CN111754327B - Queuing prompt method and device - Google Patents
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- CN111754327B CN111754327B CN202010589870.2A CN202010589870A CN111754327B CN 111754327 B CN111754327 B CN 111754327B CN 202010589870 A CN202010589870 A CN 202010589870A CN 111754327 B CN111754327 B CN 111754327B
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Abstract
The invention provides a queuing prompt method and a queuing prompt device, wherein the method comprises the following steps: responding to the prediction instruction, determining the current banknote residual amount of the self-service cash withdrawal equipment, and acquiring user information of queuing users in a queuing area; judging whether a target queuing user exists in the queuing area; if yes, generating a feature vector of each target queuing user; identifying the feature vector by applying a withdrawal amount prediction model corresponding to the target queuing user to obtain a first estimated withdrawal amount of the target queuing user; obtaining a predicted withdrawal amount sum based on each first predicted withdrawal amount and a second predicted withdrawal amount of the non-target queuing user; judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote; if yes, determining the number of estimated service clients; and sending the estimated service client number to a user terminal of the target queuing user so as to complete queuing prompt. By applying the method provided by the invention, queuing prompt can be timely sent to the user.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a queuing prompt method and a queuing prompt device.
Background
Along with the development of science and technology, self-service also becomes a research hotspot of each bank, and each bank website is in order to meet the demands of clients, saves human resources, and is additionally provided with a self-service withdrawal device, so that the self-service withdrawal device is convenient to operate and withdraw money conveniently, and brings great convenience to the life of people.
However, the number of banknotes stored in the banknote cassettes of the self-service cash dispenser is limited, so that after a user spends a lot of time and effort to queue, the situation that the user cannot withdraw money due to insufficient number of banknotes in the banknote cassettes often occurs, and experience brought to the user is poor.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a queuing prompt method which can timely send out queuing prompts for queuing users so as to avoid the situation that the users cannot withdraw money due to insufficient banknote quantity of banknote boxes after spending a great amount of time and energy for queuing.
The invention also provides a queuing prompt device which is used for ensuring the realization and the application of the method in practice.
A queuing prompt method, comprising:
responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user;
Judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor;
identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user;
obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote;
If the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount;
and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users.
The method, optionally, the determining the current banknote remaining amount of the self-service cash dispenser corresponding to the prediction instruction includes:
analyzing the predicted instruction to obtain instruction information of the predicted instruction;
determining self-service withdrawal equipment corresponding to the predicted instruction based on the instruction information;
acquiring service flow information of the self-service withdrawal device;
and obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
In the above method, optionally, the determining the estimated service client number based on the first estimated withdrawal amount, the second estimated withdrawal amount, and the remaining amount of the banknote includes:
calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
And determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknote.
The method, optionally, wherein the sending the estimated service client number to each target queuing user includes:
determining a prompting mode corresponding to each target queuing user;
and sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
The method, optionally, after determining that the sum of the estimated withdrawal amounts is greater than the remaining amount of the banknote, further includes:
generating a banknote distribution task message based on the sum of the estimated withdrawal amounts and the residual banknote amount;
sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
A queuing prompt device, comprising:
the processing unit is used for responding to the prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on the bank cards of all queuing users in the queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain the user information of each queuing user;
A first judging unit, configured to judge whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
the first determining unit is used for determining a current withdrawal amount influence factor if the target queuing user exists in the queuing area, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor;
the recognition unit is used for recognizing the characteristic vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user;
the calculating unit is used for obtaining the sum of the estimated withdrawal amounts based on the first estimated withdrawal amounts and the second estimated withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
The second judging unit is used for judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote;
the second determining unit is used for determining the estimated service customer number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount if the estimated withdrawal amount sum is larger than the banknote remaining amount;
and the prompting unit is used for sending the estimated service client number to the user terminals of the target queuing users so as to finish queuing prompt of the target queuing users.
The above apparatus, optionally, the processing unit includes:
the analysis subunit is used for analyzing the prediction instruction to obtain instruction information of the prediction instruction;
the first determining subunit is used for determining the self-service withdrawal equipment corresponding to the prediction instruction based on the instruction information;
the acquisition subunit is used for acquiring the service flow information of the self-service withdrawal equipment;
and the processing subunit is used for obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
The above apparatus, optionally, the second determining unit includes:
The calculating subunit is used for calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
and the second determination subunit is used for determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknotes.
The above device, optionally, the prompting unit includes:
a third determining subunit, configured to determine a prompting mode corresponding to each target queuing user;
and the sending subunit is used for sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
The above device, optionally, further comprises: a transmitting unit;
the sending unit is used for generating a banknote distribution task message based on the estimated withdrawal sum and the banknote residual amount; sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
Compared with the prior art, the invention has the following advantages:
the invention provides a queuing prompt method and a queuing prompt device, wherein the method comprises the following steps: responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user; judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction; if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor; identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user; obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs; judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote; if the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount; and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users. The queuing prompt can be timely sent out for queuing users, so that the situation that the users cannot withdraw money due to insufficient quantity of the banknotes in the banknote box after the users spend a great deal of time and energy for queuing is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a queuing prompt method provided by the invention;
FIG. 2 is a flowchart of a queuing prompt method according to another embodiment of the present invention;
FIG. 3 is a diagram illustrating an exemplary implementation scenario provided by the present invention;
fig. 4 is a schematic structural diagram of a queuing prompt device provided by the invention;
fig. 5 is a schematic structural diagram of an electronic device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is operational with numerous general purpose or special purpose computing device environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor devices, distributed computing environments that include any of the above devices or devices, and the like.
The embodiment of the invention provides a queuing prompt method which can be applied to various system platforms, an execution subject of the queuing prompt method can be a processor of a computer terminal or various mobile devices, and a flow chart of the queuing prompt method is shown in fig. 1, and specifically comprises the following steps:
s101: responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user.
In the method provided by the embodiment of the invention, the prediction instruction can be sent when the ATM finishes the money withdrawing task of the user each time.
The banknote surplus amount of the self-service cash dispenser can be determined according to the business flow records of the self-service cash dispenser.
Specifically, a radio frequency chip is preset in the bank card, and radio frequency scanning is performed on the queuing area through radio frequency signal receiving equipment, so that the banks of all queuing users in the queuing area can be subjected to radio frequency identification, and user information of each queuing user is read.
Optionally, the user information may include information such as an identification of the user and a bank card account number, and the user information may further include a history withdrawal record and the like.
And presetting a corresponding withdrawal amount prediction model for each queuing user.
S102: judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction.
In the method provided by the embodiment of the invention, whether the queuing area contains the target queuing user can be judged based on the preset prompt record file.
The prompting time range is composed of a time point represented by the time stamp information and a previous time point of the time point, the duration of the prompting time range is not limited and can be any duration, for example, 3 minutes, 5 minutes, 10 minutes, 15 minutes and the like, and the prompting time range is specifically set by a technician according to actual requirements, and the time stamp information can be generated when the self-service withdrawal device completes a withdrawal task of a user.
Specifically, the user identification of each queuing user can be obtained from the user information of each queuing user, each prompting record in the prompting time range of the self-service withdrawal device is queried in the prompting record file, if the prompting record corresponding to the user identification does not exist, the queuing user to which the user identification belongs is the target queuing user, if the prompting record corresponding to the user identification exists, the fact that the prompting message is sent to the queuing user in the prompting time range is indicated, and for the queuing user with the prompting record, prompting is not needed in a short time.
Alternatively, if it is determined that the target queuing user does not exist in the queuing area, the flow may be ended.
S103: and if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on the user information of each target queuing user and the withdrawal amount influence factor.
In the method provided by the embodiment of the invention, the withdrawal amount influence factor can comprise current time information, current weather information and the like, and the feature vector of the target queuing user can be obtained based on the user information and the withdrawal amount influence factor.
One way to generate the feature vector of the target queuing user may be: if the user information contains the historical withdrawal record of the target queuing user, preprocessing is carried out based on the historical withdrawal record and the withdrawal amount influence factor to obtain a feature vector of the target queuing user, if the user information does not contain the historical withdrawal record of the target queuing user, a service running list of the target user can be obtained based on a user identification in the user information, the historical withdrawal record of the target queuing user is extracted from the service running list, and then preprocessing is carried out on the historical withdrawal record and the withdrawal amount influence factor to obtain the feature vector of the target queuing user.
S104: and identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user.
In the method provided by the embodiment of the invention, the withdrawal amount prediction model corresponding to each target queuing user is preset.
The process of setting the withdrawal amount prediction model for each target queuing user can be as follows: acquiring a training sample set corresponding to the target queuing user; the training sample set comprises a plurality of training samples; training an initial model to be trained by using training samples in a training sample set to obtain a reserve selection money amount prediction model; acquiring a test sample set, and determining the prediction accuracy of the alternative money amount prediction model based on the test sample set; judging whether the prediction accuracy is larger than a preset accuracy threshold; if the prediction accuracy is greater than the accuracy threshold, determining the withdrawal amount prediction model as a withdrawal amount prediction model, and if the prediction accuracy is not greater than the accuracy threshold, returning to the step of acquiring the training sample set of the target queuing user.
Specifically, the training sample may be a historical withdrawal record of the target queuing user, and the initial model may be a GA-BP neural network model, that is, the withdrawal amount prediction model of the target queuing user may be a GA-BP neural network model that has been trained in advance.
Optionally, the GA-BP neural network model may include a three-layer structure, that is, an input layer, a hidden layer, and an output layer, where the number of nodes in the hidden layer may be determined by using a real-time method, and the withdrawal amount prediction model may be continuously self-optimized according to a use result in a use process, that is, the withdrawal amount prediction model may be optimized by a degree of difference between an estimated withdrawal amount of a target queuing user and an actual withdrawal amount of the target queuing user.
S105: obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
in the method provided by the embodiment of the invention, the first estimated withdrawal amount and the second estimated withdrawal amount can be summed to obtain the sum of the estimated withdrawal amounts.
S106: and judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote.
In the method provided by the embodiment of the invention, the sum of the withdrawal amount is compared with the residual amount of the banknote, so that whether the estimated withdrawal amount is larger than the residual amount of the banknote can be judged.
Optionally, if the sum of the estimated withdrawal amounts is not greater than the remaining amount of the banknote, it is indicated that the remaining amount of the banknote may satisfy the requirements of each queuing user in the current queuing area.
S107: and if the estimated withdrawal amount sum is larger than the residual amount of the banknotes, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the residual amount of the banknotes.
In the method provided by the embodiment of the invention, the first estimated withdrawal amount, the second estimated withdrawal amount and the residual amount of the banknote can be substituted into a preset calculation formula to obtain the estimated service client number.
S108: and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users.
In the method provided by the embodiment of the invention, the estimated service client number is sent to the target queuing user, so that when the target queuing user obtains the estimated service client number, whether the risk of being unable to finish withdrawal exists currently or not can be determined according to the estimated service client number and the current queuing position of the estimated service client number.
The queuing prompt method provided by the embodiment of the invention comprises the following steps: responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user; judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction; if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor; identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user; obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs; judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote; if the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount; and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users. The queuing prompt can be timely sent out for queuing users, so that the situation that the users cannot withdraw money due to insufficient quantity of the banknotes in the banknote box after the users spend a great deal of time and energy for queuing is avoided.
In the method provided by the embodiment of the present invention, based on the implementation process, specifically, the process of determining the current remaining amount of the banknote of the self-service teller machine corresponding to the prediction instruction, as shown in fig. 2, may include:
s201: analyzing the predicted instruction to obtain instruction information of the predicted instruction.
In the method provided by the embodiment of the invention, the instruction information can comprise the identification of the ATM, the timestamp information and the like.
S202: and determining the self-service withdrawal equipment corresponding to the predicted instruction based on the instruction information.
In the method provided by the embodiment of the invention, the self-service withdrawal device corresponding to the prediction instruction can be determined based on the self-service withdrawal device identification in the instruction information, and the self-service withdrawal device identification corresponds to the self-service withdrawal device.
S203: and acquiring service flow information of the self-service withdrawal device.
According to the method provided by the embodiment of the invention, the business flow of the self-service withdrawal device comprises the business handled by each user in the self-service withdrawal device, and also comprises the currency flow condition of the currency box of the self-service withdrawal device and the like.
S204: and obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
According to the method provided by the embodiment of the invention, the current banknote remaining amount of the self-service cash dispensing equipment can be obtained by the banknote box quota in the service flow information, the total monetary deposit amount and the total monetary outflow amount of the self-service cash dispensing equipment.
In the method provided by the embodiment of the present invention, based on the implementation process, specifically, based on each of the first estimated withdrawal amount, each of the second estimated withdrawal amount, and the remaining amount of the banknote, determining the estimated service client number includes:
calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
and determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknote.
In the method provided by the embodiment of the invention, one feasible way for obtaining the average estimated withdrawal amount can be as follows: summing the first estimated withdrawal amount and the second estimated withdrawal amount to obtain an estimated withdrawal amount sum, and obtaining an average estimated withdrawal amount based on the estimated withdrawal amount sum and the number of queuing users in the queuing area, wherein the average estimated withdrawal amount is the average estimated withdrawal amount of each queuing user in the queuing area.
Wherein the estimated service customer number can be obtained by dividing the remaining amount of the banknote by the average estimated withdrawal amount.
In the method provided by the embodiment of the present invention, based on the implementation process, specifically, the sending the estimated service client number to each target queuing user includes:
determining a prompting mode corresponding to each target queuing user;
and sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
In the method provided by the embodiment of the invention, the prompting mode of the target queuing user can be short message prompting or application message pushing prompting.
Whether terminal equipment corresponding to each target queuing user runs a preset application program can be judged, for the target queuing user of which the terminal equipment runs the application program, a prompt mode corresponding to the target queuing user is determined to push a prompt for an application message, and for the target queuing user of which the terminal equipment does not run the application program, a prompt mode corresponding to the target queuing user is determined to prompt for a short message.
In the method provided by the embodiment of the present invention, based on the implementation process, specifically, after determining that the sum of the estimated withdrawal amounts is greater than the remaining amount of the banknote, the method further includes:
Generating a banknote distribution task message based on the sum of the estimated withdrawal amounts and the residual banknote amount;
sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
In the method provided by the embodiment of the invention, the minimum money distribution amount currently required by the self-service money withdrawing equipment can be determined based on the current estimated total money withdrawal amount and the money distribution residual amount, the minimum money distribution amount is filled into a preset message template to obtain a money distribution task message, and the money distribution task message is sent to a preset money distribution task system, so that the money distribution task system generates a money distribution task corresponding to the money distribution task message, and reminds a money distribution person corresponding to the self-service money withdrawing equipment to execute the money distribution task.
Referring to fig. 3, an exemplary diagram of an implementation scenario provided by the present invention includes a banking server 301, an self-service teller machine 302, a user terminal 303 of each target queuing user in a queuing area of the self-service teller machine, and a radio frequency signal receiving device 304 corresponding to the self-service teller machine.
In practice, the user terminal 303 shown in fig. 3 may be an electronic device such as a mobile phone, a tablet computer, a personal computer, or the like. The banking server 301 may be a server, a server cluster formed by a plurality of servers, or a cloud computing service center. The banking server 301 and the user terminal 303 establish communication connection through a network, the banking server 301 and the self-service withdrawal device 302 establish communication connection through a network, and the self-service withdrawal device 302 may be a self-service device with a withdrawal function.
When the self-service withdrawal device 302 completes the withdrawal task of each queuing user, a prediction instruction is sent to a banking server, and after the banking server receives the prediction instruction, the banking server carries out radio frequency identification on the bank cards of each queuing user in the queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of the queuing user 1, the queuing user 2 and the queuing user 3; determining that a queuing user 2 and a queuing user 3 in a queuing area are target queuing users based on user information of each queuing user, identifying feature vectors of the queuing user 2 and the queuing user 3 by using a withdrawal amount estimation model corresponding to each queuing user 2 and the queuing user 3, obtaining first estimated withdrawal amounts of each queuing user 2 and the queuing user 3, and determining second estimated withdrawal amounts of the queuing user 1, wherein, because the queuing user 1 is not the target queuing user, the feature vectors of the queuing user 1 are predicted by indicating that the withdrawal amount model corresponding to the queuing user 1 is applied in advance, the estimated withdrawal amount sum is obtained based on each first estimated withdrawal amount and the second estimated withdrawal amount, judging whether the estimated withdrawal amount sum is larger than the current residual amount of a self-service withdrawal device, if the estimated withdrawal amount sum is larger than the current residual amount, indicating that the current residual amount of a bank note is insufficient, in this case, calculating average estimated withdrawal amounts of each queuing user, and the residual amount of the bank note based on the average estimated withdrawal amount, obtaining estimated withdrawal amounts of the queuing user 1, and sending the estimated service client amounts to a user terminal 303, so that the estimated service client amounts are obtained, and the estimated service client amounts can not be obtained when the estimated withdrawal amount of the queuing user 2 and the queuing user 3 are available, and the current withdrawal amount can not meet the current requirements of the current customer withdrawal device can not be obtained, for example, if the estimated service demands of the current client device can not be satisfied, and the estimated service client amount can not be found by the current client device can be withdrawn according to the current estimated client amount is 3.
Corresponding to the method shown in fig. 1, the embodiment of the present invention further provides a queuing prompt device, which is used for implementing the method shown in fig. 1, where the queuing prompt device provided in the embodiment of the present invention may be applied to a computer terminal or various mobile devices, and the structural schematic diagram of the queuing prompt device is shown in fig. 4, and specifically includes:
the processing unit 401 is configured to determine a current banknote remaining amount of the self-service withdrawal device corresponding to a prediction instruction in response to the prediction instruction, and perform radio frequency identification on a bank card of each queuing user in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device, so as to obtain user information of each queuing user;
a first judging unit 402, configured to judge whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
a first determining unit 403, configured to determine a current withdrawal amount influencing factor if the target queuing user exists in the queuing area, and generate a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influencing factor;
The identifying unit 404 is configured to identify the feature vector by applying a withdrawal amount prediction model corresponding to each target queuing user, so as to obtain a first estimated withdrawal amount of each target queuing user;
a calculating unit 405, configured to obtain a sum of estimated withdrawal amounts based on each of the first estimated withdrawal amounts and a second estimated withdrawal amount of each queuing user except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
a second judging unit 406, configured to judge whether the sum of the estimated withdrawal amounts is greater than the current remaining amount of the banknote;
a second determining unit 407, configured to determine, if it is determined that the sum of the estimated withdrawal amounts is greater than the remaining amount of the banknotes, the estimated service client number based on each of the first estimated withdrawal amounts, each of the second estimated withdrawal amounts, and the remaining amount of the banknotes;
and the prompting unit 408 is configured to send the estimated service client number to a user terminal of each target queuing user, so as to complete queuing prompting for each target queuing user.
According to the queuing prompt device provided by the embodiment of the invention, the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction is determined in response to the prediction instruction, and the bank cards of all queuing users in the queuing area of the self-service withdrawal device are subjected to radio frequency identification through the preset radio frequency signal receiving equipment, so that the user information of each queuing user is obtained; judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction; if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor; identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user; obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs; judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote; if the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount; and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users. The queuing prompt can be timely sent out for queuing users, so that the situation that the users cannot withdraw money due to insufficient quantity of the banknotes in the banknote box after the users spend a great deal of time and energy for queuing is avoided.
In an embodiment of the present invention, based on the implementation process described above, specifically, the processing unit 401 includes:
the analysis subunit is used for analyzing the prediction instruction to obtain instruction information of the prediction instruction;
the first determining subunit is used for determining the self-service withdrawal equipment corresponding to the prediction instruction based on the instruction information;
the acquisition subunit is used for acquiring the service flow information of the self-service withdrawal equipment;
and the processing subunit is used for obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
In an embodiment of the present invention, based on the implementation process described above, specifically, the second determining unit 407 includes:
the calculating subunit is used for calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
and the second determination subunit is used for determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknotes.
In an embodiment of the present invention, based on the implementation process described above, specifically, the prompting unit 408 includes:
A third determining subunit, configured to determine a prompting mode corresponding to each target queuing user;
and the sending subunit is used for sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
In an embodiment of the present invention, based on the implementation process, specifically, the queuing prompt device further includes: a transmitting unit;
the sending unit is used for generating a banknote distribution task message based on the estimated withdrawal sum and the banknote residual amount; sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
The specific principle and execution process of each unit and module in the queuing prompt device disclosed in the embodiment of the present invention are the same as those of the queuing prompt method disclosed in the embodiment of the present invention, and may refer to the corresponding parts in the queuing prompt method provided in the embodiment of the present invention, which are not repeated here.
The embodiment of the invention also provides a storage medium, which comprises stored instructions, wherein the equipment where the storage medium is located is controlled to execute the queuing prompt method when the instructions run.
The embodiment of the present invention further provides an electronic device, whose structural schematic diagram is shown in fig. 5, specifically including a memory 501, and one or more instructions 502, where the one or more instructions 502 are stored in the memory 501, and configured to be executed by the one or more processors 503, where the one or more instructions 502 perform the following operations:
responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user;
judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
if the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor;
Identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user;
obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote;
if the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount;
and sending the estimated service client number to the user terminals of the target queuing users to finish queuing prompt of the target queuing users.
It should be noted that, in the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described as different from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other. For the apparatus class embodiments, the description is relatively simple as it is substantially similar to the method embodiments, and reference is made to the description of the method embodiments for relevant points.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in the same piece or pieces of software and/or hardware when implementing the present invention.
From the above description of embodiments, it will be apparent to those skilled in the art that the present invention may be implemented in software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments of the present invention.
The above describes a queuing prompt method provided by the present invention in detail, and specific examples are applied to illustrate the principles and embodiments of the present invention, and the above examples are only used to help understand the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (10)
1. A queuing prompt method, comprising:
responding to a prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on bank cards of all queuing users in a queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain user information of each queuing user;
judging whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
If the target queuing users exist in the queuing area, determining a current withdrawal amount influence factor, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor;
identifying the feature vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user;
obtaining a predicted withdrawal amount sum based on the first predicted withdrawal amounts and second predicted withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote;
if the estimated withdrawal amount sum is larger than the banknote remaining amount, determining the estimated service client number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount;
The estimated service client number is sent to the user terminal of each target queuing user so as to complete queuing prompt of each target queuing user;
wherein the determining the estimated service client number based on each of the first estimated withdrawal amount, each of the second estimated withdrawal amount, and the remaining amount of the banknote includes: calculating to obtain an average estimated withdrawal amount according to each first estimated withdrawal amount and each second estimated withdrawal amount; and dividing the residual money amount of the bank note by the average estimated withdrawal amount to obtain the estimated service customer number.
2. The method of claim 1, wherein determining the current remaining amount of the banknote of the self-service teller machine corresponding to the predictive instruction comprises:
analyzing the predicted instruction to obtain instruction information of the predicted instruction;
determining self-service withdrawal equipment corresponding to the predicted instruction based on the instruction information;
acquiring service flow information of the self-service withdrawal device;
and obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
3. The method of claim 1, wherein the determining the estimated service customer number based on each of the first estimated withdrawal amount, each of the second estimated withdrawal amount, and the remaining amount of the banknote comprises:
Calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
and determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknote.
4. The method of claim 1, wherein said sending said estimated number of service clients to each of said target queuing users comprises:
determining a prompting mode corresponding to each target queuing user;
and sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
5. The method of claim 1, wherein after determining that the estimated withdrawal amount sum is greater than the remaining amount of the banknote, further comprising:
generating a banknote distribution task message based on the sum of the estimated withdrawal amounts and the residual banknote amount;
sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
6. A queuing prompt device, comprising:
The processing unit is used for responding to the prediction instruction, determining the current banknote remaining amount of the self-service withdrawal device corresponding to the prediction instruction, and carrying out radio frequency identification on the bank cards of all queuing users in the queuing area of the self-service withdrawal device through a preset radio frequency signal receiving device to obtain the user information of each queuing user;
a first judging unit, configured to judge whether a target queuing user exists in the queuing area; the target queuing user is a queuing user with no prompt record in a prompt time range, and the prompt time range is determined by timestamp information contained in the prediction instruction;
the first determining unit is used for determining a current withdrawal amount influence factor if the target queuing user exists in the queuing area, and generating a feature vector of each target queuing user based on user information of each target queuing user and the withdrawal amount influence factor;
the recognition unit is used for recognizing the characteristic vector of each target queuing user by applying a withdrawal amount prediction model corresponding to each target queuing user to obtain a first estimated withdrawal amount of each target queuing user;
The calculating unit is used for obtaining the sum of the estimated withdrawal amounts based on the first estimated withdrawal amounts and the second estimated withdrawal amounts of all queuing users except the target queuing user in the queuing area; the second estimated withdrawal amount is obtained by identifying the feature vector of the queuing user in advance through a withdrawal amount prediction model corresponding to the queuing user to which the second estimated withdrawal amount belongs;
the second judging unit is used for judging whether the sum of the estimated withdrawal amounts is larger than the current residual amount of the banknote;
the second determining unit is used for determining the estimated service customer number based on each first estimated withdrawal amount, each second estimated withdrawal amount and the banknote remaining amount if the estimated withdrawal amount sum is larger than the banknote remaining amount;
the prompting unit is used for sending the estimated service client number to the user terminals of the target queuing users so as to finish queuing prompt of the target queuing users;
wherein the determining the estimated service client number based on each of the first estimated withdrawal amount, each of the second estimated withdrawal amount, and the remaining amount of the banknote includes: calculating to obtain an average estimated withdrawal amount according to each first estimated withdrawal amount and each second estimated withdrawal amount; and dividing the residual money amount of the bank note by the average estimated withdrawal amount to obtain the estimated service customer number.
7. The apparatus of claim 6, wherein the processing unit comprises:
the analysis subunit is used for analyzing the prediction instruction to obtain instruction information of the prediction instruction;
the first determining subunit is used for determining the self-service withdrawal equipment corresponding to the prediction instruction based on the instruction information;
the acquisition subunit is used for acquiring the service flow information of the self-service withdrawal equipment;
and the processing subunit is used for obtaining the current banknote residual amount of the self-service cash withdrawal device according to the business flow information.
8. The apparatus according to claim 6, wherein the second determining unit includes:
the calculating subunit is used for calculating each first estimated withdrawal amount and each second estimated withdrawal amount to obtain an average estimated withdrawal amount;
and the second determination subunit is used for determining the estimated service client number based on the average estimated withdrawal amount and the residual amount of the banknotes.
9. The apparatus of claim 6, wherein the prompting unit comprises:
a third determining subunit, configured to determine a prompting mode corresponding to each target queuing user;
And the sending subunit is used for sending the estimated service client number to each target queuing user according to the prompt mode corresponding to each target queuing user.
10. The apparatus as recited in claim 6, further comprising: a transmitting unit;
the sending unit is used for generating a banknote distribution task message based on the estimated withdrawal sum and the banknote residual amount; sending the banknote distribution task message to a preset banknote distribution task system so as to trigger the banknote distribution task system to generate a banknote distribution task corresponding to the banknote distribution task message.
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