information.

[0119] Exemplarily, the complaint request may also include pictures, videos or texts, which may be automatically collected by the terminal device.

[0120] Step B2: Send the appeal request to a third-party server, which is the supplier of the target.

[0121] Step S213: If the difference between the actual growth rate and the expected growth rate is less than the first preset value, respond to the payment request.

[0122] Exemplarily, responding to the payment request is sending the payment request to a server of a bank.

[0123] Exemplarily, responding to the payment request is sending the payment request to a server of a third party, where the third party is the target supplier.

[0124] In the method for automatic payment provided in the embodiment of the present application, during the process of automatic payment, it can be found whether there is a problem with the first total number of targets used in the first time period to be paid. If there is a problem, the automatic payment will not be performed, and the appeal operation will be automatically performed. If there is no problem, the automatic payment can be performed. Since the appeal is automatically made immediately when a problem is found, no human intervention is required, so it is easy to find evidence, saving time in finding evidence. Moreover, in the process of manual appeal, the user needs to find the corresponding appeal interface and fill in the reason, which makes the operation cumbersome. The present application can automatically appeal without human intervention, making the user operation simple.

[0125] In an optional implementation, before executing step S203, it also includes: if the quotient of the second difference and the total number of actual usage targets corresponding to the second time period is greater than or equal to a second preset value, executing step S203; the second difference is the difference between the first total number and the total number of actual usage targets corresponding to the second time period.

[0126] It is understandable that if the first total quantity corresponding to the first time period is ridiculously higher than the total quantity of the actual usage target corresponding to the second time period, it can be directly determined based on the above steps that there is a problem with the first total quantity without going through steps S203 to S212. This can speed up the determination of whether there is a problem with the first total quantity.

[0127] In an optional implementation, there are multiple implementations of responding to a payment request, and the embodiments of the present application provide but are not limited to the following two.

[0128] The first implementation method of responding to a payment request includes steps C1 and C2.

[0129] Step C1: deducting a first amount from a bank card associated with the payment account or a pre-stored balance, where the first amount is obtained based on the first total amount.

[0130] It is understandable that the user can store money in the payment account.

[0131] Exemplarily, the first amount=the first total quantity*the unit price of the target.

[0132] Step C2: At the end of the day or after a set time, the first amount will be added to the bank card associated with the third party, and the third party is the supplier of the target.

[0133] It is understandable that the above steps C1 to C2 can be executed by the bank's server.

[0134] Since it involves transfers between bank cards, it needs to be executed by the bank's server. It is understandable that since there may be many users paying third parties, it needs to be processed uniformly at the end of the day or after a set time, that is, reconciliation. This has the problem of delayed charging.

[0135] It is understandable that for each user, when the user pays a third party, real-time transfer processing can also be performed, but this consumes computing resources of the server and increases the difficulty of subsequent reconciliation. In view of this, the embodiment of the present application provides a second method.

[0136] The second implementation method of responding to the payment request includes steps D1 and D2.

[0137] Step D1: deducting a first amount of digital currency from the digital currency corresponding to the payment account, where the first amount is obtained based on the first total amount.

[0138] Exemplarily, first quantity = first total quantity * unit price of target / unit price of digital currency

[0139] Step D2: Add the first amount of digital currency to a third-party account, where the third-party account is an account of the supplier of the target.

[0140] Exemplarily, the third-party account may be a digital currency wallet account.

[0141] The addition and subtraction of digital currency does not need to go through the bank's server. It only involves the payment account and the third-party account. The bank's server does not need to be involved, so it can be done in real time. There is no problem of delayed charging, nor is there a problem of consuming the computing resources of the bank's server.

[0142] In an optional implementation, the embodiment of the present application can also be combined with the blockchain to store all information in the payment process on the blockchain.

[0143] The method is described in detail in the embodiments disclosed in the above-mentioned application. The method of the application can be implemented by various forms of devices. Therefore, the application also discloses a device, and a specific embodiment is given below for detailed description.

[0144] like Figure 3 As shown, it is a structural diagram of the automatic payment device provided in an embodiment of the present application, and the device includes: a monitoring module 301, a first acquisition module 302, a second acquisition module 303, a third acquisition module 304, a derivation module 305, a fourth acquisition module 306, a fifth acquisition module 307, a first determination module 308, a second determination module 309, a third determination module 310, a fourth determination module 311, a first execution module 312 and a second execution module 313, wherein:

[0145] Monitoring module 301, used to monitor payment request, the payment request includes a first time period to be paid, a first total number of objects used in the first time period and a payment account, the object being electricity or water or mobile phone charges;

[0146] A first acquisition module 302 is used to acquire a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper and lower bounds as the first time period;

[0147] A second acquisition module 303 is used to obtain a plurality of discrete points according to the first quantity corresponding to each day in the second time period, wherein the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date;

[0148] A third acquisition module 304 is configured to obtain a regression analysis equation based on the plurality of discrete points, wherein the independent variable of the regression analysis equation is the date, and the dependent variable of the regression analysis equation is the first quantity;

[0149] A derivation module 305 is used to derive the regression analysis equation to obtain a growth exponential trend equation;

[0150] A fourth acquisition module 306 is used to, for any date in the first time period, substitute the date into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation;

[0151] A fifth acquisition module 307 is used to substitute any date in the first time period into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation;

[0152] A first determining module 308 is configured to determine, for any date in the first time period, that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date;

[0153] The second determination module 309 is used to determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period;

[0154] The third determination module 310 is used to determine the quotient of the total number of growth of the predicted usage target and the total number of actual usage targets corresponding to the second time period as the expected growth rate;

[0155] A fourth determining module 311 is used to determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period;

[0156] A first execution module 312, configured to execute a complaint operation if the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value;

[0157] The second execution module 313 is used to respond to the payment request if the difference between the actual growth rate and the expected growth rate is less than the first preset value.

[0158] In an optional implementation, the method further includes:

[0159] A trigger module is used to trigger the second acquisition module if the quotient of the second difference and the total number of actual usage targets corresponding to the second time period is greater than or equal to a second preset value; the second difference is the difference between the first total number and the total number of actual usage targets corresponding to the second time period.

[0160] In an optional implementation, the second execution module includes:

[0161] a deduction unit, configured to deduct a first amount of digital currency from the digital currency corresponding to the payment account, wherein the first amount is obtained based on the first total amount;

[0162] An adding unit is used to add the first amount of digital currency to a third-party account, and the third-party account is an account of a supplier of the target.

[0163] In an optional implementation, the first execution module includes:

[0164] a generating unit, configured to generate an appeal request, wherein the appeal request includes the payment account, the first time period, and the first total amount;

[0165] A sending unit is used to send the appeal request to a third-party server, where the third-party server is the supplier of the target.

[0166] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0167] Figure 4 1 is a block diagram of a device for an electronic device according to an exemplary embodiment. The electronic device may be a terminal device 11 or a server 12.

[0168] The electronic device includes, but is not limited to, a processor 41 , a memory 42 , a network interface 43 , an I / O controller 44 , and a communication bus 45 .

[0169] It should be noted that those skilled in the art can understand that Figure 4 The structure of the electronic device shown in the figure does not constitute a limitation on the electronic device, and the electronic device may include Figure 4 More or fewer components may be shown, or certain components may be combined, or the components may be arranged differently.

[0170] Combine the following Figure 4 A detailed introduction to the various components of electronic equipment:

[0171] The processor 41 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 42, and calling data stored in the memory 42, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. The processor 41 may include one or more processing units; illustratively, the processor 41 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 41.

[0172] The processor 41 may be a central processing unit (CPU), or an application specific integrated circuit ASIC (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention;

[0173] The memory 42 may include a memory, such as a high-speed random access memory (RAM) 421 and a read-only memory (ROM) 422, and may also include a large-capacity storage device 423, such as at least one disk storage, etc. Of course, the electronic device may also include hardware required for other services.

[0174] The memory 42 is used to store instructions executable by the processor 41. The processor 41 has the following functions:

[0175] Monitoring a payment request, the payment request including a first time period to be paid, a first total amount of an object used in the first time period, and a payment account, the object being electricity, water, or mobile phone charges;

[0176] Obtaining a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper bound and lower bound as the first time period;

[0177] Obtain multiple discrete points by using the first quantity corresponding to each day in the second time period, where the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date;

[0178] Obtaining a regression analysis equation based on the multiple discrete points, wherein the independent variable of the regression analysis equation is the date, and the dependent variable of the regression analysis equation is the first quantity;

[0179] Derivative the regression analysis equation to obtain a growth exponential trend equation;

[0180] For any date in the first time period, the date is substituted into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation;

[0181] For any date in the first time period, the date is substituted into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation;

[0182] For any date in the first time period, determine that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date;

[0183] Determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period;

[0184] Determine the quotient of the total growth amount of the predicted usage target and the total amount of actual usage targets corresponding to the second time period as the expected growth rate;

[0185] Determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period;

[0186] If the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value, executing a complaint operation;

[0187] If the difference between the actual growth rate and the expected growth rate is less than the first preset value, respond to the payment request.

[0188] A wired or wireless network interface 43 is configured to connect the electronic device to a network.

[0189] The processor 41, the memory 42, the network interface 43 and the I / O controller 44 may be interconnected via a communication bus 45, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.

[0190] In an exemplary embodiment, the electronic device may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned method of automatic payment between knowledge points.

[0191] In an exemplary embodiment, the present disclosure provides a storage medium including instructions, such as a memory 42 including instructions, and the instructions can be executed by a processor 41 of an electronic device to complete the above method. Optionally, the storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0192] In an exemplary embodiment, a computer-readable storage medium is also provided, which can be directly loaded into the internal memory of a computer, such as the above-mentioned memory 42, and contains software code. After being loaded and executed by a computer, the computer program can implement the steps shown in any embodiment of the above-mentioned automatic payment method.

[0193] In an exemplary embodiment, a computer program product is also provided, which can be directly loaded into the internal memory of a computer, such as the memory contained in the electronic device, and contains software code. After being loaded and executed by the computer, the computer program can implement the steps shown in any embodiment of the automatic payment method described above.

[0194] It should be noted that the automatic payment method, device, electronic device, medium and product provided by the present invention can be used in the blockchain field or the financial field. The above is only an example and does not limit the application field of the automatic payment method, device, electronic device, medium and product provided by the present invention.

[0195] It should be noted that the features described in the various embodiments in this specification can be replaced or combined with each other. For the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0196] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0197] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0198] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for automatic payment, characterized in that: include: Monitoring a payment request, the payment request including a first time period to be paid, a first total amount of an object used in the first time period, and a payment account, the object being electricity, water, or mobile phone charges; Obtaining a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper bound and lower bound as the first time period; Obtain multiple discrete points by using the first quantity corresponding to each day in the second time period, where the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date; Obtaining a regression analysis equation based on the multiple discrete points, wherein the independent variable of the regression analysis equation is the date, and the dependent variable of the regression analysis equation is the first quantity; Derivative the regression analysis equation to obtain a growth exponential trend equation; For any date in the first time period, the date is substituted into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation; For any date in the first time period, the date is substituted into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation; For any date in the first time period, determine that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date; Determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period; Determine the quotient of the total growth amount of the predicted usage target and the total amount of actual usage targets corresponding to the second time period as the expected growth rate; Determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period; If the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value, executing a complaint operation; If the difference between the actual growth rate and the expected growth rate is less than the first preset value, respond to the payment request.

2. The method for automatic payment according to claim 1, characterized in that: Also includes: If the quotient of the second difference and the total number of actual usage targets corresponding to the second time period is greater than or equal to a second preset value, the step of obtaining a plurality of discrete points by using the first numbers corresponding to each day in the second time period is performed; The second difference is a difference between the first total quantity and the total quantity of actually used targets corresponding to the second time period.

3. The automatic payment method according to claim 1 or 2, characterized in that: The responding to the payment request comprises: deducting a first amount of digital currency from the digital currency corresponding to the payment account, where the first amount is obtained based on the first total amount; The first amount of digital currency is increased in a third-party account, where the third-party account is an account of a supplier of the target.

4. The automatic payment method according to claim 1 or 2, characterized in that: The steps for executing the appeal operation include: generating an appeal request, wherein the appeal request includes the payment account, the first time period, and the first total amount; The appeal request is sent to a third-party server, where the third-party server is a supplier of the target.

5. An automatic payment device, characterized in that: include: A monitoring module, configured to monitor a payment request, wherein the payment request includes a first time period to be paid, a first total number of objects used in the first time period, and a payment account, wherein the object is electricity, water, or mobile phone charges; A first acquisition module is used to acquire a first number of usage targets corresponding to each day in a second time period; the second time period is a time period in historical time having the same upper and lower bounds as the first time period; A second acquisition module is used to obtain a plurality of discrete points according to the first quantity corresponding to each day in the second time period, wherein the ordinate of the discrete point is the first quantity and the abscissa of the discrete point is the date; A third acquisition module is used to obtain a regression analysis equation based on the multiple discrete points, where the independent variable of the regression analysis equation is the date and the dependent variable of the regression analysis equation is the first quantity; A derivation module, used for derivation of the regression analysis equation to obtain a growth exponential trend equation; A fourth acquisition module is used to, for any date in the first time period, substitute the date into the regression analysis equation to obtain a second number of predicted usage targets corresponding to the date output by the regression analysis equation; A fifth acquisition module, for any date in the first time period, substituting the date into the growth index trend equation to obtain a growth rate of the usage target corresponding to the date output by the growth index trend equation; A first determining module, configured to determine, for any date in the first time period, that the product of the second quantity corresponding to the date and the growth rate corresponding to the date is the growth amount of the usage target corresponding to the date; A second determination module is used to determine the sum of the growth amounts of the usage targets corresponding to the respective dates in the first time period as the total growth amount of the predicted usage targets corresponding to the first time period; A third determination module is used to determine the quotient of the total growth amount of the predicted usage target and the total amount of actual usage targets corresponding to the second time period as the expected growth rate; A fourth determining module is used to determine a quotient of a first difference and a total number of actual usage targets corresponding to the second time period as an actual growth rate, wherein the first difference is a difference between the first total number and the total number of actual usage targets corresponding to the second time period; A first execution module, configured to execute a complaint operation if the difference between the actual growth rate and the expected growth rate is greater than or equal to a first preset value; The second execution module is used to respond to the payment request if the difference between the actual growth rate and the expected growth rate is less than the first preset value.

6. The automatic payment device according to claim 5, characterized in that: Also includes: A triggering module, configured to trigger the second acquisition module if a quotient of the second difference and the total number of actual usage targets corresponding to the second time period is greater than or equal to a second preset value; The second difference is a difference between the first total quantity and the total quantity of actually used targets corresponding to the second time period.

7. The automatic payment device according to claim 5 or 6, characterized in that: The second execution module includes: a deduction unit, configured to deduct a first amount of digital currency from the digital currency corresponding to the payment account, wherein the first amount is obtained based on the first total amount; An adding unit is used to add the first amount of digital currency to a third-party account, and the third-party account is an account of a supplier of the target.

8. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the automatic payment method as described in any one of claims 1 to 4.

9. A computer-readable storage medium, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the automatic payment method as described in any one of claims 1 to 4.

10. A computer program product that can be directly loaded into the internal memory of a computer, wherein the memory is the memory contained in the electronic device described in claim 8 and contains software code. After being loaded and executed by the computer, the computer program can implement the automatic payment method described in any one of claims 1 to 4.

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