CN112712347A - Salary calculation method, device, equipment and medium based on AI - Google Patents
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Abstract
The invention provides a salary calculation method, a salary calculation device, salary calculation equipment and a salary calculation medium based on AI, wherein the method comprises the following steps: providing a payroll creating module for creating different types of payrolls according to the employee types by a user; providing a payroll calculation formula setting module for a user to set and obtain corresponding step calculation formulas and generate the priority of each step calculation formula; providing a data acquisition module, acquiring salary detailed item data of different employees through a data interface and filling the salary detailed item data into paytables of corresponding types; providing a final compensation result calculation module, and performing gradual calculation according to the step-by-step calculation formula and the corresponding priority; and meanwhile, backing up the data obtained by each step of calculation to obtain historical node data, monitoring through an AI algorithm, and when an abnormality is found, backing the abnormal historical node data to a corresponding time node in time and prompting a problem. The invention greatly reduces the complexity of the formula and greatly improves the fault-tolerant rate by monitoring abnormal data.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a salary calculation method, device, equipment and medium based on AI.
Background
The salary management system is dynamic electronic dynamic management for determining, distributing and adjusting the salary payment principle, the salary strategy, the salary level, the salary structure and the salary composition of the staff under the guidance of an organization development strategy, thereby simplifying and reducing the workload and the complex workflow for arranging a large amount of paper data and inputting repeated work to the maximum extent.
At present, the salary issuing statistics of hospitals adopts an excel entry manual calculation mode, the salary of employees in each month is calculated according to the basic wages, post wages, subsidies, performance and other composition items of the employees in the hospitals, and a process of recording statistics, auditing and final issuing from a financial department is adopted.
However, the above method still has many disadvantages: when the number of staff in a hospital is large, data is huge, for the contact calculation among different projects, a complex formula needs to be set to realize calculation, a large amount of manpower is consumed in the process, and abnormal data cannot be cleared in the calculation process of the multiple formulas. In addition, some complex formulas are difficult to realize through excel calculation, after settlement in the month, basic data and formulas among columns cannot be inherited to the next month, and manual matching of each column and the formulas among the columns is needed, so that labor consumed in the repeated working process is a great loss.
Disclosure of Invention
The invention aims to solve the technical problem of providing a salary calculation method, a salary calculation device, salary calculation equipment and salary calculation medium based on AI, which are used for rapidly debugging by setting the calculation rules of columns, adopting a step-by-step calculation formula to reduce the complexity and setting a corresponding monitoring function.
In a first aspect, the present invention provides an AI-based compensation calculation method, including the following steps:
s1, providing a payroll creating module for creating different types of payrolls according to employee types, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
s2, providing a payroll calculation formula setting module for a user to set and obtain corresponding step calculation formulas according to the checking relationship among payroll columns and generate the priority of each step calculation formula;
s3, providing a data acquisition module, acquiring salary detail data of different employees through a data interface, and filling the salary detail data into paytables of corresponding types;
s4, providing a final salary result calculation module, calculating step by step according to the step calculation formula and the corresponding priority to obtain the final salary results of different employees and storing the final salary results; in the step-by-step calculation process, data obtained by each step of calculation is backed up to obtain historical node data, each historical node data is monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to a corresponding time node and a problem is prompted.
In a second aspect, the present invention provides an AI-based compensation calculation apparatus, comprising:
the system comprises a payroll creating module, a payroll determining module and a payroll selecting module, wherein the payroll creating module is used for creating different types of payroll according to employee types by a user, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
the payroll calculation formula setting module is used for setting and obtaining corresponding step calculation formulas by a user according to the checking relationship among the payroll columns and generating the priority of each step calculation formula;
the data acquisition module acquires salary detailed item data of different employees through the data interface and fills the salary tables of corresponding types;
the final salary result calculation module is used for carrying out gradual calculation according to the step-by-step calculation formula and the corresponding priority to obtain and store final salary results of different employees;
and the monitoring module is used for backing up the data obtained by each step of calculation to obtain historical node data in the process of performing step-by-step calculation, monitoring each historical node data through an AI algorithm, and returning the abnormal historical node data to a corresponding time node in time and prompting the problem when the historical node data are abnormal.
In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of the first aspect when executing the program.
In a fourth aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the first aspect.
One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages: according to the embodiment of the application, the data result of the target column is calculated according to the input basic data and the set calculation rule and according to a certain priority, in the process of gradual calculation, data obtained by calculation in each step are backed up to obtain historical node data, the historical node data are monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to the corresponding time node, so that the detail errors which are difficult to find by manual processing can be quickly found, and the fault tolerance of the operation is greatly improved. And the data can be ensured to be correct through the auditing and rechecking of financial staff, and finally the settlement and the issuing of the month compensation, the statistics of data report forms and the historical data of the file reservation can be carried out.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
The invention will be further described with reference to the following examples with reference to the accompanying drawings.
FIG. 1 is a schematic overall flow chart of a method according to a first embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a formula setting page according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an apparatus according to a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to a third embodiment of the invention;
fig. 6 is a schematic structural diagram of a medium according to a fourth embodiment of the present invention.
Detailed Description
The embodiment of the application provides a salary calculation method, a salary calculation device, salary calculation equipment and a salary calculation medium based on AI, and by setting a calculation rule of columns, a stepwise calculation formula is adopted to reduce complexity and set a corresponding monitoring function, so that mistakes are quickly eliminated.
The technical scheme in the embodiment of the application has the following general idea: according to the input basic data, through a set calculation rule, a data result of a calculation target column is achieved according to a certain priority, in the process of gradual calculation, data obtained by each step of calculation are backed up to obtain historical node data, each historical node data is monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to corresponding time nodes, so that detail errors which are difficult to find by manual processing can be quickly found, and the fault tolerance of operation is greatly improved.
Example one
As shown in fig. 1 and fig. 2, the embodiment provides an AI-based compensation calculation method, which includes the following steps:
s1, providing a payroll creating module for creating different types of payrolls according to employee types, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
for example: dividing according to the personnel types, creating internal and external payroll tables, columns A, B, C, and D.
Then, corresponding personnel can be loaded and basic data can be input, and the following basic data are assumed to exist:
monthly staff pay-per-view A column, B column, C tax due to D
Knitted fabric 3500.003000.00
3400.003800.00 in Lei-Si-1.
S2, providing a payroll calculation formula setting module for a user to set and obtain corresponding step calculation formulas according to the checking relationship among payroll columns and generate the priority of each step calculation formula;
for example, the set column calculation formula is as follows:
1. c response total ═ A column + B column
2. D, getting the tax (C should be added).
S3, providing a data acquisition module, acquiring salary detail data of different employees through a data interface, and filling the salary detail data into paytables of corresponding types;
s4, providing a final salary result calculation module, calculating step by step according to the step calculation formula and the corresponding priority to obtain the final salary results of different employees and storing the final salary results; in the step-by-step calculation process, data obtained by each step of calculation is backed up to obtain historical node data, each historical node data is monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to a corresponding time node and a problem is prompted.
For example, the final compensation result is calculated as follows:
monthly staff pay-per-view A column, B column, C tax due to D
Knitted fabric 3500.003000.006500.0045.00
3400.003800.007200.0066.00 in Lei-Si-1.
As a preferred implementation manner of this embodiment, the method further includes:
s5, providing an approval issuing module for the department to check the stored final salary result data according to the month, and after the summarized data is correct, the financial chief can check the result, settle the account and issue the monthly salary;
for example, after aggregation, payroll table within month 1, column a, 6900.00, column B, 6800.00, column C, 13700.00, column D, 111.00; and (4) the finance chief approves, issues and settles data in 1 month.
S6, providing a report statistics module, and establishing a periodic ratio report with different dimensions according to the monthly compensation data of the employee.
For example: 1. comparing the monthly data with the last year data; 2. doctors and nurses pay statistics; 3. and summarizing and counting the amount among departments.
As a more preferred or more specific implementation manner of this embodiment, in step S4, the specific process of monitoring each piece of history node data is: setting an early warning rule for each calculation step of the step calculation formula in an early warning library, judging whether the historical node data belongs to an early warning range or not according to the early warning rule after each calculation step of the formula is finished, if so, giving a warning and providing an option of 'skipping early warning' for a user to select, and if the user chooses to skip, recording the corresponding early warning rule into a rule library, and perfecting the early warning rule through an AI algorithm.
As shown in fig. 3, as a more preferred or specific implementation manner of this embodiment, the payroll formula setting module divides the formula setting page into upper, middle and lower 3 regions by the front-end technology of EXTJS;
the upper area is divided into a formula list, an option list and an operation list; wherein the formula list is used for selecting the set type of the step calculation formula, the option list is used for filling the input formula content, and the operation list is used for positioning and modifying a part in the step calculation formula;
the middle area is divided into two columns of formula definition and formula analysis results, and the two column scroll bars automatically roll in a linkage manner, and when a certain row in any column is clicked, the state of defining and modifying the content of the row is achieved;
the lower area is divided into a text field and an analysis field, the text field and the analysis field can freely input formulas, and then the system carries out association identification according to the existing columns.
Based on the same inventive concept, the application also provides a device corresponding to the method in the first embodiment, which is detailed in the second embodiment.
Example two
As shown in fig. 4, in the present embodiment, an AI-based compensation calculating apparatus is provided, including:
the system comprises a payroll creating module, a payroll determining module and a payroll selecting module, wherein the payroll creating module is used for creating different types of payroll according to employee types by a user, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
the payroll calculation formula setting module is used for setting and obtaining corresponding step calculation formulas by a user according to the checking relationship among the payroll columns and generating the priority of each step calculation formula;
the data acquisition module acquires salary detailed item data of different employees through the data interface and fills the salary tables of corresponding types;
the final salary result calculation module is used for carrying out gradual calculation according to the step-by-step calculation formula and the corresponding priority to obtain and store final salary results of different employees;
and the monitoring module is used for backing up the data obtained by each step of calculation to obtain historical node data in the process of performing step-by-step calculation, monitoring each historical node data through an AI algorithm, and returning the abnormal historical node data to a corresponding time node in time and prompting the problem when the historical node data are abnormal.
As a preferred implementation manner of this embodiment, the apparatus further includes:
the approval issuing module is used for checking the stored final salary result data according to months by departments, settling accounts and issuing the monthly salary after the summarized data is correct and the auditing is passed by the financial chief;
and the report counting module is used for establishing a periodic ratio report with different dimensions according to the salary data of each month of the employee.
As a more preferred or specific implementation manner of this embodiment, the specific process of the monitoring module monitoring each historical node data is as follows: setting an early warning rule for each calculation step of the step calculation formula in an early warning library, judging whether the historical node data belongs to an early warning range or not according to the early warning rule after each calculation step of the formula is finished, if so, giving a warning and providing an option of 'skipping early warning' for a user to select, and if the user chooses to skip, recording the corresponding early warning rule into a rule library, and perfecting the early warning rule through an AI algorithm.
As shown in fig. 3, as a more preferred or specific implementation manner of this embodiment, the payroll formula setting module divides the formula setting page into upper, middle and lower 3 regions through the front-end technology of EXTJS;
the upper area is divided into a formula list, an option list and an operation list; wherein the formula list is used for selecting the set type of the step calculation formula, the option list is used for filling the input formula content, and the operation list is used for positioning and modifying a part in the step calculation formula;
the middle area is divided into two columns of formula definition and formula analysis results, and the two column scroll bars automatically roll in a linkage manner, and when a certain row in any column is clicked, the state of defining and modifying the content of the row is achieved;
the lower area is divided into a text field and an analysis field, the text field and the analysis field can freely input formulas, and then the system carries out association identification according to the existing columns.
Since the apparatus described in the second embodiment of the present invention is an apparatus used for implementing the method of the first embodiment of the present invention, based on the method described in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the apparatus, and thus the details are not described herein. All the devices adopted in the method of the first embodiment of the present invention belong to the protection scope of the present invention.
Based on the same inventive concept, the application provides an electronic device embodiment corresponding to the first embodiment, which is detailed in the third embodiment.
EXAMPLE III
The embodiment provides an electronic device, as shown in fig. 5, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, any one of the first embodiment modes may be implemented.
Since the electronic device described in this embodiment is a device used for implementing the method in the first embodiment of the present application, based on the method described in the first embodiment of the present application, a specific implementation of the electronic device in this embodiment and various variations thereof can be understood by those skilled in the art, and therefore, how to implement the method in the first embodiment of the present application by the electronic device is not described in detail herein. The equipment used by those skilled in the art to implement the methods in the embodiments of the present application is within the scope of the present application.
Based on the same inventive concept, the application provides a storage medium corresponding to the fourth embodiment, which is described in detail in the fourth embodiment.
Example four
The present embodiment provides a computer-readable storage medium, as shown in fig. 6, on which a computer program is stored, and when the computer program is executed by a processor, any one of the embodiments can be implemented.
The technical scheme provided in the embodiment of the application at least has the following technical effects or advantages: according to the embodiment of the application, the data result of the target column is calculated according to the input basic data and the set calculation rule and according to a certain priority, in the process of gradual calculation, data obtained by calculation in each step are backed up to obtain historical node data, the historical node data are monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to the corresponding time node, so that the detail errors which are difficult to find by manual processing can be quickly found, and the fault tolerance of the operation is greatly improved. And the data can be ensured to be correct through the auditing and rechecking of financial staff, and finally the settlement and the issuing of the month compensation, the statistics of data report forms and the historical data of the file reservation can be carried out. As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus or system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.
Claims (10)
1. An AI-based compensation calculation method, comprising: the method comprises the following steps:
s1, providing a payroll creating module for creating different types of payrolls according to employee types, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
s2, providing a payroll calculation formula setting module for a user to set and obtain corresponding step calculation formulas according to the checking relationship among payroll columns and generate the priority of each step calculation formula;
s3, providing a data acquisition module, acquiring salary detail data of different employees through a data interface, and filling the salary detail data into paytables of corresponding types;
s4, providing a final salary result calculation module, calculating step by step according to the step calculation formula and the corresponding priority to obtain the final salary results of different employees and storing the final salary results; in the step-by-step calculation process, data obtained by each step of calculation is backed up to obtain historical node data, each historical node data is monitored through an AI algorithm, and when the historical node data are found to be abnormal, the abnormal historical node data are timely returned to a corresponding time node and problem prompt is carried out.
2. The AI-based compensation calculation method of claim 1, wherein: in step S4, the specific process of monitoring each of the historical node data by an AI algorithm is as follows: setting an early warning rule for each calculation step of the step calculation formula in an early warning library, judging whether the historical node data belongs to an early warning range or not according to the early warning rule after each calculation step of the formula is finished, if so, giving a warning and providing an option of 'skipping early warning' for a user to select, and if the user chooses to skip, recording the corresponding early warning rule into a rule library, and perfecting the early warning rule through an AI algorithm.
3. The AI-based compensation calculation method of claim 1, wherein: further comprising:
s5, providing an approval issuing module for the department to check the stored final salary result data according to the month, and after the summarized data is correct, the financial chief can check the result, settle the account and issue the monthly salary;
s6, providing a report statistics module, and establishing a periodic ratio report with different dimensions according to the monthly compensation data of the employee.
4. The AI-based compensation calculation method of claim 3, wherein: the payroll calculation formula setting module divides a formula setting page into an upper area, a middle area and a lower area through the front-end technology of EXTJS;
the upper area is divided into a formula list, an option list and an operation list; wherein the formula list is used for selecting the set type of the step calculation formula, the option list is used for filling the input formula content, and the operation list is used for positioning and modifying a part in the step calculation formula;
the middle area is divided into two columns of formula definition and formula analysis results, and the two column scroll bars automatically roll in a linkage manner, and when a certain row in any column is clicked, the state of defining and modifying the content of the row is achieved;
the lower area is divided into a text field and an analysis field, the text field and the analysis field can freely input formulas, and then the system carries out association identification according to the existing columns.
5. An AI-based compensation calculation apparatus, comprising: the method comprises the following steps:
the system comprises a payroll creating module, a payroll determining module and a payroll selecting module, wherein the payroll creating module is used for creating different types of payroll according to employee types by a user, setting different payroll columns on the payroll to record payroll items of employees and setting checking relations among the payroll columns;
the payroll calculation formula setting module is used for setting and obtaining corresponding step calculation formulas by a user according to the checking relationship among the payroll columns and generating the priority of each step calculation formula;
the data acquisition module acquires salary detailed item data of different employees through the data interface and fills the salary tables of corresponding types;
the final salary result calculation module is used for carrying out gradual calculation according to the step-by-step calculation formula and the corresponding priority to obtain and store final salary results of different employees;
and the monitoring module is used for backing up the data obtained by each step of calculation to obtain historical node data in the process of performing step-by-step calculation, monitoring each historical node data through an AI algorithm, and returning the abnormal historical node data to a corresponding time node in time and prompting the problem when the historical node data are abnormal.
6. The AI-based compensation calculation apparatus of claim 5, wherein: the specific process of the monitoring module for monitoring each historical node data through an AI algorithm is as follows: setting an early warning rule for each calculation step of the step calculation formula in an early warning library, judging whether the historical node data belongs to an early warning range or not according to the early warning rule after each calculation step of the formula is finished, if so, giving a warning and providing an option of 'skipping early warning' for a user to select, and if the user chooses to skip, recording the corresponding early warning rule into a rule library, and perfecting the early warning rule through an AI algorithm.
7. The AI-based compensation calculation apparatus of claim 5, wherein: further comprising:
the approval issuing module is used for checking the stored final salary result data according to months by departments, settling accounts and issuing the monthly salary after the summarized data is correct and the auditing is passed by the financial chief;
and the report counting module is used for establishing a periodic ratio report with different dimensions according to the salary data of each month of the employee.
8. The AI-based compensation calculation apparatus of claim 5, wherein: the payroll calculation formula setting module divides a formula setting page into an upper area, a middle area and a lower area through the front-end technology of EXTJS;
the upper area is divided into a formula list, an option list and an operation list; wherein the formula list is used for selecting the set type of the step calculation formula, the option list is used for filling the input formula content, and the operation list is used for positioning and modifying a part in the step calculation formula;
the middle area is divided into two columns of formula definition and formula analysis results, and the two column scroll bars automatically roll in a linkage manner, and when a certain row in any column is clicked, the state of defining and modifying the content of the row is achieved;
the lower area is divided into a text field and an analysis field, the text field and the analysis field can freely input formulas, and then the system carries out association identification according to the existing columns.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 4 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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| CN114066590A (en) * | 2021-11-30 | 2022-02-18 | 中国平安财产保险股份有限公司 | Salary data processing method, device and equipment based on big data and storage medium |
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