CN112581267A

CN112581267A - Credit card data simulation method, credit card data simulation device, computer equipment and storage medium

Info

Publication number: CN112581267A
Application number: CN202011599952.1A
Authority: CN
Inventors: 鲁晓颖; 郑秀明; 张朝晖; 金夏瑞
Original assignee: Ping An Bank Co Ltd
Current assignee: Ping An Bank Co Ltd
Priority date: 2020-12-29
Filing date: 2020-12-29
Publication date: 2021-03-30
Anticipated expiration: 2040-12-29
Also published as: CN112581267B

Abstract

The invention relates to the technical field of data processing, and provides a credit card data simulation method, a device, computer equipment and a storage medium, wherein the credit card data simulation method comprises the following steps: responding to a credit card simulation request, and extracting a credit card simulation message corresponding to the credit card simulation request; receiving a plurality of first computing sub-engines selected by a first user, and extracting a plurality of first computing objects in each first computing sub-engine; receiving object values input by the first user in the plurality of first computing objects; generating a first total calculation engine according to the plurality of first sub-calculation engines, wherein the first total calculation engine corresponds to a first simulated operation environment of the credit card; and calling the first total calculation engine to perform simulation calculation based on the object values input in the plurality of first calculation objects and the credit card simulation message to obtain a first credit card response message. The invention can intelligently simulate the credit card running environment according to the calculation sub-engine selected by the user, and the simulation efficiency of the credit card data is high.

Description

Credit card data simulation method, credit card data simulation device, computer equipment and storage medium

Technical Field

The invention relates to the technical field of data processing, in particular to a credit card data simulation method, a credit card data simulation device, computer equipment and a storage medium.

Background

As one of the retail credits, the credit card which is convenient to apply and use continuously climbs in daily consumption settlement, and becomes an important support for rapid development of bank retail business. There is a credit card simulation system provided in the prior art to simulate whether consumption data of a credit card is increased or decreased.

However, in the process of implementing the invention, the inventor finds that the existing credit card simulation system has fixed templates, non-selectable parameters and single credit card simulation; in addition, the output of the staged data in the credit card simulation system requires manual calculation of the final result by means of the spreadsheet, which results in low calculation efficiency, and errors are easily generated in manual input of the staged data into the spreadsheet, which results in low accuracy of the calculation result of the credit card simulation data.

Disclosure of Invention

In view of the above, there is a need for a credit card data simulation method, apparatus, computer device and storage medium, which can intelligently calculate a credit card simulation message according to a calculation sub-engine selected by a user and have high credit card data simulation efficiency.

A first aspect of the present invention provides a credit card data simulation method, the method comprising:

responding to a credit card simulation request, and extracting a credit card simulation message corresponding to the credit card simulation request;

receiving a plurality of first computing sub-engines selected by a first user, and extracting a plurality of first computing objects in each first computing sub-engine;

receiving object values input by the first user in the plurality of first computing objects;

generating a first total calculation engine according to the plurality of first sub-calculation engines, wherein the first total calculation engine corresponds to a first simulated operation environment of the credit card;

and calling the first total calculation engine to perform simulation calculation based on the object values input in the plurality of first calculation objects and the credit card simulation message to obtain a first credit card response message.

In an alternative embodiment, the generating a first compute farm engine from the plurality of first compute sub-engines comprises:

initializing an inverted binary tree for the first compute total engine;

identifying a plate identification for each first compute sub-engine;

determining the level of a plurality of first calculation objects corresponding to the first calculation sub-engine in an inverted binary tree according to the plate identification;

determining two first calculation objects corresponding to the same operation operator in the same level as brother nodes of the level;

determining two first calculation sub-engines corresponding to two adjacent plate identifications, determining a plurality of target first calculation objects corresponding to the two first calculation sub-engines, and determining two target first calculation objects corresponding to the same first calculation object in the plurality of target first calculation objects as parent-child nodes.

In an optional embodiment, the invoking the first total computing engine to perform a simulation computation based on the object values input in the plurality of first computation objects and the credit card simulation message, and obtaining a first credit card response message includes:

acquiring simulation time and expected time input by the first user;

calculating iterative simulation calculation frequency according to the simulation time and the expected time;

traversing each layer of the inverted binary tree from a root node of the inverted binary tree layer by layer upwards according to the iterative simulation calculation frequency;

starting from a root node of the inverted binary tree, performing analog computation based on object values input in a plurality of first computation objects corresponding to the root node and the credit card analog messages to obtain a computation result corresponding to the root node;

performing analog calculation based on object values input in a plurality of first calculation objects corresponding to the nodes in the previous layer and calculation results corresponding to the nodes in the next layer to obtain calculation results corresponding to the nodes in the previous layer;

and acquiring a calculation result corresponding to the first layer of nodes when the iterative simulation calculation is finished, and generating the first credit card response message according to the calculation result corresponding to the first layer of nodes.

In an alternative embodiment, said extracting the first compute object in each of said first compute sub-engines comprises:

identifying a plurality of operational operators in each of the first compute sub-engines;

cutting the corresponding first computing sub-engine by taking each operation operator as a cutter to obtain a plurality of candidate computing objects corresponding to the first computing sub-engine;

initializing a set of compute objects for each of the first compute sub-engines;

and sequentially writing the candidate calculation objects into the corresponding calculation object set to obtain a plurality of first calculation objects of the first calculation sub-engine.

In an optional embodiment, the extracting the credit card emulation message corresponding to the credit card emulation request includes:

acquiring a request account number in the credit card simulation request;

identifying a request client corresponding to the request account;

informing the request client side to establish a punching connection channel with a credit card simulation system;

judging whether the punching connection channel is successfully established or not;

and when the punching connection channel is successfully established, pulling the credit card simulation message from the request client through the punching connection channel.

In an optional embodiment, the method further comprises:

judging whether the first credit card simulation data in the first credit card response message is smaller than a first preset threshold value or not;

when the first credit card simulation data is smaller than the first preset threshold value, calculating a calculation value of a corresponding first calculation sub-engine based on an object value input in the first calculation object;

acquiring a target first calculation sub-engine corresponding to a target calculation value smaller than a second preset threshold;

extracting a context first computation sub-engine of the target first computation sub-engine;

generating a simulation interpretation report according to the target first computation sub-engine and the context first computation sub-engine.

In an optional embodiment, the method further comprises:

receiving a plurality of second computing sub-engines selected by a second user, and extracting a plurality of second computing objects in each second computing sub-engine;

calling the second calculation total engine to perform simulation calculation based on object values input by the second user in the plurality of second calculation objects and the credit card simulation message to obtain a second credit card response message;

comparing first credit card simulation data in the first credit card response message with second credit card simulation data in the second credit card response message;

when the first credit card simulation data is larger than the second credit card simulation data, determining that the first user is a target user;

and when the second credit card simulation data is larger than the first credit card simulation data, determining that the second user is a target user.

A second aspect of the present invention provides a credit card data simulation apparatus, the apparatus comprising:

the request response module is used for responding to the credit card simulation request and extracting a credit card simulation message corresponding to the credit card simulation request;

the object extraction module is used for receiving a plurality of first computing sub-engines selected by a first user and extracting a plurality of first computing objects in each first computing sub-engine;

a value receiving module, configured to receive object values input by the first user in the plurality of first computing objects;

the environment generation module is used for generating a first total calculation engine according to the plurality of first sub-calculation engines, and the first total calculation engine corresponds to a first simulated operation environment of the credit card;

and the simulation calculation module is used for calling the first calculation total engine to perform simulation calculation based on the object values input in the plurality of first calculation objects and the credit card simulation message to obtain a first credit card response message.

A third aspect of the invention provides a computer apparatus comprising a processor for implementing the credit card data emulation method when executing a computer program stored in a memory.

A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the credit card data simulation method.

In summary, the credit card data simulation method, the device, the computer device and the storage medium according to the present invention, in response to a credit card simulation request, extract a credit card simulation packet corresponding to the credit card simulation request, and when receiving a plurality of first computing sub-engines selected by a first user, extract a plurality of first computing objects in each of the first computing sub-engines, thereby generating a first total computing engine according to the plurality of first computing sub-engines; and when object values input by a first user in the plurality of first computing objects are received, calling the first computing total engine to perform simulation computation based on the object values input in the plurality of first computing objects and the credit card simulation message to obtain a first credit card response message. The invention can generate the total calculation engine according to the calculation sub-engine selected by the user, thereby realizing the dynamic simulation of the simulated operation environment of the credit card, only needing the user to input the object value, automatically calculating the credit card simulated message, and having high credit card data simulation efficiency and high accuracy of the calculation result of the credit card simulated data.

Drawings

Fig. 1 is a flowchart of a credit card data simulation method according to an embodiment of the present invention.

Fig. 2 is a structural diagram of a credit card data simulation apparatus according to a second embodiment of the present invention.

Fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention.

Detailed Description

In order that the above objects, features and advantages of the present invention can be more clearly understood, a detailed description of the present invention will be given below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

The credit card data simulation method provided by the embodiment of the invention is executed by computer equipment, and correspondingly, the credit card data simulation device runs in the computer equipment.

Fig. 1 is a flowchart of a credit card data simulation method according to an embodiment of the present invention. The credit card data simulation method specifically comprises the following steps, and the sequence of the steps in the flow chart can be changed and some steps can be omitted according to different requirements.

S11, responding to the credit card simulation request, extracting the credit card simulation message corresponding to the credit card simulation request.

A credit card simulation system is installed in the computer equipment and is used for simulating the credit card data volume so as to simulate whether the credit card data is increased or adjusted on the premise of the selected calculation sub-engine.

Each client needs to register an account and a password in the credit card simulation system in advance before logging in the credit card simulation system. And when the subsequent client logs in the credit card simulation system, inputting an account and a password, and successfully logging in the credit card simulation system after passing the verification of the credit card simulation system.

The credit card simulation system is provided with a credit card simulation interface, confirms that a credit card simulation request is received after the account and the password of the client are verified to be correct, and responds to the credit card simulation request to display the credit card simulation interface.

acquiring a request account number in the credit card simulation request;

identifying a request client corresponding to the request account;

And the account when the client logs in the credit card simulation system is a request account number, and the request client can be determined according to the request account number, so that a credit card simulation message required by credit card simulation is pulled from the request client.

The interconnection between the credit card simulation system and the requesting client can be realized by adopting a punching technology, wherein the punching technology can comprise the following steps: a Session transfer Protocol for Network Address translations (STUN) Protocol, a User Datagram Protocol (UDP), and the like.

The method comprises the steps that a request client sends a PING data packet to the request client, whether a PING response packet of the request client is received or not is detected, when the PING response packet of the request client is received, the successful establishment of a punching connection channel is determined, and when the PING response packet of the request client is not received, the unsuccessful establishment of the punching connection channel is determined.

And after the punching connection channel is successfully established, the credit card simulation system actively sends a credit card simulation message request to the request client to request to download the credit card simulation message. And the request client responds after receiving the credit card simulation message request, pulls the credit card simulation message from a local storage and sends the credit card simulation message to the credit card simulation system through the punching connection channel, thereby completing the transmission of the credit card simulation message. The credit card emulation messages may be the underlying data of the credit card, such as fixed assets, mobile assets, etc.

In the optional embodiment, the fast communication connection between the request client and the credit card simulation system is realized by establishing the punching connection, and safety guarantee is provided for the transmission of the credit card simulation message.

S12, receiving a plurality of first computing sub-engines selected by a first user, and extracting a plurality of first computing objects in each first computing sub-engine.

The credit card simulation interface displays a plurality of plates, each plate corresponds to a credit card simulation activity, for example, a first plate corresponds to a credit card market analysis activity, a second plate corresponds to a credit card product development activity, and a third plate corresponds to a credit card organization production activity. Each plate corresponds to one or more computation sub-engines, which may be a Fast Expression Language (FEL) computation engine. The calculation operator engine may be a mathematical model, e.g., a mathematical formula.

The user may select a plurality of calculation sub-engines in the credit card simulation interface through the client.

The calculation sub-engine selected by the user for simulating for the first time can be called a first calculation sub-engine, and the calculation sub-engine selected by the user for simulating for the second time can be called a second calculation sub-engine; the first user simulation selected calculation sub-engine may be referred to as a first calculation sub-engine, and the second user simulation selected calculation sub-engine may be referred to as a second calculation sub-engine, which is not limited herein.

Wherein the first computation sub-engine may be a set of operation operators and a plurality of computation objects for simulating computation results of the computation objects.

The operation operators are mathematical calculation symbols, e.g., "+", "-", "+", "/", etc. For example, assuming that a certain computing engine is revenue by one price, the "+" is an operation operator, and the sales and the price are two computing objects corresponding to the operation operator.

Because one or more computation sub-engines correspond to each plate, a certain logical operation relation exists between one or more computation sub-engines in each plate, for example, a first compute sub-engine includes a first compute object A, a first compute object B, a second first compute sub-engine includes a first compute object B, a first compute object C, a first compute object B in common between the first compute sub-engine and the second first compute sub-engine, therefore, by utilizing the non-overlapping property of the data in the set, the same first calculation object can be effectively filtered out by sequentially writing the plurality of candidate calculation objects into the calculation object set, therefore, the plurality of first computing objects written into the computing object set have no repeatability, and the first computing objects in the plurality of first computing sub-engines selected by the first user can be quickly extracted.

S13, receiving object values input by the first user in the plurality of first calculation objects.

After extracting the plurality of first computing objects in each first computing sub-engine, the credit card simulation computing system displays the plurality of first computing objects in each first computing sub-engine in a form of text boxes in a credit card simulation display interface for the first user to input object values of the first computing objects. Illustratively, a first user enters an object value of 30 in a text box corresponding to a first computing object "sales amount" and the first user enters an object value of 100 in a text box corresponding to a first computing object "unit price".

And S14, generating a first total calculation engine according to the plurality of first sub-calculation engines, wherein the first total calculation engine corresponds to the first simulated operation environment of the credit card.

The first user selecting the plurality of first computing sub-engines and entering an object value in each first computing object in each first computing sub-engine corresponds to determining a credit card simulation environment.

A total first calculation total engine is generated according to a plurality of first calculation sub-engines selected by a first user so as to simulate the operation environment of the credit card.

initializing an inverted binary tree for the first compute total engine;

identifying a plate identification for each first compute sub-engine;

In the conventional binary tree, the root node is at the top of the binary tree, and then the leaf nodes are expanded downward from the root node. In addition, the inverted binary tree in this embodiment includes one or more root nodes.

Each first computation sub-engine corresponds to one simulation plate, different simulation plates correspond to different plate identifiers according to simulation logic, and the plate identifiers are used for identifying the sequence of the corresponding first computation sub-engines in the simulation logic. The smaller the plate identification, the earlier execution order of the corresponding first computation sub-engine in the simulation logic is indicated, and the larger the plate identification, the later execution order of the corresponding first computation sub-engine in the simulation logic is indicated. For example, assuming that the plate corresponding to a certain first compute sub-engine is labeled "1", it indicates that the one first compute sub-engine is in the first order of the simulation logic and should be simulated to compute first, and therefore, the one first compute sub-engine is at the first level in the inverted binary tree.

And a plurality of first computing objects corresponding to the same first computing sub-engine are positioned in the same level in the inverted binary tree. And some first computing objects located at the same level correspond to the same operation operator, and two first computing objects corresponding to the same operation operator are determined as sibling nodes of the level, wherein the first computing object located at the left side of the same operation operator is a left sibling node, the first computing object located at the right side of the same operation operator is a right sibling node, and the like, so that the plurality of first objects of the same first computing sub-engine can be rendered at the same level of the inverted binary tree, and a directed line segment pointing from the left sibling node to the right sibling node is rendered, and therefore during simulation computation, a computing process can be executed from left to right according to the indication of the priority line segment, so that simulation computation of the same simulation block is completed.

And two first computation sub-engines corresponding to two adjacent plate identifiers indicate that the two first computation sub-engines have sequential analog logic order, so that the first computation sub-engine corresponding to the smaller plate identifier is determined as the next level in the inverted binary tree, and the first computation sub-engine corresponding to the larger plate identifier is determined as the previous level in the inverted binary tree. After determining the upper and lower levels in the inverted binary tree, determining other two first calculation objects corresponding to the same first calculation object as parent and child nodes, wherein the first calculation object corresponding to the small plate identifier in the other two first calculation objects is determined as the parent node, and the first calculation object corresponding to the large plate identifier in the other two first calculation objects is determined as the child node.

And S15, calling the first total calculation engine to perform simulation calculation based on the object values input in the plurality of first calculation objects and the credit card simulation message, and obtaining a first credit card response message.

After the credit card simulation operation environment is generated, the first calculation general engine can be called to perform simulation calculation, and after the simulation calculation is finished, a first credit card response message is generated.

acquiring simulation time and expected time input by the first user;

The simulation time is the system running time of the credit card simulation system set by the user, and the expected time is the time of the credit card simulation system set by the user simulating the running environment of the credit card. For example, assuming that the simulation time is 2 days and the expected time is 5 years, the operation data of the credit card is simulated for 5 years in the 2-day operation time of the credit card simulation system.

And calculating the quotient of the expected time and the simulation time to obtain iterative simulation calculation frequency, namely the required running time of each iterative simulation calculation.

For the first iteration simulation calculation, traversing each layer of the inverted binary tree from the root node of the inverted binary tree layer by layer upwards, and for the first layer, performing simulation calculation from the root node of the inverted binary tree based on object values input in a plurality of first calculation objects corresponding to the root node and the credit card simulation message to obtain a calculation result corresponding to the root node; for a second layer, performing analog computation based on object values input in a plurality of first computation objects corresponding to nodes of the second layer and computation results corresponding to root nodes to obtain computation results corresponding to the nodes of the second layer; for the third layer, performing analog computation based on object values input in a plurality of first computation objects corresponding to the nodes of the third layer and the computation results corresponding to the second layer to obtain the computation results corresponding to the nodes of the third layer; and so on; and (4) knowing that the simulation calculation is carried out on the uppermost layer of the inverted binary tree to obtain a calculation result, and finishing the first iteration simulation calculation process.

For the second iteration simulation calculation, traversing each layer of the inverted binary tree layer by layer upwards from the root node of the inverted binary tree, and for the first layer, performing simulation calculation from the root node of the inverted binary tree based on object values input in a plurality of first calculation objects corresponding to the root node and the credit card simulation message to obtain a calculation result corresponding to the root node; for a second layer, performing analog computation based on object values input in a plurality of first computation objects corresponding to nodes of the second layer and computation results corresponding to root nodes to obtain computation results corresponding to the nodes of the second layer; for the third layer, performing analog computation based on object values input in a plurality of first computation objects corresponding to the nodes of the third layer and the computation results corresponding to the second layer to obtain the computation results corresponding to the nodes of the third layer; and so on; and (4) knowing that the simulation calculation is carried out on the uppermost layer of the inverted binary tree to obtain a calculation result, and finishing the second iteration simulation calculation process.

And so on.

Knowing that all iterative simulation calculations are completed, generating a calculation result corresponding to the topmost node when the iterative simulation calculation is finished, and generating the first credit card response message according to the calculation result corresponding to the topmost node.

In this alternative embodiment, the conversion from the abstract mathematical model to the parameterized computational model is implemented by selecting the first computation sub-engine by the user and generating the inverted binary tree according to the selected first computation sub-engine, thereby performing the simulated computation process logically and sequentially according to the inverted binary tree.

In an optional embodiment, the method further comprises:

The first preset threshold may be 0, and the second preset threshold may also be 0. When the first credit card simulation data is smaller than the first preset threshold value, the fact that the credit card data is in negative growth under the first simulation operation environment is indicated, and when the first credit card simulation data is larger than the first preset threshold value, the fact that the credit card data is in positive growth under the first simulation operation environment is indicated.

In this alternative embodiment, when the first credit card analog data in the first credit card response message shows negative growth, the reason for the negative growth of the first credit card analog data is queried by obtaining the target first calculation sub-engine corresponding to each target calculation value smaller than the second preset threshold. And for more accurate explanation of the reason for the negative growth, generating a target simulation interpretation report by combining the target first computing sub-engine and the context of the target first computing sub-engine for reference by the first user.

In an optional embodiment, the method further comprises:

Wherein the second user and the first user may be users in the same credit card company.

After receiving a plurality of second computing sub-engines selected by a second user, the credit card simulation system extracts a plurality of second computing objects in each second computing sub-engine, simultaneously receives object values input by the second user in the second computing objects, and generates a second total computing engine according to the second computing sub-engines, so that the second total computing engine is called to perform simulation computation based on the object values input in the second computing objects and the credit card simulation messages, and a second credit card response message is obtained.

When the first credit card simulation data is larger than the second credit card simulation data, the simulation performance of the first general calculation engine is better than that of the second general calculation engine, namely, the simulated first simulation operation environment of the credit card is more suitable for the development of the credit card business than the simulated second simulation operation environment of the credit card. When the first credit card simulation data is smaller than the second credit card simulation data, the simulation performance of the first general computing engine is inferior to that of the second general computing engine, namely, the simulated second simulated operation environment of the credit card is more suitable for the development of the credit card business than the simulated first simulated operation environment of the credit card.

The simulated operation environment of the credit card is obtained based on actual combat management experience of the user, so that the larger simulation data of which credit card is larger indicates that the corresponding simulated operation environment of the credit card is better, and the richer management experience of the corresponding user determines that the user is a target user and serves as a leader of credit card business to lead the better development of the credit card business.

In this alternative embodiment, the first user selects the plurality of first calculation sub-engines to simulate the first simulated operation environment of the credit card to simulate the first credit card simulated data of the credit card in the first simulated operation environment, the second user selects the plurality of second calculation sub-engines to simulate the second simulated operation environment of the credit card to simulate the second credit card simulated data of the credit card in the second simulated operation environment, the first credit card simulated data is compared with the second credit card simulated data, and which user is selected as the target user is determined according to the comparison result, so that the target user is determined more objectively and accurately.

The credit card data simulation method provided by the embodiment of the invention responds to a credit card simulation request, extracts a credit card simulation message corresponding to the credit card simulation request, and extracts a plurality of first calculation objects in each first calculation sub-engine when receiving a plurality of first calculation sub-engines selected by a first user, so as to generate a first total calculation engine according to the plurality of first calculation sub-engines; and when object values input by a first user in the plurality of first computing objects are received, calling the first computing total engine to perform simulation computation based on the object values input in the plurality of first computing objects and the credit card simulation message to obtain a first credit card response message. The invention can generate the total calculation engine according to the calculation sub-engine selected by the user, thereby realizing the dynamic simulation of the simulated operation environment of the credit card, only needing the user to input the object value, automatically calculating the credit card simulated message, and having high credit card data simulation efficiency and high accuracy of the calculation result of the credit card simulated data.

It is emphasized that the calculation sub-engines may be stored in the nodes of the blockchain in order to further ensure privacy and security of the calculation sub-engines.

In some embodiments, the credit card data simulator 20 may include a plurality of functional modules comprising computer program segments. The computer program of the various program segments in the credit card data emulation device 20 may be stored in a memory of a computer device and executed by at least one processor to perform the functions of credit card data emulation (described in detail with reference to fig. 1).

In this embodiment, the credit card data simulation apparatus 20 may be divided into a plurality of functional modules according to the functions performed by the credit card data simulation apparatus. The functional module may include: a request response module 201, an object extraction module 202, a value receiving module 203, an environment generation module 204, a simulation calculation module 205, a report generation module 206, a data comparison module 207, and a targeting module 208. The module referred to herein is a series of computer program segments capable of being executed by at least one processor and capable of performing a fixed function and is stored in memory. In the present embodiment, the functions of the modules will be described in detail in the following embodiments.

The request response module 201 is configured to respond to a credit card simulation request, and extract a credit card simulation message corresponding to the credit card simulation request.

In an alternative embodiment, the request response module 201 extracting the credit card simulation message corresponding to the credit card simulation request includes:

acquiring a request account number in the credit card simulation request;

identifying a request client corresponding to the request account;

The object extraction module 202 is configured to receive a plurality of first computing sub-engines selected by a first user, and extract a plurality of first computing objects in each of the first computing sub-engines.

The credit card simulation interface displays a plurality of plates, each plate corresponds to a credit card simulation activity, for example, a first plate corresponds to a credit card market analysis activity, a second plate corresponds to a credit card product development activity, and a third plate corresponds to a credit card organization production activity. Each plate corresponds to one or more computation sub-engines, which may be a Fast Expression Language (FEL) computation engine. The calculation operator engine may be a mathematical model, e.g., a mathematical formula. The user may select a plurality of calculation sub-engines in the credit card simulation interface through the client.

In an alternative embodiment, the extracting the first computation object in each of the first computation sub-engines by the object extraction module 202 comprises:

The value receiving module 203 is configured to receive object values input by the first user in the plurality of first computing objects.

The environment generating module 204 generates a first total computing engine according to the plurality of first sub-computing engines, where the first total computing engine corresponds to a first simulated operating environment of the credit card.

In an alternative embodiment, the environment generation module 204 generating the first total compute engine from the plurality of first compute sub-engines comprises:

initializing an inverted binary tree for the first compute total engine;

identifying a plate identification for each first compute sub-engine;

The simulation computation module 205 is configured to invoke the first computation engine to perform simulation computation based on the object values input in the plurality of first computation objects and the credit card simulation packet, so as to obtain a first credit card response packet.

In an optional embodiment, the invoking of the first general computation engine by the simulation computation module 205 performs simulation computation based on the object values input in the first computation objects and the credit card simulation message, and obtaining a first credit card response message includes:

acquiring simulation time and expected time input by the first user;

And so on.

The report generating module 206 is configured to determine whether first credit card simulation data in the first credit card response message is smaller than a first preset threshold; when the first credit card simulation data is smaller than the first preset threshold value, calculating a calculation value of a corresponding first calculation sub-engine based on an object value input in the first calculation object; acquiring a target first calculation sub-engine corresponding to a target calculation value smaller than a second preset threshold; extracting a context first computation sub-engine of the target first computation sub-engine; generating a simulation interpretation report according to the target first computation sub-engine and the context first computation sub-engine.

The object extraction module 202 is further configured to receive a plurality of second computing sub-engines selected by a second user, and extract a plurality of second computing objects in each of the second computing sub-engines;

the environment generating module 204 is further configured to generate a first total computing engine according to the plurality of first sub-computing engines, where the first total computing engine corresponds to a first simulated operating environment of the credit card;

the analog computation module 205 is further configured to invoke the second computation engine to perform analog computation based on object values input by the second user in the plurality of second computation objects and the credit card analog messages, so as to obtain second credit card response messages;

the data comparison module 207 is configured to compare first credit card simulation data in the first credit card response message with second credit card simulation data in the second credit card response message;

the target determination module 208 is configured to determine that the first user is a target user when the first credit card simulation data is greater than the second credit card simulation data;

the target determination module 208 is further configured to determine that the second user is a target user when the second credit card simulation data is greater than the first credit card simulation data.

The credit card data simulation device provided by the embodiment of the invention responds to a credit card simulation request, extracts a credit card simulation message corresponding to the credit card simulation request, and extracts a plurality of first calculation objects in each first calculation sub-engine when receiving a plurality of first calculation sub-engines selected by a first user, so as to generate a first total calculation engine according to the plurality of first calculation sub-engines; and when object values input by a first user in the plurality of first computing objects are received, calling the first computing total engine to perform simulation computation based on the object values input in the plurality of first computing objects and the credit card simulation message to obtain a first credit card response message. The invention can generate the total calculation engine according to the calculation sub-engine selected by the user, thereby realizing the dynamic simulation of the simulated operation environment of the credit card, only needing the user to input the object value, automatically calculating the credit card simulated message, and having high credit card data simulation efficiency and high accuracy of the calculation result of the credit card simulated data.

Fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention. In the preferred embodiment of the present invention, the computer device 3 includes a memory 31, at least one processor 32, at least one communication bus 33, and a transceiver 34.

It will be appreciated by those skilled in the art that the configuration of the computer device shown in fig. 3 does not constitute a limitation of the embodiments of the present invention, and may be a bus-type configuration or a star-type configuration, and that the computer device 3 may include more or less hardware or software than those shown, or a different arrangement of components.

In some embodiments, the computer device 3 is a device capable of automatically performing numerical calculation and/or information processing according to instructions set or stored in advance, and the hardware includes but is not limited to a microprocessor, an application specific integrated circuit, a programmable gate array, a digital processor, an embedded device, and the like. The computer device 3 may also include a client device, which includes, but is not limited to, any electronic product capable of interacting with a client through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device, for example, a personal computer, a tablet computer, a smart phone, a digital camera, etc.

It should be noted that the computer device 3 is only an example, and other electronic products that are currently available or may come into existence in the future, such as electronic products that can be adapted to the present invention, should also be included in the scope of the present invention, and are included herein by reference.

In some embodiments, the memory 31 has stored therein a computer program that, when executed by the at least one processor 32, performs all or part of the steps of the credit card data emulation method as described. The Memory 31 includes a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an electronically Erasable rewritable Read-Only Memory (Electrically-Erasable Programmable Read-Only Memory (EEPROM)), an optical Read-Only disk (CD-ROM) or other optical disk Memory, a magnetic disk Memory, a tape Memory, or any other medium readable by a computer capable of carrying or storing data.

Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.

The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

In some embodiments, the at least one processor 32 is a Control Unit (Control Unit) of the computer device 3, connects various components of the entire computer device 3 by using various interfaces and lines, and executes various functions and processes data of the computer device 3 by running or executing programs or modules stored in the memory 31 and calling data stored in the memory 31. For example, the at least one processor 32, when executing the computer program stored in the memory, implements all or a portion of the steps of the credit card data emulation method described in embodiments of the present invention; or to implement all or part of the functions of the credit card data emulation device. The at least one processor 32 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips.

In some embodiments, the at least one communication bus 33 is arranged to enable connection communication between the memory 31 and the at least one processor 32 or the like.

Although not shown, the computer device 3 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 32 through a power management device, so as to implement functions of managing charging, discharging, and power consumption through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The computer device 3 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.

The integrated unit implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a computer device, or a network device) or a processor (processor) to execute parts of the methods according to the embodiments of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or that the singular does not exclude the plural. A plurality of units or means recited in the specification may also be implemented by one unit or means through software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A credit card data emulation method, comprising:

2. The method of credit card data emulation of claim 1, wherein said generating a first compute farm engine from said plurality of first compute sub-engines comprises:

initializing an inverted binary tree for the first compute total engine;

identifying a plate identification for each first compute sub-engine;

3. The method of claim 2, wherein said invoking the first computational overall engine to perform a simulation computation based on the object values input in the first plurality of computational objects and the credit card simulation message, and obtaining a first credit card response message comprises:

acquiring simulation time and expected time input by the first user;

4. The credit card data emulation method of claim 3, wherein said extracting a first computational object in each of said first computational sub-engines comprises:

5. The method of claim 3, wherein the extracting the credit card emulation message corresponding to the credit card emulation request comprises:

acquiring a request account number in the credit card simulation request;

identifying a request client corresponding to the request account;

6. The credit card data simulation method of claim 4 or 5, wherein the method further comprises:

7. The credit card data simulation method of claim 4 or 5, wherein the method further comprises:

8. A credit card data emulation apparatus, comprising:

9. A computer device, characterized in that the computer device comprises a processor for implementing the credit card data emulation method according to any one of claims 1 to 7 when executing a computer program stored in a memory.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the credit card data simulation method according to any one of claims 1 to 7.