CN117236778A - Intelligent settlement management system for flexible labor based on big data - Google Patents
Intelligent settlement management system for flexible labor based on big data Download PDFInfo
- Publication number
- CN117236778A CN117236778A CN202311286159.XA CN202311286159A CN117236778A CN 117236778 A CN117236778 A CN 117236778A CN 202311286159 A CN202311286159 A CN 202311286159A CN 117236778 A CN117236778 A CN 117236778A
- Authority
- CN
- China
- Prior art keywords
- module
- data
- terminal
- user
- evaluation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000011156 evaluation Methods 0.000 claims abstract description 91
- 238000012544 monitoring process Methods 0.000 claims abstract description 45
- 238000007726 management method Methods 0.000 claims abstract description 41
- 238000000034 method Methods 0.000 claims abstract description 23
- 230000007115 recruitment Effects 0.000 claims description 15
- 238000012806 monitoring device Methods 0.000 claims description 12
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000012795 verification Methods 0.000 claims description 9
- 230000003044 adaptive effect Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000013523 data management Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 238000013075 data extraction Methods 0.000 description 2
- 238000011068 loading method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of big data management, in particular to a flexible labor-based intelligent settlement management system which comprises a data acquisition module, a cloud database, a monitoring module, a reminding module, a settlement module, an evaluation module, a user side evaluation database and a self-adaptive module, wherein the data acquisition module, the monitoring module, the settlement module and the reminding module are electrically connected with the cloud database, and the monitoring module is electrically connected with the reminding module. According to the invention, the evaluation module, the user terminal evaluation database and the self-adaptive module are directly matched, so that each user terminal can be evaluated, and the high-quality user terminal can be objectively screened out, the number of steps of the user in the operation process is reduced, the self-adaptive matching of the high-quality user terminal is directly realized, the operation tasks are distributed to the high-quality user terminal, and the parameter data required in the settlement can be calibrated in the settlement process through the settlement module.
Description
Technical Field
The invention relates to the technical field of big data management, in particular to an intelligent settlement management system based on big data and flexible labor.
Background
The large data or huge amount of data refers to the fact that the related data is huge in size and cannot penetrate through a main stream software tool, the information which is more positive in helping business decision making of enterprises is obtained, managed, processed and tidied in reasonable time, flexible employment is taken as a brand new employment mode, the brand new employment mode is different from the traditional employment mode of the enterprises, the enterprises adopt a mode which does not establish labor relation and adopts more flexible employment according to production and operation conditions of the enterprises, the mode can solve a plurality of problems for the enterprises, the business mode is more accurate due to the appearance of flexible employment platforms, and the working and settlement efficiency of users and the enterprises is improved.
The flexible and labor-saving intelligent settlement management system in the prior art has the following defects in the use process:
(1) In the process of performing intelligent settlement management, a plurality of steps, including data extraction, conversion, loading and the like, are generally required to be performed in the process of performing settlement management on the existing user terminal, and complicated codes and conversion rules are required to be written in the process of using the steps, so that time-consuming problems and error-prone problems exist due to the complexity;
(2) In the process of intelligent settlement management, data can undergo a plurality of steps to be calculated and processed, and the data volume is huge, so that the data is easy to lose, the problems of integrity and consistency of the data are caused, and the final settlement result of a settlement management system can be influenced if the data is lost.
The publication number is: the invention discloses a settlement management system for flexible labor, which relates to a settlement management system for flexible labor, in particular to the technical field of settlement management for flexible labor, and comprises the following components: the acquisition module comprises an information acquisition unit for acquiring data information of enterprises and users and an image acquisition unit for acquiring finished images uploaded by the users; the analysis module is connected with the acquisition module and comprises a data operation unit for calculating the credibility of the task issued by the enterprise, a data comparison unit for comparing the credibility with a preset credibility and a deployment control unit for judging the credibility according to the result of the data comparison unit; the storage module is connected with the analysis module and used for storing historical data of enterprises and users; the early warning module is connected with the analysis module and used for carrying out early warning prompt on the enterprise and the user; the invention further improves the safety of the flexible working platform through the management of enterprises and users.
The publication number is: the invention discloses a signing method, a settlement method and a system of a flexible employment service center, in particular to a Chinese patent of CN114219414A, which relates to a flexible employment service center system, comprising a flexible employment end, a user end and a user end, wherein the flexible employment end is used for acquiring a request and related information sent by a flexible employment; the flexible industrial enterprise terminal is used for acquiring the request and related information of the flexible industrial enterprise; the signing module is used for receiving the flexible employment and the flexible employment enterprise to send a reception request, a service request and related information to match, generating a signing contract and completing signing; the settlement module is used for generating a settlement task list according to the successfully signed data and the acquired settlement request; the auditing module is used for auditing the settlement task form; the payment module is used for paying according to the checked and approved settlement task list; and the data storage and return module is used for storing data and returning data. The invention adopts the business processes under various flexible employment modes and can be freely combined and called, combines the actual employment scenes of the connection and settlement in each flexible employment enterprise, and greatly improves the flexibility of the system and has more compatibility.
The scheme can further improve the safety of the flexible employment platform through the management of enterprises and users, can adopt business processes under various different flexible employment modes and can be freely combined and called, combines the actual employment scenes of the connected and settled flexible employment enterprises, greatly improves the flexibility of the system and has compatibility, but fails to solve the problems in the prior art.
The present invention has been made in view of this.
Disclosure of Invention
The invention aims to provide an intelligent settlement management system based on big data and flexible labor, which solves the problems in the background technology.
In order to achieve the above object, one of the objects of the present invention is to provide a flexible and labor-saving intelligent settlement management system based on big data, comprising the following steps:
s1: firstly, establishing a big data platform for intelligent settlement management of flexible labor use;
s2: the data parameters of the terminal and the user side are acquired through a data acquisition module in a large data platform for flexible labor-saving intelligent settlement management, and all acquired data are integrated;
s3: storing each data integrated in the data acquisition module into a cloud database in a big data platform;
s4: connecting the cloud database with a monitoring module;
s5: monitoring a user side through a monitoring module, and connecting the monitoring module with a reminding module;
s6: after the user finishes the operation, the user will settle accounts through the settlement module;
s7: after settlement is completed, the user terminal is evaluated through an evaluation module in a big data platform, and the parameter data of the time is stored in a cloud database;
s8: then generating a user side evaluation database according to the evaluation of the user side by the evaluation module;
s9: dividing each user terminal into a high-quality user terminal and a common user terminal according to the evaluation parameter data of each user terminal in the user terminal evaluation database;
s10: collecting various parameter data of a high-quality user terminal through a self-adaptive module in a big data platform;
s11: and finally, carrying out self-adaptive matching on the high-quality user terminal through a self-adaptive module under the operation of the high-quality user terminal, and distributing operation tasks to the high-quality user terminal.
As a further improvement of the technical scheme, the big data platform in the S1 comprises a data acquisition module, a cloud database, a monitoring module, a reminding module, a settlement module, an evaluation module, a user side evaluation database and a self-adaptation module;
the data acquisition module, the monitoring module, the settlement module and the reminding module are electrically connected with the cloud database;
the monitoring module is electrically connected with the reminding module;
the self-adaptive module and the evaluation module are electrically connected with the user terminal evaluation database.
As a further improvement of the technical scheme, in S2, the specific steps for acquiring the data parameters of the terminal and the user side by the data acquisition module in the big data platform are as follows:
s2.1: firstly, acquiring labor parameter data of a terminal;
s2.2: analyzing the acquired labor parameter data of the terminal through an analysis module in a big data platform, so as to obtain standardized labor parameter data;
s2.3: secondly, acquiring parameter data of a user side;
s2.4: analyzing the acquired parameter data of the user terminal through an analysis module in a big data platform, so as to obtain standardized parameter data of the user terminal;
s2.5: and integrating the labor parameter data of the terminal and the parameter data of the user side.
As a further improvement of the technical scheme, in S2.1, the labor parameter data of the terminal and the standardized labor parameter data at least comprise labor type parameters of the terminal, personnel number parameters of the terminal, time interval parameter data of labor of the terminal and labor compensation parameter data of the terminal;
the parameter data of the user side and the standardized parameter data of the user side at least comprise user side personnel number parameters, user side demand parameter data, user side operation time interval parameter data and user side salary expected parameter data.
As a further improvement of the technical scheme, in S4, the monitoring module is used for acquiring the labor progress of each user end through the set monitoring device, acquiring the parameter data of the user end and the labor type parameter of the terminal in the cloud database through being connected with the cloud database, extracting the labor progress characteristics of the user end through the monitoring device set by the monitoring module, and transmitting the labor progress characteristics to the reminding module.
As a further improvement of the present technical solution, in S5, the operation flow of the reminding module is specifically as follows:
s5.1: firstly, a reminding module receives the user end labor progress feature extracted from a monitoring device arranged by a monitoring module;
s5.2: extracting the user end labor progress characteristics by a monitoring device arranged by a monitoring module and carrying out standardized treatment;
s5.3: setting the normalized user end labor progress characteristic points as；
S5.4: then, according to the operation time threshold value of the user side monitored by the monitoring module, extracting standard labor progress characteristics in the time threshold value from the cloud database;
s5.5: setting the extracted standard labor progress feature points as；
S5.6: characteristic points of standard labor progressWith user side recruitment progress feature pointComparing;
s5.7: and if the compared matching degree is smaller than the set threshold value, reminding the user side through a reminding module.
As a further improvement of the present technical solution, in S6, the settlement of the user terminal with the completed operation by the settlement module specifically includes the following steps:
s6.1: firstly, extracting graphic data parameters from the settled operation state by a monitoring module connected with a settlement module and matched with the set monitoring equipment;
s6.2: feature points in the extracted graphic data parametersExtracting;
s6.3: extracting standard recruitment settlement feature points in the connected cloud database through a settlement module；
S6.4: standard recruitment settlement feature pointsCalculating feature points with user endComparing;
s6.5: then, according to the compared difference value, determining the final operation state of the user terminal;
s6.6: and finally, extracting the recruitment parameter data of the terminal and the time interval parameter data of the recruitment of the terminal, which are acquired in the cloud database, as reference basis, and completing settlement for the operation of the user terminal by combining the compared difference values.
As a further improvement of the present technical solution, in S7, the evaluation module is configured to evaluate a service flow formed between the current ue and the terminal, and set an evaluation thresholdBased on the set evaluation thresholdEvaluating the current business processes of the user terminal and the terminal;
if the current business flow of the user terminal and the terminal is greater than the set evaluation threshold valueThe task user side and the terminal directly meet the index required by the terminal;
if the current business flow of the user and the terminal is smaller than the set evaluation threshold valueAnd if the task is that the current and the terminal direct business flow of the user terminal do not meet the index required by the terminal.
As a further improvement of the present technical solution, the evaluation threshold valueThe specific calculation mode is as follows:
(1) Firstly, extracting each item of data in an evaluation database of a user side, and adding a certain floating threshold value to obtain the proportion of high-quality data in the evaluation databaseThe specific formula is as follows:
；
in the formulaRepresented as all parameter data in the client evaluation database,represented as a floating threshold value,represented as a verification threshold;
(2) For high quality data proportion in evaluation databaseThe verification is carried out, and the specific formula is as follows:
if it isRepresenting the proportion of the high-quality data in the evaluation databaseIs unreasonable;
if it isRepresenting the proportion of the high-quality data in the evaluation databaseIs reasonable;
(3) Scaling of quality data in a pair-wise evaluation databaseAfter verification is completed, the evaluation threshold is extractedThe specific expression is as follows:
；
in the formulaRepresented as quantity parameter data of all clients in the cloud database,expressed as a proportion of quality data in an evaluation databaseAnd (5) reasonably learning floating parameters.
As a further improvement of the technical scheme, in S10 and S11, the adaptive module is configured to evaluate each operation condition of each user terminal according to the evaluation module, store the evaluated result into the evaluation database, divide each user terminal into a high-quality user terminal and a normal user terminal according to the data stored in the evaluation database by using the adaptive module as a basis, and adaptively adapt to the subsequent allocation operation of the high-quality user terminal.
Compared with the prior art, the invention has the beneficial effects that:
1. in the flexible labor-based intelligent settlement management system based on big data, through the settlement module, parameter data required to be used in settlement can be calibrated in the settlement process, so that the problems that the data are lost easily due to the fact that the calculation and the processing are carried out through a plurality of steps and the data quantity is huge are avoided, the integrity and the consistency of the data are caused, and the final settlement result of the settlement management system is affected after the data are lost are solved.
2. In the flexible labor-based intelligent settlement management system, the evaluation module, the user side evaluation database and the self-adaptive module are directly matched, so that all user sides can be evaluated, and the high-quality user sides can be objectively screened out, the number of steps is reduced in the operation process of the user, the self-adaptive matching of the high-quality user sides is directly realized, the task of the operation is distributed to the high-quality user sides, a plurality of steps, including data extraction, conversion, loading and the like, are usually required in the settlement management process of the existing user terminals, and the steps, including complex codes, conversion rules and the like, need to be written in the use process, so that the time-consuming problem and the error-prone problem are caused by the complexity.
Drawings
FIG. 1 is a schematic diagram of a flexible-to-use intelligent settlement management system for big data according to the invention;
FIG. 2 is a schematic flow diagram of the intelligent settlement management system for flexible employment of big data according to the present invention;
fig. 3 is a schematic diagram of specific steps of data acquisition of a terminal and a user by a data acquisition module in a big data platform according to the present invention;
FIG. 4 is a schematic diagram of specific steps in the operation flow of the reminding module according to the present invention;
fig. 5 is a schematic diagram of a specific step of the settlement module of the present invention for performing settlement on a user terminal having completed a job.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-5, one of the purposes of this embodiment is to provide a flexible and labor-saving intelligent settlement management system based on big data, which includes the following steps:
s1: firstly, establishing a big data platform for intelligent settlement management of flexible labor use;
s2: the data parameters of the terminal and the user side are acquired through a data acquisition module in a large data platform for flexible labor-saving intelligent settlement management, and all acquired data are integrated;
s3: storing each data integrated in the data acquisition module into a cloud database in a big data platform;
s4: connecting the cloud database with a monitoring module;
s5: monitoring a user side through a monitoring module, and connecting the monitoring module with a reminding module;
s6: after the user finishes the operation, the user will settle accounts through the settlement module;
s7: after settlement is completed, the user terminal is evaluated through an evaluation module in a big data platform, and the parameter data of the time is stored in a cloud database;
s8: then generating a user side evaluation database according to the evaluation of the user side by the evaluation module;
s9: dividing each user terminal into a high-quality user terminal and a common user terminal according to the evaluation parameter data of each user terminal in the user terminal evaluation database;
s10: collecting various parameter data of a high-quality user terminal through a self-adaptive module in a big data platform;
s11: and finally, carrying out self-adaptive matching on the high-quality user terminal through a self-adaptive module under the operation of the high-quality user terminal, and distributing operation tasks to the high-quality user terminal.
The big data platform in S1 comprises a data acquisition module, a cloud database, a monitoring module, a reminding module, a settlement module, an evaluation module, a user side evaluation database and a self-adaptive module;
the data acquisition module, the monitoring module, the settlement module and the reminding module are electrically connected with the cloud database;
the monitoring module is electrically connected with the reminding module;
the self-adaptive module and the evaluation module are electrically connected with the user terminal evaluation database.
In S4, the monitoring module is configured to obtain the labor progress of each user through the set monitoring device, and obtain the parameter data of the user and the labor type parameter of the terminal in the cloud database through being connected with the cloud database, and extract the labor progress feature of the user through the monitoring device set by the monitoring module, and transmit the labor progress feature to the reminding module.
In S7, the evaluation module evaluates the business process formed between the user terminal and the terminal and sets an evaluation thresholdBased on the set evaluation thresholdEvaluating the current business processes of the user terminal and the terminal;
if the current business flow of the user terminal and the terminal is greater than the set evaluation threshold valueTask the userThe direct business process between the terminal and the terminal meets the index required by the terminal;
if the current business flow of the user and the terminal is smaller than the set evaluation threshold valueAnd if the task is that the current and the terminal direct business flow of the user terminal do not meet the index required by the terminal.
Evaluation thresholdThe specific calculation mode is as follows:
(1) Firstly, extracting each item of data in an evaluation database of a user side, and adding a certain floating threshold value to obtain the proportion of high-quality data in the evaluation databaseThe specific formula is as follows:
；
in the formulaRepresented as all parameter data in the client evaluation database,represented as a floating threshold value,represented as a verification threshold;
(2) For high quality data proportion in evaluation databaseThe verification is carried out, and the specific formula is as follows:
if it isRepresenting the proportion of the high-quality data in the evaluation databaseIs unreasonable;
if it isRepresenting the proportion of the high-quality data in the evaluation databaseIs reasonable;
(3) Scaling of quality data in a pair-wise evaluation databaseAfter verification is completed, the evaluation threshold is extractedThe specific expression is as follows:
；
in the formulaRepresented as quantity parameter data of all clients in the cloud database,expressed as a proportion of quality data in an evaluation databaseAnd (5) reasonably learning floating parameters.
In S10 and S11, the adaptive module is configured to evaluate each operation condition of each user terminal according to the evaluation module, store the evaluated result in the evaluation database, divide each user terminal into a high-quality user terminal and a normal user terminal according to the data stored in the evaluation database by using the adaptive module as a basis, and adaptively adapt the subsequent allocation operation of the high-quality user terminal.
Example 1
Referring to fig. 3, one of the purposes of the present embodiment is to provide a flexible and labor-saving intelligent settlement management system based on big data, in S2, the specific steps for acquiring data parameters of a terminal and a user side by a data acquisition module in a big data platform are as follows:
s2.1: firstly, acquiring labor parameter data of a terminal;
s2.2: analyzing the acquired labor parameter data of the terminal through an analysis module in a big data platform, so as to obtain standardized labor parameter data;
s2.3: secondly, acquiring parameter data of a user side;
s2.4: analyzing the acquired parameter data of the user terminal through an analysis module in a big data platform, so as to obtain standardized parameter data of the user terminal;
s2.5: and integrating the labor parameter data of the terminal and the parameter data of the user side.
The labor parameter data of the terminal and the standardized labor parameter data in the S2.1 at least comprise the labor type parameter of the terminal, the personnel number parameter of the terminal, the time interval parameter data of the labor of the terminal and the labor compensation parameter data of the terminal;
the parameter data of the user side and the standardized parameter data of the user side at least comprise the personnel number parameter of the user side, the demand parameter data of the user side, the operation time interval parameter data of the user side and the salary expected parameter data of the user side.
Example 1
Referring to fig. 4, one of the purposes of this embodiment is to provide a flexible and labor-saving intelligent settlement management system based on big data, and in S5, the operation flow of the reminding module is specifically as follows:
s5.1: firstly, a reminding module receives the user end labor progress feature extracted from a monitoring device arranged by a monitoring module;
s5.2: extracting the user end labor progress characteristics by a monitoring device arranged by a monitoring module and carrying out standardized treatment;
s5.3: setting the normalized user end labor progress characteristic points as；
S5.4: then, according to the operation time threshold value of the user side monitored by the monitoring module, extracting standard labor progress characteristics in the time threshold value from the cloud database;
s5.5: setting the extracted standard labor progress feature points as；
S5.6: characteristic points of standard labor progressWith user side recruitment progress feature pointComparing;
s5.7: and if the compared matching degree is smaller than the set threshold value, reminding the user side through a reminding module.
Example 1
Referring to fig. 5, one of the purposes of this embodiment is to provide a flexible and labor-saving intelligent settlement management system based on big data, in S6, the settlement module is used to settle the user end with completed operation, which specifically includes the following steps:
s6.1: firstly, extracting graphic data parameters from the settled operation state by a monitoring module connected with a settlement module and matched with the set monitoring equipment;
s6.2: feature points in the extracted graphic data parametersExtracting;
s6.3: extracting standard recruitment settlement feature points in the connected cloud database through a settlement module；
S6.4: standard recruitment settlement feature pointsCalculating feature points with user endComparing;
s6.5: then, according to the compared difference value, determining the final operation state of the user terminal;
s6.6: and finally, extracting the recruitment parameter data of the terminal and the time interval parameter data of the recruitment of the terminal, which are acquired in the cloud database, as reference basis, and completing settlement for the operation of the user terminal by combining the compared difference values.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. An intelligent settlement management system for flexible labor based on big data is characterized in that: the method comprises the following steps:
s1: firstly, establishing a big data platform for intelligent settlement management of flexible labor use;
s2: the data parameters of the terminal and the user side are acquired through a data acquisition module in a large data platform for flexible labor-saving intelligent settlement management, and all acquired data are integrated;
s3: storing each data integrated in the data acquisition module into a cloud database in a big data platform;
s4: connecting the cloud database with a monitoring module;
s5: monitoring a user side through a monitoring module, and connecting the monitoring module with a reminding module;
s6: after the user finishes the operation, the user will settle accounts through the settlement module;
s7: after settlement is completed, the user terminal is evaluated through an evaluation module in a big data platform, and the parameter data of the time is stored in a cloud database;
s8: then generating a user side evaluation database according to the evaluation of the user side by the evaluation module;
s9: dividing each user terminal into a high-quality user terminal and a common user terminal according to the evaluation parameter data of each user terminal in the user terminal evaluation database;
s10: collecting various parameter data of a high-quality user terminal through a self-adaptive module in a big data platform;
s11: and finally, carrying out self-adaptive matching on the high-quality user terminal through a self-adaptive module under the operation of the high-quality user terminal, and distributing operation tasks to the high-quality user terminal.
2. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: the big data platform in the S1 comprises a data acquisition module, a cloud database, a monitoring module, a reminding module, a settlement module, an evaluation module, a user side evaluation database and a self-adaptive module;
the data acquisition module, the monitoring module, the settlement module and the reminding module are electrically connected with the cloud database;
the monitoring module is electrically connected with the reminding module;
the self-adaptive module and the evaluation module are electrically connected with the user terminal evaluation database.
3. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in the step S2, the data acquisition module in the big data platform acquires the data parameters of the terminal and the user terminal as follows:
s2.1: firstly, acquiring labor parameter data of a terminal;
s2.2: analyzing the acquired labor parameter data of the terminal through an analysis module in a big data platform, so as to obtain standardized labor parameter data;
s2.3: secondly, acquiring parameter data of a user side;
s2.4: analyzing the acquired parameter data of the user terminal through an analysis module in a big data platform, so as to obtain standardized parameter data of the user terminal;
s2.5: and integrating the labor parameter data of the terminal and the parameter data of the user side.
4. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: the labor parameter data of the terminal and the standardized labor parameter data in the S2.1 at least comprise labor type parameters of the terminal, personnel number parameters of the terminal, time interval parameter data of labor of the terminal and labor compensation parameter data of the terminal;
the parameter data of the user side and the standardized parameter data of the user side at least comprise user side personnel number parameters, user side demand parameter data, user side operation time interval parameter data and user side salary expected parameter data.
5. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in the S4, the monitoring module is configured to obtain the labor progress of each user through the set monitoring device, and obtain the parameter data of the user and the labor type parameter of the terminal in the cloud database through being connected with the cloud database, and extract the labor progress feature of the user through the monitoring device set by the monitoring module, and transmit the labor progress feature to the reminding module.
6. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in the step S5, the operation flow of the reminding module is specifically as follows:
s5.1: firstly, a reminding module receives the user end labor progress feature extracted from a monitoring device arranged by a monitoring module;
s5.2: extracting the user end labor progress characteristics by a monitoring device arranged by a monitoring module and carrying out standardized treatment;
s5.3: setting the normalized user end labor progress characteristic points as；
S5.4: then, according to the operation time threshold value of the user side monitored by the monitoring module, extracting standard labor progress characteristics in the time threshold value from the cloud database;
s5.5: setting the extracted standard labor progress feature points as；
S5.6: characteristic points of standard labor progressWith user side recruitment progress feature pointComparing;
s5.7: and if the compared matching degree is smaller than the set threshold value, reminding the user side through a reminding module.
7. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in the step S6, the settlement module performs settlement on the user terminal that has completed the operation, specifically including the following steps:
s6.1: firstly, extracting graphic data parameters from the settled operation state by a monitoring module connected with a settlement module and matched with the set monitoring equipment;
s6.2: feature points in the extracted graphic data parametersExtracting;
s6.3: extracting standard recruitment settlement feature points in the connected cloud database through a settlement module；
S6.4: standard recruitment settlement feature pointsCalculating feature points with user endComparing;
s6.5: then, according to the compared difference value, determining the final operation state of the user terminal;
s6.6: and finally, extracting the recruitment parameter data of the terminal and the time interval parameter data of the recruitment of the terminal, which are acquired in the cloud database, as reference basis, and completing settlement for the operation of the user terminal by combining the compared difference values.
8. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in the step S7, the evaluation module is used for evaluating the service flow formed between the user terminal and the terminal and setting an evaluation threshold valueBased on the set evaluation threshold +.>Evaluating the current business processes of the user terminal and the terminal;
if the current business flow of the user terminal and the terminal is greater than the set evaluation threshold valueThe task user side and the terminal directly process the current business process to meet the index required by the terminal；
If the current business flow of the user and the terminal is smaller than the set evaluation threshold valueAnd if the task is that the current and the terminal direct business flow of the user terminal do not meet the index required by the terminal.
9. The flexible-use intelligent settlement management system based on big data as claimed in claim 8, wherein: the evaluation threshold valueThe specific calculation mode is as follows:
(1) Firstly, extracting each item of data in an evaluation database of a user side, and adding a certain floating threshold value to obtain the proportion of high-quality data in the evaluation databaseThe specific formula is as follows:
；
in the formulaRepresented as all parameter data in the user side evaluation database, < >>Represented as floating threshold, +.>Represented as a verification threshold;
(2) For high quality data proportion in evaluation databaseThe verification is carried out, and the specific formula is as follows:
if it isThen the ratio of quality data in the evaluation database is indicated +.>Is unreasonable;
if it isThen the ratio of quality data in the evaluation database is indicated +.>Is reasonable;
(3) Scaling of quality data in a pair-wise evaluation databaseAfter verification is completed, the evaluation threshold is extracted>The specific expression is as follows:
；
in the formulaQuantity parameter data expressed as all user terminals in cloud database, < >>Expressed as a proportion of premium data in the evaluation database +.>And (5) reasonably learning floating parameters.
10. The flexible-use intelligent settlement management system based on big data according to claim 1, wherein: in S10 and S11, the adaptive module performs evaluation on each operation condition of each user terminal according to the evaluation module, stores the evaluated result in the evaluation database, and divides each user terminal into a high-quality user terminal and a normal user terminal according to the data stored in the evaluation database by the adaptive module, so as to adaptively adapt to the subsequent allocation operation of the high-quality user terminal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311286159.XA CN117236778B (en) | 2023-10-08 | Intelligent settlement management system for flexible labor based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311286159.XA CN117236778B (en) | 2023-10-08 | Intelligent settlement management system for flexible labor based on big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117236778A true CN117236778A (en) | 2023-12-15 |
| CN117236778B CN117236778B (en) | 2024-05-31 |
Family
ID=
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111553656A (en) * | 2020-04-28 | 2020-08-18 | 好活（昆山）网络科技有限公司 | Capital settlement method and device based on big data, electronic equipment and medium |
| CN112053090A (en) * | 2020-09-28 | 2020-12-08 | 拉卡拉汇积天下技术服务（北京）有限公司 | Flexible employment data processing method, device and system based on block chain |
| CN112070385A (en) * | 2020-09-01 | 2020-12-11 | 好活（昆山）网络科技有限公司 | Flexible employment supervision method, device, platform, equipment and storage medium |
| KR102197286B1 (en) * | 2020-04-24 | 2020-12-31 | 조용삼 | System for providing automatic service for human resource management and salary transaction per stakeholder |
| CN112734413A (en) * | 2021-01-20 | 2021-04-30 | 深圳市葆康丽教育发展有限公司 | Flexible employment system and method |
| CN113344525A (en) * | 2021-06-03 | 2021-09-03 | 佛山市思博达科技有限公司 | Enterprise human resource comprehensive management system |
| CN113344503A (en) * | 2020-11-30 | 2021-09-03 | 上海昌投网络科技有限公司 | Flexible employment management system and module matching method thereof |
| CN113822527A (en) * | 2021-08-02 | 2021-12-21 | 广州南方仕通网络科技有限公司 | Compliance monitoring method, equipment, medium and product based on flexible employment platform |
| CN114219414A (en) * | 2021-11-02 | 2022-03-22 | 才星(广州)科技服务有限公司 | Subscription method, settlement method and system for flexible employment business middling station |
| CN114493126A (en) * | 2021-12-27 | 2022-05-13 | 上海佩琪信息技术有限公司 | Flexible employment information processing method |
| CN114936792A (en) * | 2022-06-10 | 2022-08-23 | 海南众乐邦网络科技有限公司 | Task management system based on flexible employment and management method thereof |
| CN115983600A (en) * | 2023-01-12 | 2023-04-18 | 汉唐融科(北京)科技有限公司 | Settlement management system for flexible employment |
| CN116432937A (en) * | 2023-01-12 | 2023-07-14 | 汉唐融科(北京)科技有限公司 | Flexible recruitment settlement management system |
| CN116757469A (en) * | 2023-05-25 | 2023-09-15 | 青岛小贝信息技术有限公司 | Instant wind control management system for flexible engineering platform |
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102197286B1 (en) * | 2020-04-24 | 2020-12-31 | 조용삼 | System for providing automatic service for human resource management and salary transaction per stakeholder |
| CN111553656A (en) * | 2020-04-28 | 2020-08-18 | 好活（昆山）网络科技有限公司 | Capital settlement method and device based on big data, electronic equipment and medium |
| CN112070385A (en) * | 2020-09-01 | 2020-12-11 | 好活（昆山）网络科技有限公司 | Flexible employment supervision method, device, platform, equipment and storage medium |
| CN112053090A (en) * | 2020-09-28 | 2020-12-08 | 拉卡拉汇积天下技术服务（北京）有限公司 | Flexible employment data processing method, device and system based on block chain |
| CN113344503A (en) * | 2020-11-30 | 2021-09-03 | 上海昌投网络科技有限公司 | Flexible employment management system and module matching method thereof |
| CN112734413A (en) * | 2021-01-20 | 2021-04-30 | 深圳市葆康丽教育发展有限公司 | Flexible employment system and method |
| CN113344525A (en) * | 2021-06-03 | 2021-09-03 | 佛山市思博达科技有限公司 | Enterprise human resource comprehensive management system |
| CN113822527A (en) * | 2021-08-02 | 2021-12-21 | 广州南方仕通网络科技有限公司 | Compliance monitoring method, equipment, medium and product based on flexible employment platform |
| CN114219414A (en) * | 2021-11-02 | 2022-03-22 | 才星(广州)科技服务有限公司 | Subscription method, settlement method and system for flexible employment business middling station |
| CN114493126A (en) * | 2021-12-27 | 2022-05-13 | 上海佩琪信息技术有限公司 | Flexible employment information processing method |
| CN114936792A (en) * | 2022-06-10 | 2022-08-23 | 海南众乐邦网络科技有限公司 | Task management system based on flexible employment and management method thereof |
| CN115983600A (en) * | 2023-01-12 | 2023-04-18 | 汉唐融科(北京)科技有限公司 | Settlement management system for flexible employment |
| CN116432937A (en) * | 2023-01-12 | 2023-07-14 | 汉唐融科(北京)科技有限公司 | Flexible recruitment settlement management system |
| CN116757469A (en) * | 2023-05-25 | 2023-09-15 | 青岛小贝信息技术有限公司 | Instant wind control management system for flexible engineering platform |
Non-Patent Citations (1)
| Title |
|---|
| 詹颖祺;: "现代工程企业管理研究――以工程结算管理为例", 商业文化, no. 32, 30 December 2014 (2014-12-30) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111131314B (en) | Network behavior detection method and device, computer equipment and storage medium | |
| CN110610431A (en) | Intelligent claim settlement method and intelligent claim settlement system based on big data | |
| CN111091106B (en) | Image clustering method and device, storage medium and electronic device | |
| WO2020232998A1 (en) | Medical image evaluation method and apparatus, computer device and storage medium | |
| CN109460775A (en) | A kind of data filling method and device based on comentropy | |
| CN115730605B (en) | Data analysis method based on multidimensional information | |
| CN108596516A (en) | A kind of automation appraisal procedure and system | |
| CN108052918A (en) | A kind of person's handwriting Compare System and method | |
| CN111445058A (en) | Data analysis method, device, equipment and computer readable storage medium | |
| CN111062602A (en) | Method, device and storage medium for enterprise credit risk assessment | |
| CN115424048A (en) | Power grid operation field violation identification system and method | |
| CN117236778B (en) | Intelligent settlement management system for flexible labor based on big data | |
| CN117236778A (en) | Intelligent settlement management system for flexible labor based on big data | |
| CN112652070A (en) | Three-dimensional model surface reduction method, device, equipment and medium | |
| CN111343271A (en) | DTU (data transfer unit) equipment-based artificial intelligence cloud control method and system | |
| CN110428409A (en) | Furniture quality detecting method and system | |
| CN111797922B (en) | Text image classification method and device | |
| CN113052726B (en) | Smart community property service system based on cloud computing | |
| CN109585013A (en) | A kind of distributed medical diagnostic analysis method and system | |
| CN115205163A (en) | Method, device and equipment for processing identification image and storage medium | |
| CN111131322B (en) | Network behavior detection method and device, computer equipment and storage medium | |
| CN114782822A (en) | Method and device for detecting state of power equipment, electronic equipment and storage medium | |
| CN115019057A (en) | Image feature extraction model determining method and device and image identification method and device | |
| CN113033373A (en) | Method and related device for training face recognition model and recognizing face | |
| CN112084884A (en) | Scanning electron microscope image pore identification method, terminal device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |