Government affair event flow processing intelligent supervision system

Abstract

The invention discloses an intelligent supervision system for government affair event flow processing, and belongs to the technical field of flow processing supervision. The method and the device are used for solving the technical problems of poor early-stage automatic verification and screening supervision effect and poor verification and screening autonomous optimization management effect of government affair event flow processing in an existing scheme. All screening abnormal data obtained through supervision are classified and combined, screening negative influence data processing and analysis of different dimensions are carried out on different event types, and type processing states corresponding to the different event types are obtained; according to the type processing abnormal states corresponding to different event types, data processing in different aspects is performed on the belonging event types, and data processing results in different aspects are analyzed to perform dynamic optimization management on standardized verification schemes corresponding to the belonging event types. According to the method, the type processing abnormal state obtained by earlier-stage processing is expanded and utilized, and the verification and screening autonomous optimization management effect of government affair event process processing is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of process processing supervision, and in particular to an intelligent supervision system for process-based processing of government affairs events. Background Art

[0002] When implementing existing supervision schemes for the standardized processing of government affairs events, most of them conduct supervision and analysis on different stages and different goals of the government affairs event process processing. However, there is no early supervision and analysis of abnormal data from the automated verification and screening of different types of government affairs events, and no verification of the abnormal causes corresponding to different abnormal data based on the supervision and analysis results, as well as integrated evaluation of the abnormal causes and dynamic optimization management of the existing automated verification and screening schemes for government affairs events. This results in poor supervision of the early automatic verification and screening of the standardized processing of government affairs events and poor autonomous optimization management of the verification and screening. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent supervision system for the process-based processing of government affairs events, which is used to solve the technical problems of poor effect of preliminary automatic verification and screening supervision and poor effect of autonomous optimization management of verification and screening in the existing solutions for the process-based processing of government affairs events.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] An intelligent supervision system for process-based processing of government affairs events, comprising:

[0006] The automated verification and screening module for government affairs events is used to conduct standardized verification and analysis and automatic screening of submitted government affairs events, mark government affairs events that pass the screening and forward them to the corresponding manual personnel for subsequent processing;

[0007] Obtain the event type and failure reason corresponding to the government affairs event that failed the screening, and sort and combine the obtained event type and failure reason to obtain the screening abnormality data corresponding to the failed government affairs event;

[0008] The government event screening anomaly supervision and analysis module is used to classify and combine all the screening anomaly data obtained by supervision, obtain the screening anomaly classification set corresponding to different event types, and perform screening negative impact data processing and analysis of different event types in different dimensions according to the screening anomaly classification set to obtain the type processing status corresponding to different event types;

[0009] The government affairs event screening and processing optimization management module is used to perform different aspects of data processing on the corresponding event types according to the type processing abnormal status corresponding to the different event types, and analyze the data processing results in different aspects to dynamically optimize the management of the standardized verification plan corresponding to the corresponding event type.

[0010] Preferably, all corresponding screening abnormality data are sorted and combined according to the same event type to obtain a screening abnormality classification set corresponding to the corresponding event type, and the screening abnormality classification set is processed and the screening negative impact analysis of different dimensions is performed;

[0011] Obtain the total number of all screening abnormality data in the screening abnormality classification set corresponding to the event type, and calculate the screening abnormality incidence rate YF1 corresponding to the event type through the formula YF1=SY / SZ; where SY and SZ are the total number of all screening abnormality data corresponding to the event type and the total number of all screening and processing government affairs events, respectively;

[0012] According to the screening anomaly classification set corresponding to the event type, obtain all the first failure reasons that appear, and the total number of occurrences corresponding to different first failure reasons;

[0013] The different first failure reasons corresponding to the event types and their corresponding total number of occurrences are sorted and combined to obtain a first local event type processing supervision sequence.

[0014] Preferably, all first government affairs events whose event types pass the automatic screening are obtained, and all second government affairs events that fail the manual review are obtained among all government affairs events, and different second failure reasons corresponding to all second government affairs events and their corresponding total number of occurrences are obtained;

[0015] Sort and combine the different second failure reasons obtained from all second government affairs events corresponding to the event type and their corresponding total number of occurrences to obtain a second local event type processing supervision sequence;

[0016] The abnormal human review rate YF2 corresponding to the event type is calculated by the formula YF2=RY / ST; where RY and ST are the total number of second government affairs events and the total number of first government affairs events corresponding to the event type, respectively;

[0017] When analyzing the negative screening impact of event type corresponding to the government event process in different dimensions, the screening abnormality incidence rate and human review abnormality incidence rate obtained by the event type corresponding processing are respectively analyzed in the local screening negative impact identification function, and the local screening negative impact coefficient JYYk of the corresponding dimension is output.

[0018] Preferably, the expression of the local screening negative impact identification function is: In the formula, k is 1 and 2, indicating the automatic screening dimension and the manual review dimension; JYYk is JYY1 and JYY2, which are the local screening negative impact coefficients corresponding to the automatic screening dimension and the local screening negative impact coefficients corresponding to the manual review dimension, respectively; YFk is YF1 and YF2; YBk is YB1 and YB2, which are the automatic screening abnormal standard values ​​corresponding to the automatic screening dimension and the manual screening abnormal standard values ​​corresponding to the manual review dimension, respectively;

[0019] The local screening negative impact coefficient contains a value of 0 or 1.

[0020] Preferably, the screening abnormality incidence rate and the human review abnormality incidence rate obtained by the corresponding processing of the event type are analyzed through the overall screening negative impact identification function, and the overall screening negative impact coefficient ZYY of the overall dimension is output;

[0021] Among them, the expression of the overall screening negative impact identification function is: In the formula, ZB is the screening difference standard value;

[0022] The overall screening negative impact coefficient contains values ​​of 0 or 1;

[0023] All local screening negative impact coefficients and overall screening negative impact coefficients obtained by processing are sorted and combined to obtain a local event type implementation analysis sequence.

[0024] Preferably, the analysis sequence is traversed and analyzed for the local event type, and the type processing status of the corresponding event type is dynamically classified and marked according to the analysis result;

[0025] If there is no element with a value of 1 in the local event type implementation analysis sequence, the associated type of the event type to which it belongs is processed in the normal state;

[0026] If there is an element with a value of 1 in the local event type implementation analysis sequence, the associated event type will be processed as an exception state.

[0027] Preferably, the event type of the associated type processing abnormal state is marked as a selected event type, and a first local event type processing supervision sequence and a second local event type processing supervision sequence corresponding to the selected event type are obtained;

[0028] The first local event type processing supervision sequence and the second local event type processing supervision sequence are matched through the first matching function UP1=U2∩U1 to obtain the first matching set UP1, and the second matching set UP2 is matched through the second matching function UP2=U2∪U1 to obtain the second matching set UP2; wherein U1 is the first failure reason set in the first local event type processing supervision sequence, and U2 is the second failure reason set in the second local event type processing supervision sequence.

[0029] Preferably, all reasons for failure to match in the first matching set are obtained, and the formula Calculate and obtain the first matching optimization necessary value YYB corresponding to the first matching set; where i is the different first failure reasons in the first matching set, i=1, 2, 3, ..., M; M is a positive integer, which is the total number of first failure reasons; YXi is the conventional failure influencing factor corresponding to different first failure reasons; Ni is the total number of occurrences corresponding to different first failure reasons; A is the conventional optimization standard value.

[0030] Preferably, all reasons for failure to match in the second matching set are obtained, and the formula Calculate and obtain the second matching optimization necessary value EYB corresponding to the second matching set; wherein, j is the different second failure reasons in the second matching set, j=1, 2, 3, ..., P; P is a positive integer, which is the total number of second failure reasons; YXj is the special failure influencing factor corresponding to different second failure reasons; Nj is the total number of occurrences corresponding to different second failure reasons; B is the special optimization standard value.

[0031] Preferably, the first matching optimization necessary value and the second matching optimization necessary value obtained by calculation are sorted and combined to obtain a matching optimization necessary supervision sequence corresponding to the corresponding event type;

[0032] The necessary regulatory sequences for matching optimization are traversed and analyzed, and based on the analysis results, the standardized verification scheme for the corresponding event type is partially optimized and upgraded, or the standardized verification scheme for the corresponding event type is optimized and upgraded as a whole.

[0033] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0034] The present invention classifies and combines all screening abnormal data obtained by supervision, and processes and analyzes the screening negative impact data of different dimensions for different event types, thereby obtaining type processing status corresponding to different event types, thereby realizing multi-dimensional supervision and processing analysis of the process processing of different event types of government affairs events, and improving the effect of automatic verification, screening and supervision in the early stage of process processing of government affairs events.

[0035] The present invention performs different aspects of data processing on the corresponding event types according to the type processing exception states corresponding to the different event types, and analyzes the data processing results in different aspects to dynamically optimize the management of the standardized verification schemes corresponding to the corresponding event types, thereby realizing the expanded utilization of the type processing exception states obtained in the early processing to optimize the subsequent process processing of different event types of government affairs events in different aspects, thereby improving the autonomous optimization management effect of the verification screening of the process processing of government affairs events. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] Figure 1 This is a module block diagram of an intelligent supervision system for process-based processing of government affairs events according to the present invention.

[0038] Figure 2 This is a flowchart of the operation of an intelligent supervision system for process-based processing of government affairs events according to the present invention.

[0039] Figure 3 A flowchart of the analysis process for matching and optimizing the necessary regulatory sequences in the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] like Figure 1 to Figure 2 As shown, the present invention is an intelligent supervision system for process-based processing of government affairs events, including an automated verification and screening module for government affairs events, a supervision and analysis module for abnormal screening of government affairs events, and an optimization management module for screening and processing of government affairs events;

[0042] The automated verification and screening module for government affairs events is used to conduct standardized verification and analysis and automatic screening of submitted government affairs events, mark government affairs events that pass the screening and forward them to the corresponding manual personnel for subsequent processing;

[0043] Obtain the event type and failure reason corresponding to the government affairs event that failed the screening, and sort and combine the obtained event type and failure reason to obtain the screening abnormality data corresponding to the failed government affairs event;

[0044] In the embodiment of the present invention, the government affairs events with standardization requirements generally refer to those matters that need to comply with specific standards, procedures, laws and regulations during the processing;

[0045] The event types corresponding to government events, including but not limited to administrative approval and licensing, finance and taxation, and people's livelihood services, can be customized according to the actual application needs of the actual application scenarios;

[0046] In addition, standardized verification analysis and automatic screening of government affairs events can be automatically implemented according to the existing standardized verification scheme, which is set based on the standardized requirement data corresponding to all existing government affairs events;

[0047] Automatic screening of standardized verification, specifically the completeness, legality and formatted data verification of application materials;

[0048] By conducting standardized verification and analysis and automatic screening of submitted government affairs events, automatically managing the subsequent handling of government affairs events based on the screening results, and conducting data monitoring and statistics on different aspects of government affairs events that fail the screening, reliable local screening and supervision data support can be provided for the autonomous optimization management and analysis of the subsequent process processing of government affairs events.

[0049] The government event screening anomaly supervision and analysis module is used to classify and combine all the screening anomaly data obtained by supervision, obtain the screening anomaly classification set corresponding to different event types, and perform screening negative impact data processing and analysis of different event types in different dimensions according to the screening anomaly classification set to obtain the type processing status corresponding to different event types; including:

[0050] All corresponding screening abnormality data are sorted and combined according to the same event type to obtain the screening abnormality classification set corresponding to the event type, and the screening abnormality classification set is processed and the negative screening impact analysis of different dimensions is performed;

[0051] Obtain the total number of all screening abnormality data in the screening abnormality classification set corresponding to the event type, and calculate the screening abnormality incidence rate YF1 corresponding to the event type through the formula YF1=SY / SZ; where SY and SZ are the total number of all screening abnormality data corresponding to the event type and the total number of all screening and processing government affairs events, respectively;

[0052] According to the screening anomaly classification set corresponding to the event type, obtain all the first failure reasons that appear, and the total number of occurrences corresponding to different first failure reasons;

[0053] Sort and combine different first failure reasons corresponding to the event type and their corresponding total number of occurrences to obtain a first local event type processing supervision sequence;

[0054] It should be noted that by monitoring, counting and processing the data of the previous automated screening failures, the first local event type processing supervision sequence corresponding to the automatic screening dimension is obtained, which can provide reliable local screening supervision processing data support for the subsequent local screening negative impact processing analysis of the automatic screening dimension.

[0055] And, obtaining all first government affairs events whose event types pass automatic screening, obtaining all second government affairs events that fail manual review among all government affairs events, and obtaining different second failure reasons corresponding to all second government affairs events and their corresponding total number of occurrences;

[0056] Sort and combine the different second failure reasons obtained from all second government affairs events corresponding to the event type and their corresponding total number of occurrences to obtain a second local event type processing supervision sequence;

[0057] The abnormal human review rate YF2 corresponding to the event type is calculated by the formula YF2=RY / ST; where RY and ST are the total number of second government affairs events and the total number of first government affairs events corresponding to the event type, respectively;

[0058] In addition, by monitoring and counting the data that passed the previous automatic screening but failed the manual review, and processing and combining them, the second local event type processing supervision sequence corresponding to the manual review dimension can be obtained, which can provide reliable local screening supervision processing data support for the subsequent local screening negative impact processing analysis in the manual review dimension; manual review conducts other content review on the basis of the automatic screening specification requirements, and the specific review content is determined according to the event type of the government event and the actual review requirements;

[0059] When analyzing the negative impact of screening on the government affairs event process corresponding to the event type in different dimensions, the screening abnormality incidence rate and the human review abnormality incidence rate obtained by the event type corresponding processing are analyzed in the local screening negative impact identification function, and the local screening negative impact coefficient JYYk of the corresponding dimension is output;

[0060] Among them, the expression of the local screening negative impact identification function is: Wherein, k is 1 and 2, indicating the automatic screening dimension and the manual review dimension; JYYk is JYY1 and JYY2, which are the local screening negative impact coefficients corresponding to the automatic screening dimension and the local screening negative impact coefficients corresponding to the manual review dimension respectively; YFk is YF1 and YF2; YBk is YB1 and YB2, which are the automatic screening abnormal standard values ​​corresponding to the automatic screening dimension and the manual screening abnormal standard values ​​corresponding to the manual review dimension respectively. They can be customized according to the actual application requirements of the actual application scenarios, or determined by the preliminary test data of automatic review and manual review;

[0061] The local screening negative impact coefficient contains a value of 0 or 1, indicating that the local screening negative impact of the corresponding dimension is normal or the local screening negative impact is abnormal;

[0062] Furthermore, the screening abnormality incidence rate and the human review abnormality incidence rate obtained by the corresponding processing of the event type are analyzed through the overall screening negative impact identification function, and the overall screening negative impact coefficient ZYY of the overall dimension is output;

[0063] Among them, the expression of the overall screening negative impact identification function is: In the formula, ZB is the screening difference standard value, which can be determined based on the previous overall screening test data;

[0064] The overall screening negative impact coefficient contains values ​​of 0 or 1, indicating that the overall screening negative impact of the overall dimension is normal and the overall screening negative impact is abnormal;

[0065] All local screening negative impact coefficients and overall screening negative impact coefficients obtained by processing are sorted and combined to obtain a local event type implementation analysis sequence;

[0066] It should be noted that by performing corresponding data processing calculations and combinations for screening negative impacts from different local dimensions and overall dimensions, the digital processing representation of screening negative impacts in the corresponding dimensions is realized, and reliable multi-dimensional regulatory processing data support can be provided for subsequent type processing status analysis corresponding to different event types, thereby improving the diversity and reliability of type processing status analysis corresponding to different event types.

[0067] Perform traversal analysis on the analysis sequence of local event types, and dynamically classify and mark the type processing status of the event type according to the analysis results;

[0068] If there is no element with a value of 1 in the local event type implementation analysis sequence, the associated type of the event type to which it belongs is processed in the normal state;

[0069] If there is an element with a value of 1 in the local event type implementation analysis sequence, the associated event type is processed with an abnormal state;

[0070] In an embodiment of the present invention, by classifying and combining all screening abnormal data obtained by supervision, and performing screening negative impact data processing and analysis of different event types in different dimensions, the type processing status corresponding to different event types is obtained, thereby realizing multi-dimensional supervision and processing analysis of the process processing of different event types of government affairs events, and improving the effect of automatic verification, screening and supervision in the early stage of process processing of government affairs events.

[0071] The government event screening and processing optimization management module is used to process data of different event types according to the abnormal state of type processing corresponding to different event types, and analyze the data processing results of different aspects to dynamically optimize the standardized verification plan corresponding to the event type; including:

[0072] Mark the event type of the associated type processing abnormal state as the selected event type, and obtain the first local event type processing supervision sequence and the second local event type processing supervision sequence corresponding to the selected event type;

[0073] The first local event type processing supervision sequence and the second local event type processing supervision sequence are matched through the first matching function UP1=U2∩U1 to obtain the first matching set UP1, and the second matching set UP2 is matched through the second matching function UP2=U2∪U1 to obtain the second matching set UP2; wherein U1 is the first failure reason set in the first local event type processing supervision sequence, and U2 is the second failure reason set in the second local event type processing supervision sequence;

[0074] Get all the reasons for failure of matching in the first matching set, and use the formula Calculate and obtain the first matching optimization necessary value YYB corresponding to the first matching set; wherein, i is the different first failure reasons in the first matching set, i=1, 2, 3, ..., M; M is a positive integer, which is the total number of first failure reasons; YXi is the conventional failure impact factor corresponding to different first failure reasons, and different first failure reasons are pre-set with a corresponding conventional failure impact factor, and the specific value can be determined by professional and technical personnel in this field, or it can be quantified according to the total number of occurrences of the corresponding first failure reasons; Ni is the total number of occurrences corresponding to different first failure reasons; A is the conventional optimization standard value, which is determined according to the operation design requirement data corresponding to the standardized verification plan;

[0075] It should be noted that the first matching optimization necessary value is used to perform data processing and calculation from the standard screening aspect of the automatic screening dimension to digitally represent the standard screening status of the standardized verification scheme corresponding to the event type;

[0076] And, get all the reasons for the failure of matching in the second matching set, and use the formula Calculate and obtain the second matching optimization necessary value EYB corresponding to the second matching set; where j is the different second failure reasons in the second matching set, j=1, 2, 3, ..., P; P is a positive integer, which is the total number of second failure reasons; YXj is the special failure impact factor corresponding to different second failure reasons, and different second failure reasons are pre-set with a corresponding conventional failure impact factor, and the specific value can be determined by professional and technical personnel in this field; Nj is the total number of occurrences corresponding to different second failure reasons; B is the special optimization standard value, which is determined according to the operation design requirement data corresponding to the standardized verification plan;

[0077] In addition, the second matching optimization necessary value is used to perform data processing calculations from the aspect of missed screening in the automatic screening dimension to digitally represent the missed screening status of the standardized verification scheme corresponding to the corresponding event type;

[0078] like Figure 3As shown, the first necessary value for matching optimization and the second necessary value for matching optimization obtained by calculation are sorted and combined to obtain a necessary supervision sequence for matching optimization corresponding to the event type;

[0079] Conduct traversal analysis on the regulatory sequences necessary for matching optimization;

[0080] If the elements in the matching optimization necessary supervision sequence are not greater than 1, the standardized verification plan of the corresponding event type is locally optimized and upgraded; specifically, all the first and second reasons for failure that appear in the standardized verification plan are optimized;

[0081] If the number of elements in the necessary supervision sequence for matching optimization is greater than 1, the standardized verification plan for the corresponding event type will be optimized and upgraded as a whole; specifically, all the first and second reasons for failure corresponding to the standardized verification plan will be improved and optimized, and the implementation verification content and verification rules of the standardized verification plan will also be improved and optimized.

[0082] In the embodiment of the present invention, different aspects of data processing are performed on the corresponding event types according to the type processing exception states corresponding to the different event types, and the data processing results in different aspects are analyzed to dynamically optimize the standardized verification schemes corresponding to the corresponding event types, thereby realizing the expanded utilization of the type processing exception states obtained in the early processing to optimize the subsequent process processing of different event types of government affairs events in different aspects, thereby improving the autonomous optimization management effect of the verification screening of the process processing of government affairs events.

[0083] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0084] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0085] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0087] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent supervision system for process-based processing of government affairs events, characterized in that: include: The automated verification and screening module for government affairs events is used to conduct standardized verification and analysis and automatic screening of submitted government affairs events, mark government affairs events that pass the screening and forward them to the corresponding manual personnel for subsequent processing; Obtain the event type and failure reason corresponding to the government affairs event that failed the screening, and sort and combine the obtained event type and failure reason to obtain the screening abnormality data corresponding to the failed government affairs event; The government event screening anomaly supervision and analysis module is used to classify and combine all the screening anomaly data obtained by supervision, obtain the screening anomaly classification set corresponding to different event types, and perform screening negative impact data processing and analysis of different event types in different dimensions according to the screening anomaly classification set to obtain the type processing status corresponding to different event types; The government affairs event screening and processing optimization management module is used to perform different aspects of data processing on the corresponding event types according to the type processing abnormal status corresponding to the different event types, and analyze the data processing results in different aspects to dynamically optimize the management of the standardized verification plan corresponding to the corresponding event type.

2. According to claim 1, a government affairs event process-based intelligent supervision system is characterized in that: All corresponding screening abnormality data are sorted and combined according to the same event type to obtain the screening abnormality classification set corresponding to the event type, and the screening abnormality classification set is processed and the negative screening impact analysis of different dimensions is performed; Obtain the total number of all screening abnormality data in the screening abnormality classification set corresponding to the event type, and calculate the screening abnormality incidence rate YF1 corresponding to the event type through the formula YF1=SY / SZ; where SY and SZ are the total number of all screening abnormality data corresponding to the event type and the total number of all screening and processing government affairs events, respectively; According to the screening anomaly classification set corresponding to the event type, obtain all the first failure reasons that appear, and the total number of occurrences corresponding to different first failure reasons; The different first failure reasons corresponding to the event types and their corresponding total number of occurrences are sorted and combined to obtain a first local event type processing supervision sequence.

3. According to claim 2, a government affairs event process-based intelligent supervision system is characterized in that: Obtain all first government affairs events whose event types pass automatic screening, obtain all second government affairs events that fail manual review among all government affairs events, and obtain different second failure reasons corresponding to all second government affairs events and their corresponding total number of occurrences; Sort and combine the different second failure reasons obtained from all second government affairs events corresponding to the event type and their corresponding total number of occurrences to obtain a second local event type processing supervision sequence; The abnormal human review rate YF2 corresponding to the event type is calculated by the formula YF2=RY / ST; where RY and ST are the total number of second government affairs events and the total number of first government affairs events corresponding to the event type, respectively; When analyzing the negative screening impact of event type corresponding to the government event process in different dimensions, the screening abnormality incidence rate and human review abnormality incidence rate obtained by the event type corresponding processing are respectively analyzed in the local screening negative impact identification function, and the local screening negative impact coefficient JYYk of the corresponding dimension is output.

4. According to claim 3, a government affairs event process-based intelligent supervision system is characterized in that: The expression of the local screening negative impact identification function is: In the formula, k is 1 and 2, indicating the automatic screening dimension and the manual review dimension; JYYk is JYY1 and JYY2, which are the local screening negative impact coefficients corresponding to the automatic screening dimension and the local screening negative impact coefficients corresponding to the manual review dimension, respectively; YFk is YF1 and YF2; YBk is YB1 and YB2, which are the automatic screening abnormal standard values ​​corresponding to the automatic screening dimension and the manual screening abnormal standard values ​​corresponding to the manual review dimension, respectively; The local screening negative impact coefficient contains a value of 0 or 1.

5. According to claim 4, a government affairs event process-based intelligent supervision system is characterized in that: The screening abnormality incidence rate and human review abnormality incidence rate obtained by the corresponding processing of the event type are analyzed through the overall screening negative impact identification function, and the overall screening negative impact coefficient ZYY of the overall dimension is output; Among them, the expression of the overall screening negative impact identification function is: In the formula, ZB is the screening difference standard value; The overall screening negative impact coefficient contains values ​​of 0 or 1; All local screening negative impact coefficients and overall screening negative impact coefficients obtained by processing are sorted and combined to obtain a local event type implementation analysis sequence.

6. According to claim 5, a government affairs event process-based intelligent supervision system is characterized in that: Perform traversal analysis on the analysis sequence of local event types, and dynamically classify and mark the type processing status of the event type according to the analysis results; If there is no element with a value of 1 in the local event type implementation analysis sequence, the associated type of the event type to which it belongs is processed in the normal state; If there is an element with a value of 1 in the local event type implementation analysis sequence, the associated event type will be processed as an exception state.

7. According to claim 6, a government affairs event process-based intelligent supervision system is characterized in that: Mark the event type of the associated type processing abnormal state as the selected event type, and obtain the first local event type processing supervision sequence and the second local event type processing supervision sequence corresponding to the selected event type; The first local event type processing supervision sequence and the second local event type processing supervision sequence are matched through the first matching function UP1=U2∩U1 to obtain the first matching set UP1, and the second matching set UP2 is matched through the second matching function UP2=U2∪U1 to obtain the second matching set UP2; wherein U1 is the first failure reason set in the first local event type processing supervision sequence, and U2 is the second failure reason set in the second local event type processing supervision sequence.

8. According to claim 7, a government affairs event process-based intelligent supervision system is characterized in that: Get all the reasons for failure of matching in the first matching set, and use the formula Calculate and obtain the first matching optimization necessary value YYB corresponding to the first matching set; where i is a different first failure reason in the first matching set, i=1, 2, 3, ..., M; M is a positive integer, which is the total number of first failure reasons; YXi is the conventional failure influencing factor corresponding to different first failure reasons; Ni is the total number of occurrences corresponding to different first failure reasons; A is the conventional optimization standard value.

9. According to claim 8, a government affairs event process-based intelligent supervision system is characterized in that: Get all the reasons for the failure of matching in the second matching set, and use the formula Calculate and obtain the second matching optimization necessary value EYB corresponding to the second matching set; wherein, j is the different second failure reasons in the second matching set, j=1, 2, 3, ..., P; P is a positive integer, which is the total number of second failure reasons; YXj is the special failure influencing factor corresponding to different second failure reasons; Nj is the total number of occurrences corresponding to different second failure reasons; B is the special optimization standard value.

10. The intelligent supervision system for process-based processing of government affairs events according to claim 9 is characterized in that: The first matching optimization necessary value and the second matching optimization necessary value obtained by calculation are sorted and combined to obtain a matching optimization necessary supervision sequence corresponding to the corresponding event type; The necessary regulatory sequences for matching optimization are traversed and analyzed, and based on the analysis results, the standardized verification scheme for the corresponding event type is partially optimized and upgraded, or the standardized verification scheme for the corresponding event type is optimized and upgraded as a whole.

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