CN111445139A - Business process simulation method and device, storage medium and electronic equipment - Google Patents
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Abstract
The disclosure relates to a business process simulation method, a business process simulation device, a computer readable storage medium and electronic equipment, and belongs to the technical field of information processing, wherein the method comprises the following steps: acquiring a historical business flow scheme according to an expected business target, wherein the historical business flow scheme comprises historical business flow rules; replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule; performing service processing according to the new service flow scheme to obtain a corresponding service result; and determining the influence of the new business process rule on the expected business target according to the business result. The method can realize the simulation of the business process and evaluate the influence of the changed distribution rule on the expected business target.
Description
Technical Field
The present disclosure relates to the field of information processing technologies, and in particular, to a business process simulation method, a business process simulation apparatus, a computer-readable storage medium, and an electronic device.
Background
At present, the loan system has a lot of customer information and a lot of factors influencing the loan application to loan payment of customers, there may be a wind control factor, a regional policy factor, a fund chain factor, an insurer factor, a guarantor factor, a channel development factor, etc., in a large loan system, a plurality of guarantors, insurers and funders are accessed at the same time, and each credit provider (guarantor, insurer, etc.) and each funder (bank, P2P, trust, etc.) are different for the business city which can be opened, the acceptable credit providers and funders, the acceptable loan duration, the loan usage, the requirements of local laws and regulations, the daily loan amount per month, etc., therefore, specific funds can be paid only under specific combination conditions, such as funds are beyond the limit of the credit or fund increase and are unavailable, and even if the client returns to the credit and redistributes the funds, the operation experience of the client can be influenced.
Therefore, accurate marketing and accurate distribution are very important for loan transaction. The traditional loan application process is long, the types of client information are multiple, and the factors influencing the fund distribution are also multiple, so that the influence on the whole loan process can be difficult to evaluate after one distribution rule is changed, or how to configure the distribution rule to reach a certain sale target is also difficult.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure is directed to a business process simulation method, a business process simulation apparatus, a computer-readable storage medium, and an electronic device, so as to simulate an influence of changing an allocation rule on an expected business target at least to a certain extent, and avoid a possible adverse effect of directly modifying the rule.
According to an aspect of the present disclosure, a business process simulation method is provided, including:
acquiring a historical business flow scheme according to an expected business target, wherein the historical business flow scheme comprises historical business flow rules;
replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule;
performing service processing according to the new service flow scheme to obtain a corresponding service result;
and determining the influence of the new business process rule on the expected business target according to the business result.
In an exemplary embodiment of the disclosure, the obtaining a historical business process scenario according to an expected business objective includes:
inquiring a historical service sample matched with an expected service target according to the expected service target;
and inputting the historical service samples into a machine learning model to obtain a historical service flow scheme output by the machine learning model.
In an exemplary embodiment of the present disclosure, the replacing the historical business process rule with the new business process rule to obtain a new business process scheme corresponding to the new business process rule includes:
receiving modification of the configuration items of the historical business process rules to generate new business process rules;
and obtaining a new business process scheme corresponding to the new business process rule according to the new business process rule.
In an exemplary embodiment of the present disclosure, the performing service processing according to the new service flow scheme to obtain a corresponding service result includes:
acquiring a historical service sample;
and performing service processing on the historical service sample according to the new service flow scheme to obtain a service result corresponding to the historical service sample.
In an exemplary embodiment of the disclosure, the determining the influence of the new business process rule on the expected business objective according to the business result includes:
analyzing the service result according to a preset statistical analysis method to obtain an analysis result;
and determining the influence of the new business process rule on the expected business target according to the analysis result.
In an exemplary embodiment of the present disclosure, the determining the influence of the new business process rule on the expected business objective according to the analysis result includes:
taking the difference value between the business result and the expected business target as the analysis result;
if the difference is smaller than the preset threshold value, determining that the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target.
In an exemplary embodiment of the present disclosure, the method further comprises:
if the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target, performing business processing according to the new business process rule to achieve the expected business target;
and if the influence of the new business process rule on the expected business target is that the new business process rule cannot realize the expected business target, adjusting the new business process rule.
According to an aspect of the present disclosure, there is provided a business process simulation apparatus, including:
the acquisition module is used for acquiring a historical business process scheme according to an expected business target, wherein the historical business process scheme comprises historical business process rules;
the replacing module is used for replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule;
the processing module is used for carrying out service processing according to the new service flow scheme to obtain a corresponding service result;
and the determining module is used for determining the influence of the new business process rule on the expected business target according to the business result.
According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the agent allocation method of any one of the above.
According to an aspect of the present disclosure, there is provided an electronic device including:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform any one of the agent allocation methods described above via execution of the executable instructions.
The invention discloses a business process simulation method and a device, wherein a historical business process rule is replaced by a new business process rule to obtain a new business process scheme corresponding to the new business process rule, then business processing is carried out according to the new business process scheme to obtain a corresponding business result, and the influence of the new business process rule on an expected business target is determined according to the business result. The technical scheme in the disclosure provides the simulation of the business process for the business system, predicts the result in advance, provides reference opinions for the strategy change, avoids inappropriate results possibly caused by directly modifying the business process rule, saves manpower by directly simulating the business process, and avoids the problems of long period and strong subjectivity caused by manual analysis.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 schematically shows an application scenario example of a business process simulation method.
Fig. 2 schematically shows a flow chart of a business process simulation method.
Fig. 3 schematically shows a flow chart of a business process simulation method.
FIG. 4 schematically illustrates a flow chart of a business process simulation method.
FIG. 5 schematically illustrates a flow chart of a business process simulation method.
FIG. 6 schematically illustrates a flow chart of a business process simulation method.
FIG. 7 schematically illustrates a flow chart of a business process simulation method.
Fig. 8 schematically shows a block diagram of a business process simulation apparatus.
Fig. 9 schematically shows an example block diagram of an electronic device for implementing the agent allocation method.
Fig. 10 schematically illustrates a computer-readable storage medium for implementing the agent allocation method described above.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
Fig. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied.
As shown in fig. 1, the system architecture may include a terminal 101 (the terminal 101 may be a smartphone as shown in fig. 1, in other embodiments of the present application, the terminal 101 may also be a tablet, a portable computer, a desktop computer, etc.), a network 102, and a server 103. Network 102 serves as a medium for providing communication links between terminals 101 and servers 103. Network 102 may include, but is not limited to: a wireless network, a wired network, including but not limited to at least one of: wide area networks, metropolitan area networks, and local area networks. The wireless network includes, but is not limited to, at least one of: bluetooth, WI-FI, near field Communication (NFC for short). A user may use the terminal 101 to interact with the server 103 via the network 102 to receive or send messages or the like.
It should be understood that the number of terminals 101, networks 102 and servers 103 in fig. 1 is merely illustrative. There may be any number of terminals 101, networks 102, and servers 103, as desired for implementation. For example, the server 103 may be a server cluster composed of a plurality of servers.
In an embodiment of the present disclosure, the terminal 101 sends the expected service target to the server 103, and the server 103 obtains a historical service flow scheme according to the expected service target, where the historical service flow scheme includes historical service flow rules.
In an embodiment of the present disclosure, the server 103 receives a modification instruction of a configuration item of a historical business process rule, generates a new business process rule, and obtains a corresponding new business process scheme according to the new business process rule.
In an embodiment of the present disclosure, the server 103 performs service processing by using a new service flow scheme to obtain a corresponding service result, determines an influence of a new service flow rule on an expected service target according to the service result, and sends a result of the influence to the terminal 101.
In the present exemplary embodiment, a business process simulation method is first provided, where the business process simulation method may be run on a server, or may also be run on a server cluster or a cloud server, and of course, a person skilled in the art may also run the method of the present invention on other platforms according to needs, and this is not particularly limited in the present exemplary embodiment. Referring to fig. 1, the business process simulation method may include the following steps:
step S210, obtaining a historical service flow scheme according to an expected service target, wherein the historical service flow scheme comprises historical service flow rules;
step S220, replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule;
step S230, performing service processing according to the new service flow scheme to obtain a corresponding service result;
and step S240, determining the influence of the new business process rule on the expected business target according to the business result.
Hereinafter, each step in the business process simulation method described above in the present exemplary embodiment will be explained and explained in detail with reference to the drawings.
In step S210, a historical business process scheme is obtained according to the expected business target, where the historical business process scheme includes historical business process rules.
In the present exemplary embodiment, the business objectives are intended to describe the business desirability that the business process would like to achieve, and one business objective includes: identifying a name, a domain, a description, input data, and output data, the input and output data being a set of variables whose attributes include: the identification, description, name, type, length and initial value, the input data can be the information input by the user, and the expected service target is resolved according to the information input by the user.
The historical business process scheme is a business process scheme stored in a business system, the business process scheme comprises business process rules, the business process rules can be various factors related to business in the business system, taking the business system as a loan system as an example, the loan system can have wind control factors, regional policy factors, fund chain factors, insurance party factors, guarantee party factors, development channel factors and the like, a plurality of guarantors, insurance parties and fund parties can be accessed simultaneously in a large-scale loan system, and each credit increase party (guarantor, insurance party and the like) and each fund party (bank, P2P, trust and the like) can open business cities, acceptable credit increase parties and fund parties, acceptable loan terms, loan purposes, requirements of local laws and regulations, monthly daily loan amount and the like. The business process rules are set according to the business related factors.
It should be understood that the business process rules may differ in different business scenarios.
In an embodiment of the present disclosure, the manner of obtaining the historical service flow scheme according to the expected service target may be to obtain a historical service sample matched with the expected service target, and then determine the historical service flow scheme according to the historical service sample, referring to fig. 3, step S210 specifically includes:
step S2101, according to the expected service target, inquiring a historical service sample matched with the expected service target;
and step S2102, inputting the historical business sample into a machine learning model to obtain a historical business process scheme output by the machine learning model.
In step S2101, a historical traffic sample matching an expected traffic target is queried according to the expected traffic target.
Specifically, the matching with the expected business objective may be to match the historical business sample according to the relevant characteristics of the expected business objective, wherein the relevant characteristics of the expected business objective may include region, time, specific conditions, and the like. The query mode can be that the query is carried out from a business database, the data obtained by sampling according to various characteristics in advance is stored in the business database, and the historical business sample matched with the expected business target can be rapidly and directly queried from the database.
The historical traffic sample is traffic data that has been saved in advance by data sampling. The data samples may include natural historical data samples and scene-specific analog samples. The natural historical data sampling can be performed on historical business data according to dimensions such as regions, time and the like by using a 6 sigma principle, and natural experience data of specific time and region range are extracted, for example, the historical business data is sampled by using 6 sigma in 3 months nationwide; the scenario-specific analog sampling may sample historical service data according to region, time and specific conditions, wherein the specific conditions correspond to a specific scenario, for example, historical service data of business-related customers are sampled at 3 months nationwide.
In step S2102, the historical business samples are input into a machine learning model, and a historical business process scenario output by the machine learning model is obtained.
In an embodiment of the present disclosure, after the historical service sample is obtained in step S2101, the historical service sample is input into the machine learning model, so that the historical service flow scheme output by the machine learning model can be obtained. In one particular embodiment, the machine learning model may be a C4.5 decision tree model. C4.5 is a series of algorithms used to classify problems in machine learning and data mining, whose goal is supervised learning. That is, given a data set, each tuple therein can be described by a set of attribute values, each tuple belonging to a certain one of mutually exclusive classes. The goal of C4.5 is to find a mapping from attribute values to classes by learning, and this mapping can be used to classify new classes of unknown entities. C4.5 is proposed on the basis of ID3, and unlike ID3, the basis adopted by C4.5 in dividing the data set is an information gain ratio, so that the phenomenon that the ID3 algorithm tends to select features with more probability of taking values can be avoided.
The decision tree is constructed using the C4.5 algorithm. A decision tree is a flow-graph-like tree structure in which each internal node (non-leaf node) represents a test on an attribute, each branch represents a test output, and each leaf node holds a class label. Once the decision tree is built, for a tuple without a given class label, a path is traced from the root node to the leaf node, which stores the prediction of the tuple. In one embodiment, a C4.5 decision tree model training method includes:
1) creating a node N;
2) if the training set is empty, marking the returned node N as Failure;
3) if all records in the training set belong to the same category, marking the node N according to the category;
4) if the candidate attribute is null, returning N as a leaf node, and marking the leaf node as the most common class in the training set;
5) the for reach candidate attribute _ list;
6) if the if candidate attribute is continuous then if the attribute is continuous;
7) discretizing the attribute: a value can be determined as a split point SplitPoint, and two branches are generated according to the split point being greater than the SplitPoint and less than or equal to the SplitPoint;
8) selecting the Attribute D with the highest information gain ratio in the candidate attributes Attribute _ list;
9) marking the node N as an attribute D;
10) a consistent value D of the for attribute D;
11) a branch with the condition that D is D is grown from a node N;
12) let s be the set of training samples in the training set D ═ D;
13) if s is null;
14) adding a leaf, and marking the leaf as the most common class in the training set;
15) else adds a point where C4.5(R- { D }, C, s) returns.
Wherein, the calculation process of the C4.5 according to the information gain ratio is as follows:
1) computing class information entropy for (D)
The category information entropy represents the sum of the uncertainties of the various categories present in all samples. According to the concept of entropy, the larger the uncertainty, and the more information is needed to make things clear.
2) Calculating information entropy for of each attribute
The information entropy of each attribute corresponds to a conditional entropy. He indicates the sum of the uncertainties that occur for each category under certain attribute conditions. The larger the information entropy of an attribute, the less "pure" the sample class that is owned in this attribute.
3) Calculating information gain (attribute) for in (d) -in (attribute)
Entropy-conditional entropy of information gain, here category information entropy-attribute information entropy, indicates the degree of information uncertainty reduction. If the information gain of an attribute is larger, the attribute is used for carrying out sample division, so that the uncertainty of divided samples can be better reduced, and of course, the attribute is selected to more quickly and better complete the classification target.
4) Computing attribute split information metric H
The splitting information metric is used to consider the number information and size information of branches when a certain attribute is split, and the information is called intrinsic information (intrinsic information) of the attribute. The information gain rate information gain/intrinsic information will cause the importance of the attribute to decrease with the increase of the intrinsic information (i.e., if the uncertainty of the attribute itself is large, i tend to select it less), thus compensating for the information gain alone.
5) The information gain ratio IGR (attribute) is calculated as gain/H.
With continued reference to fig. 2, in step S220, the historical business process rule is replaced with a new business process rule, so as to obtain a new business process scheme corresponding to the new business process rule.
The disclosed invention aims to simulate the business process, and the business process is a business flow composed of business process rules, so that a new business process scheme can be obtained by changing the business process rules in the simulated business process, thereby realizing the business process simulation.
In an embodiment of the present disclosure, referring to fig. 4, step S220 specifically includes:
step S2201, receiving modification of the configuration items of the historical business process rules, and generating new business process rules;
and step S2202, obtaining a new business process scheme corresponding to the new business process rule according to the new business process rule.
These steps are explained in detail below.
In step S2201, a modification to the configuration item of the historical business process rule is received, and a new business process rule is generated.
Specifically, as described above, the historical business process rules are rules that have been generated in the business system, and these rules correspond to the relevant configuration items, so that when the business process is simulated, new business process rules can be generated by modifying the configuration items of the historical business process rules.
In step S2202, a new business process scenario corresponding to the new business process rule is obtained according to the new business process rule.
The new business process scheme generated after the historical business process rules are modified may not achieve the expected business target, but better meets the current actual requirements.
With continued reference to fig. 2, in step S230, service processing is performed according to the new service flow scheme, so as to obtain a corresponding service result.
After the new business process scheme corresponding to the new business process rule is obtained through step S220, simulation analysis may be performed on the new business process scheme to determine whether the new business process scheme can achieve the desired business objective. Therefore, the service processing can be performed according to the new service flow scheme, so that a corresponding service processing result is obtained.
In an embodiment of the present disclosure, the service processing is performed by using a new service flow scheme, which may be processing for a historical service sample, on one hand, the historical service sample data is the existing service sample data and is real service data, and processing the historical service sample data by using the new service flow scheme is more real and scientific and closer to the actual service development condition, and the historical service sample can be directly and conveniently obtained, and on the other hand, the data size of the historical service sample is large, and a plurality of simulation results can be obtained by performing simulation analysis on each historical service sample, so as to improve the accuracy of the simulation result, referring to fig. 5, step S230 specifically includes:
step S2301, obtaining historical business samples.
In one embodiment, since the historical traffic sample is data that has been previously stored, it can be retrieved directly from the database.
Step S2302, the historical service sample is subjected to service processing according to the new service flow scheme, and a service result corresponding to the historical service sample is obtained.
In this embodiment, the historical service samples are substituted into the new service flow scheme to obtain service results corresponding to each historical service sample.
With continued reference to fig. 2, in step S240, the influence of the new business process rule on the expected business objective is determined according to the business result.
In this embodiment, since the business result is a result obtained by the new business process scenario, the impact of the new business process scenario on the desired business objective may be determined based on the business result.
In a particular embodiment, the impact of the new business process rules on the expected business goals may include being feasible or infeasible, etc.
In an embodiment of the present disclosure, referring to fig. 6, step S240 specifically includes:
step S2401, analyzing the service result according to a predetermined statistical analysis method to obtain an analysis result;
step S2402, determining the influence of the new business process rule on the expected business target according to the analysis result.
In step S2401, the service result is analyzed according to a predetermined statistical analysis method to obtain an analysis result.
Specifically, the predetermined statistical analysis method may be to summarize and display the service result through a statistical form, or calculate the difference between the service result and the expected service target according to a predetermined analysis calculation method.
In step S2402, the influence of the new business process rule on the expected business objective is determined according to the analysis result.
Specifically, after the service processing is performed according to the new service flow scheme and the corresponding service result is obtained, the service result is analyzed according to the predetermined statistical analysis method through step S2401, and after the analysis result is obtained, the influence of the new service flow rule on the expected service target can be directly determined according to the analysis result.
In a specific embodiment, the influence of the new business process rule on the expected business target is determined according to the analysis result, which may be displaying a report to a user, and determining whether the expected business target is met by the user, or comparing the difference with a predetermined threshold to determine the influence of the new business process rule on the expected business target, where the size of the predetermined threshold may be set according to an actual situation, and the embodiment of the present application is not limited herein.
And if the difference value between the calculated business result and the expected business target is smaller than a preset threshold value, the business result is close to the expected business target, and the influence of the new business process rule on the expected business target is determined to be that the new business process rule can realize the expected business target.
And if the difference value between the calculated business result and the expected business target is greater than or equal to a preset threshold value, the business result and the expected business target have a difference, and the influence of the new business process rule on the expected business target is determined to be that the new business process rule cannot achieve the expected business target.
According to the technical scheme in the embodiment, the historical business process rule is replaced by the new business process rule to obtain a new business process scheme corresponding to the new business process rule, then business processing is carried out according to the new business process scheme to obtain a corresponding business result, the influence of the new business process rule on an expected business target is determined according to the business result, business process simulation is provided for a business system, the result is predicted in advance, a reference opinion is provided for strategy change, an improper result possibly caused by directly modifying the business process rule is avoided, meanwhile, manpower is saved by directly simulating the business process, and the problems of long period and strong subjectivity caused by manual analysis are avoided.
The influence of the new business process rule on the expected business target may include feasibility or infeasibility, and after the influence of the new business process rule on the expected business target is determined, the technical solution of the present disclosure may further generate a recommended business process scheme, see fig. 7, which further includes:
step S710, if the influence of the new business process rule on the expected business target is that the new business process rule can realize the expected business target, performing business processing according to the new business process rule to realize the expected business target;
step S720, if the influence of the new business process rule on the expected business target is that the new business process rule can not realize the expected business target, adjusting the new business process rule.
In step S710, if the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target, performing business processing according to the new business process rule to achieve the expected business target.
In one embodiment, if the new business process rule can achieve the expected business goal, it indicates that the new business process rule is feasible, so the business process can be directly performed according to the new business process scheme corresponding to the new business process rule, thereby achieving the expected business goal.
In step S720, if the new business process rule fails to achieve the desired business goal, it indicates that the new business process rule is not feasible, so the new business process rule cannot be used for business processing, and the new business process rule needs to be adjusted, that is, steps S220 to S240 in the above embodiment need to be repeated until it is determined that the adjusted business process rule can achieve the desired business goal.
In this embodiment, whether recommendation is performed is determined according to the influence of the new business process rule on the expected business target, and if the new business process rule can achieve the expected business target, the new business process rule is recommended if the new business process rule is feasible.
The present disclosure also provides a business process simulation device. Referring to fig. 8, the business process simulation apparatus may include an acquisition module 810, a replacement module 820, a processing module 830, and a determination module 840. Wherein:
an obtaining module 810, configured to obtain a historical service flow scheme according to an expected service target, where the historical service flow scheme includes historical service flow rules;
a replacing module 820, configured to replace the historical business process rule with a new business process rule, so as to obtain a new business process scheme corresponding to the new business process rule;
the processing module 830 is configured to perform service processing according to the new service flow scheme to obtain a corresponding service result;
a determining module 840, configured to determine, according to the service result, an influence of the new service flow rule on the expected service target.
In one embodiment, the obtaining module 810 is configured to: inquiring a historical service sample matched with an expected service target according to the expected service target; and inputting the historical service samples into a machine learning model to obtain a historical service flow scheme output by the machine learning model.
In one embodiment, the replacement module 820 is configured to: receiving modification of the configuration items of the historical business process rules to generate new business process rules; and obtaining a new business process scheme corresponding to the new business process rule according to the new business process rule.
In one embodiment, the processing module 830 is configured to: acquiring a historical service sample; and performing service processing on the historical service sample according to the new service flow scheme to obtain a service result corresponding to the historical service sample.
In one embodiment, the determining module 840 includes: the analysis unit is used for analyzing the service result according to a preset statistical analysis method to obtain an analysis result; and the influence determining unit is used for determining the influence of the new business process rule on the expected business target according to the analysis result.
In one embodiment, the influence determination unit is configured to: taking the difference value between the business result and the expected business target as the analysis result; if the difference is smaller than the preset threshold value, determining that the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target.
In one embodiment, the apparatus further comprises: if the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target, performing business processing according to the new business process rule to achieve the expected business target; and if the influence of the new business process rule on the expected business target is that the new business process rule cannot realize the expected business target, adjusting the new business process rule.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 900 according to this embodiment of the invention is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.
As shown in fig. 9, the electronic device 900 is embodied in the form of a general purpose computing device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one memory unit 920, and a bus 930 that couples various system components including the memory unit 920 and the processing unit 910.
Wherein the storage unit stores program code that is executable by the processing unit 910 to cause the processing unit 910 to perform steps according to various exemplary embodiments of the present invention described in the above section "exemplary methods" of the present specification. For example, the processing unit 910 may perform step S210 as shown in fig. 2: acquiring a historical business flow scheme according to an expected business target, wherein the historical business flow scheme comprises historical business flow rules; step S220: replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule; step S230: performing service processing according to the new service flow scheme to obtain a corresponding service result; step S240: and determining the influence of the new business process rule on the expected business target according to the business result.
The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM)9201 and/or a cache memory unit 9202, and may further include a read only memory unit (ROM) 9203.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.
Referring to fig. 10, a program product 1000 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including AN object oriented programming language such as Java, C + +, or the like, as well as conventional procedural programming languages, such as the "C" language or similar programming languages.
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A business process simulation method, comprising:
acquiring a historical business flow scheme according to an expected business target, wherein the historical business flow scheme comprises historical business flow rules;
replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule;
performing service processing according to the new service flow scheme to obtain a corresponding service result;
and determining the influence of the new business process rule on the expected business target according to the business result.
2. The method of claim 1, wherein obtaining historical business process scenarios based on expected business objectives comprises:
inquiring a historical service sample matched with an expected service target according to the expected service target;
and inputting the historical service samples into a machine learning model to obtain a historical service flow scheme output by the machine learning model.
3. The method of claim 1, wherein the replacing the historical business process rule with the new business process rule to obtain a new business process scenario corresponding to the new business process rule comprises:
receiving modification of the configuration items of the historical business process rules to generate new business process rules;
and obtaining a new business process scheme corresponding to the new business process rule according to the new business process rule.
4. The method of claim 1, wherein the performing the service processing according to the new service flow scheme to obtain the corresponding service result comprises:
acquiring a historical service sample;
and performing service processing on the historical service sample according to the new service flow scheme to obtain a service result corresponding to the historical service sample.
5. The method of claim 1, wherein determining the impact of the new business process rule on the expected business objective based on the business result comprises:
analyzing the service result according to a preset statistical analysis method to obtain an analysis result;
and determining the influence of the new business process rule on the expected business target according to the analysis result.
6. The method of claim 5, wherein determining the impact of the new business process rule on the expected business objective based on the analysis comprises:
taking the difference value between the business result and the expected business target as the analysis result;
if the difference is smaller than the preset threshold value, determining that the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target.
7. The method of claim 1, further comprising:
if the influence of the new business process rule on the expected business target is that the new business process rule can achieve the expected business target, performing business processing according to the new business process rule to achieve the expected business target;
and if the influence of the new business process rule on the expected business target is that the new business process rule cannot realize the expected business target, adjusting the new business process rule.
8. A business process simulation apparatus, comprising:
the acquisition module is used for acquiring a historical business process scheme according to an expected business target, wherein the historical business process scheme comprises historical business process rules;
the replacing module is used for replacing the historical business process rule by using a new business process rule to obtain a new business process scheme corresponding to the new business process rule;
the processing module is used for carrying out service processing according to the new service flow scheme to obtain a corresponding service result;
and the determining module is used for determining the influence of the new business process rule on the expected business target according to the business result.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the business process simulation method of any one of claims 1 to 7.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the business process simulation method of any of claims 1-7 via execution of the executable instructions.
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