Innovative service policy matching service supervision processing system and method based on artificial intelligence

Abstract

The invention discloses an innovation service policy matching service supervision processing system and method based on artificial intelligence, and belongs to the technical field of service supervision. The method is used for solving the technical problem that multi-dimensional supervision analysis and active evaluation optimization management cannot be carried out on innovation service policies in an existing scheme. Screening and data analysis are carried out on different targets by using different policy items in the innovation service policy to obtain screening passing data and screening non-passing data; carrying out data processing calculation on non-passing screening data and passing screening data obtained by screening to obtain an early-stage screening influence degree and a later-stage non-passing influence degree of corresponding dimensions; and carrying out integrated calculation and analysis on the early-stage screening influence degree and the later-stage non-passing influence degree obtained through calculation of different dimensions to carry out influence evaluation on the innovative service policy, and carrying out dynamic adjustment and improvement on the innovative service policy according to an evaluation result.

Description

Technical Field

[0001] The present invention relates to the field of service supervision technology, and in particular to an innovative service policy matching service supervision processing system and method based on artificial intelligence. Background Art

[0002] Innovative service policy is a series of measures and strategies formulated by the government or enterprises to promote innovation in the service industry, improve service quality and efficiency, enhance competitiveness, and meet social and market needs.

[0003] The existing innovation service policy matching service plan has certain defects in implementation. It is unable to conduct multi-dimensional regulatory analysis in the early and late stages of the implementation of the innovation service policy, and is unable to integrate the results of the multi-dimensional regulatory analysis and actively evaluate and optimize management. Summary of the invention

[0004] The purpose of the present invention is to provide an innovative service policy matching service supervision processing system and method based on artificial intelligence, which is used to solve the technical problems in existing solutions that cannot conduct multi-dimensional supervision analysis and active evaluation and optimization management of innovative service policies.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] The innovative service policy matching service supervision and processing system based on artificial intelligence includes:

[0007] The policy implementation preprocessing module is used to screen the effectiveness of all targets for the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform;

[0008] The policy data analysis and management module is used to evaluate the impact of the innovation service policy based on the screening failure data and screening pass data obtained through screening, and dynamically adjust and improve the innovation service policy based on the evaluation results;

[0009] Among them, the preliminary screening influence corresponding to the innovation service policy is obtained based on the first total number of failed screening targets and the selected policy items corresponding to all failed screening targets according to the failed screening data statistics;

[0010] And, a follow-up statistical analysis is performed on all the targets that have passed the screening in the screening data, and all the targets that have passed the screening are evaluated according to the preset evaluation rules to obtain the targets that have passed the evaluation and the targets that have not passed the evaluation;

[0011] Obtain the subsequent failure impact of the innovation service policy based on the total number of second failures of the failed evaluation targets and the total number of all targets;

[0012] Determine the overall impact identifier corresponding to the innovation service policy based on the calculated pre-screening impact and post-failure impact; analyze the overall impact identifier to evaluate the impact of the implementation of the innovation service policy, as well as provide dynamic prompts and adjustments.

[0013] Preferably, all policy items and corresponding policy conditions included in the innovation service policy are obtained, and the policy items and corresponding policy conditions are sorted and combined to obtain a policy item sequence;

[0014] Sort and combine all normal item sequences to obtain a set of policy conditions;

[0015] According to the policy items corresponding to all policy item sequences in the policy condition set, target conditions corresponding to different targets are obtained in sequence, and all target conditions corresponding to the targets are arranged and combined with the corresponding policy items in order to obtain a target condition set.

[0016] Preferably, when screening and analyzing the matching situations between the target and different policy items in the innovation service policy, the different target conditions in the target condition set corresponding to the target are subjected to data analysis through the policy item matching piecewise function and the corresponding policy item identifiers are output, and the policy item identifiers corresponding to all target conditions of the target are sorted and combined to obtain a policy item screening sequence.

[0017] Preferably, the expression of the policy item matching piecewise function is: Where Mi is the target condition corresponding to different policy items associated with the target; Ui is the policy condition corresponding to different policy items in the innovation service policy.

[0018] Preferably, when determining the matching between the target and the innovation service policy according to the policy item sequence, the policy item screening sequence is traversed and analyzed, and if there is no element with a value of 1 in the policy item screening sequence, the target is marked as a target that has passed the screening;

[0019] If there is an element with a value of 1 in the policy item screening sequence, the target is marked as a target that fails the screening, and the policy item corresponding to the element with a value of 1 is marked as a selected policy item;

[0020] All the targets that have passed the screening are sorted and combined to obtain the data that have passed the screening; and all the targets that have not passed the screening and their corresponding selected policy items are sorted and combined to obtain the data that have not passed the screening.

[0021] Preferably, the total number n of first failures of the targets that failed the screening is counted according to the failed screening data, and the selected policy items corresponding to all the failed screening targets are obtained;

[0022] When all selected policy items are digitized, all selected policy items are traversed and matched with the pre-built policy item impact table in turn to obtain the corresponding policy item impact value Yi, i = 1, 2, 3, ..., n; n is a positive integer; according to the total number of unsuccessful screening data and the impact values ​​of different policy items, the formula Calculate the preliminary screening impact YQ corresponding to the innovation service policy; N is the total number of all targets.

[0023] Preferably, a follow-up statistics is performed on all the screening-passing targets in the screening-passing data, all the screening-passing targets are evaluated according to preset evaluation rules, and the screening-passing targets that pass the evaluation are marked as evaluation-passing targets, and the screening-passing targets that fail the evaluation are marked as evaluation-failed targets;

[0024] The total number of second failures n′ that do not pass the target is statistically evaluated and the formula is used Calculate the subsequent failure impact YH corresponding to the innovation service policy; where N′ is the total number of all targets that passed the screening.

[0025] Preferably, when the overall impact status corresponding to the innovation service policy is determined by integrating the calculated pre-screening impact YQ and the post-screening impact YH, the formula Calculate and obtain the overall impact identifier YZ corresponding to the innovation service policy; where α and β are different impact weights, 0<α<β, α+β=1; A is the standard value of the overall impact status.

[0026] Preferably, when the impact assessment of the innovation service policy is carried out according to the overall impact indicator, if the overall impact indicator is 0, a policy service effective instruction is generated and prompted;

[0027] If the overall impact flag is not 0, an invalid policy service instruction will be generated and prompted, and targeted adjustments and improvements will be made to the subsequent implementation of the same innovative service policy.

[0028] Innovative service policy matching service supervision and processing methods based on artificial intelligence, including:

[0029] Conduct effectiveness screening for all targets of the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform;

[0030] The policy data analysis and management module is used to conduct impact assessment on the innovation service policy based on the screening-failed data and screening-passed data obtained through screening, and dynamically adjust and improve the innovation service policy based on the assessment results.

[0031] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0032] The present invention utilizes different policy items in the innovation service policy to screen different targets and conduct data analysis to obtain the targets that passed the screening and the targets that failed the screening. By processing and combining all the targets that passed the screening and the targets that failed the screening, corresponding passed data and failed data are obtained, which can provide reliable multi-dimensional data support for subsequent innovation service policy impact analysis in different dimensions.

[0033] The present invention calculates the early screening influence and the late screening failure influence of the corresponding dimensions by performing data processing on the screening failure data and the screening pass data obtained by screening, and integrates the early screening influence and the late screening failure influence obtained by different dimensions for calculation and analysis to implement impact evaluation on the innovation service policy, and dynamically adjusts and improves the innovation service policy according to the evaluation results, thereby realizing the supervision and data analysis of the innovation service policy from different dimensions, and multi-dimensional evaluation and prompt management of the innovation service policy, thereby improving the diversity of the supervision of the innovation service policy and the flexibility and adaptability of the active evaluation optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention will be further described below in conjunction with the accompanying drawings.

[0035] Figure 1 This is a module block diagram of the innovative service policy matching service supervision and processing system based on artificial intelligence of the present invention.

[0036] Figure 2 This is a flowchart of the innovative service policy matching service supervision processing method based on artificial intelligence of the present invention. DETAILED DESCRIPTION

[0037] 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.

[0038] Example 1: Figure 1 As shown, the present invention is an innovative service policy matching service supervision processing system based on artificial intelligence, including a policy implementation preprocessing module, a policy data analysis and management module and a cloud platform;

[0039] The policy implementation preprocessing module is used to screen the effectiveness of all targets for the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform; including:

[0040] Obtain all policy items and corresponding policy conditions included in the innovation service policy, sort and combine the policy items and corresponding policy conditions to obtain a policy item sequence;

[0041] It should be explained that policy items include, but are not limited to, enterprise size (e.g., limited to small and micro enterprises), industry sectors, and performance requirements. The policy conditions corresponding to the performance requirements may specifically be certain innovation or performance indicators that the beneficiary may need to achieve, such as the number of patent applications, product development progress, or employment creation targets;

[0042] In addition, the target can be all enterprises in the target area, and the target area can be specifically an administrative district;

[0043] Sort and combine all normal item sequences to obtain a set of policy conditions;

[0044] Obtain target conditions corresponding to different targets in turn according to the policy items corresponding to all policy item sequences in the policy condition set, and arrange and combine all target conditions corresponding to the target with the corresponding policy items in order to obtain a target condition set;

[0045] Among them, the target condition set can provide reliable data support for the subsequent matching status analysis of different targets and different policy items in the innovation service policy;

[0046] When screening and analyzing the matching between the target and different policy items in the innovation service policy, the different target conditions in the target condition set corresponding to the target are subjected to data analysis through the policy item matching piecewise function and the corresponding policy item identifiers are output. The policy item identifiers corresponding to all target conditions of the target are sorted and combined to obtain a policy item screening sequence.

[0047] Among them, the expression of the policy item matching piecewise function is: In the formula, Mi is the target condition corresponding to different policy items associated with the target; Ui is the policy condition corresponding to different policy items in the innovation service policy;

[0048] It is necessary to explain that the policy item identifier is used to digitally represent the matching between the policy conditions corresponding to the policy items in the innovation service policy and the target conditions associated with the target;

[0049] When determining the matching between the target and the innovation service policy according to the policy item sequence, the policy item screening sequence is traversed and analyzed. If there is no element with a value of 1 in the policy item screening sequence, a screening pass label is generated and the target is marked as a screening pass target;

[0050] If there is an element with a value of 1 in the policy item screening sequence, a screening failure label is generated and the target is marked as a screening failure target, and the policy item corresponding to the element with a value of 1 is marked as a selected policy item;

[0051] All the targets that passed the screening are sorted and combined to obtain the data that passed the screening; and all the targets that failed the screening and their corresponding selected policy items are sorted and combined to obtain the data that failed the screening;

[0052] In an embodiment of the present invention, different policy items in the innovation service policy are used to screen different targets and perform data analysis to obtain targets that pass the screening and targets that fail the screening. All the targets that pass the screening and targets that fail the screening are processed and combined to obtain corresponding data that pass the screening and data that fail the screening. This can provide reliable multidimensional data support for subsequent innovation service policy impact analysis in different dimensions.

[0053] The policy data analysis and management module is used to evaluate the impact of the innovation service policy based on the screening failure data and screening pass data obtained through screening, and dynamically adjust and improve the innovation service policy based on the evaluation results; including:

[0054] According to the screening failure data, the total number of first failures n of the screening failure targets is counted, and the selected policy items corresponding to all the screening failure targets are obtained;

[0055] When all selected policy items are digitally processed, all selected policy items are sequentially traversed and matched with the pre-built policy item impact table to obtain the corresponding policy item impact value Yi, i = 1, 2, 3, ..., n; n is a positive integer; i represents different selected policy items;

[0056] It should be noted that the policy item impact table is pre-set with a number of different sample policy items and their corresponding policy item impact values. Different sample policy items are pre-set with a corresponding policy item impact value. The policy item impact value is used to digitize and differentiate the impacts corresponding to different policy items. The specific value of the policy item impact value can be determined based on the total number of occurrences of all selected policy items in history.

[0057] According to the total number of failed data and the impact value of different policy items in the screening, the formula Calculate the pre-screening impact YQ corresponding to the innovation service policy; N is the total number of all targets;

[0058] It should be explained that the pre-screening impact is used to integrate and calculate the different dimensional data of the failed screening to digitally represent the impact of the failed pre-screening. The pre-screening impact can not only digitally represent the impact of the pre-screening, but also provide reliable pre-screening impact analysis data support for the overall impact analysis of the subsequent implementation of the innovation service policy.

[0059] And, performing follow-up statistics on all the screening-passed targets in the screening-passed data, evaluating all the screening-passed targets according to preset evaluation rules, marking the screening-passed targets that passed the evaluation as evaluation-passed targets, and marking the screening-passed targets that failed the evaluation as evaluation-failed targets;

[0060] Among them, the preset evaluation rule can be: the standard increase rate of corporate profits, the specific value can be determined according to the actual application requirements of the actual application scenario, and the corporate profit change data of the screened target within one year can be analyzed and evaluated; that is, when the actual increase rate of the profit of the screened target is greater than or equal to the standard increase rate, the screened target is determined to be an evaluation pass target; otherwise, it is determined to be an evaluation fail target;

[0061] The total number of second failures n′ that do not pass the target is statistically evaluated and the formula is used Calculate the later failure impact YH corresponding to the innovation service policy; where N′ is the total number of all targets that have passed the screening;

[0062] It should be explained that the impact of failure in the later stage is used to integrate and calculate the data of different dimensions of failure in the evaluation to digitally represent the impact of failure in the later stage of the evaluation;

[0063] When the overall impact status of the innovation service policy is determined by integrating the calculated pre-screening impact YQ and the post-screening impact YH, the formula Calculate and obtain the overall impact identifier YZ corresponding to the innovation service policy; where α and β are different impact weights, 0<α<β, α+β=1; A is the standard value of the overall impact status, which can be determined based on the median of all historical overall impact status values, where the overall impact status value is

[0064] When implementing the impact assessment of the innovation service policy based on the overall impact indicator, if the overall impact indicator is 0, a policy service effective instruction is generated and prompted;

[0065] If the overall impact indicator is not 0, an invalid policy service instruction will be generated and prompted, and targeted adjustments and improvements will be made to the subsequent implementation of the same innovative service policy;

[0066] Among them, targeted adjustments are implemented completely, and the total number of occurrences corresponding to all selected policy items can be counted, and all selected policy items are sorted in descending order according to the value of the total number of occurrences, and the selected policy items corresponding to the total number of occurrences greater than the standard total number of occurrences are marked as adjustment policy items and optimized and adjusted; the standard total number of occurrences can be customized according to the actual application needs of the actual application scenario, and all selected policy items that appear can also be optimized and adjusted;

[0067] In the embodiment of the present invention, the early screening influence and the late screening failure influence of the corresponding dimension are calculated by processing the screening failure data and the screening pass data obtained by screening, and the early screening influence and the late screening failure influence obtained by different dimensions are integrated and calculated and analyzed to implement the impact evaluation of the innovation service policy, and the innovation service policy is dynamically adjusted and improved according to the evaluation results, thereby realizing the supervision and data analysis of the innovation service policy from different dimensions, and multi-dimensional evaluation and prompt management of the innovation service policy, thereby improving the diversity of the supervision of the innovation service policy and the flexibility and adaptability of the active evaluation optimization.

[0068] Example 2: Figure 2 As shown, the present invention is an innovative service policy matching service supervision processing method based on artificial intelligence, comprising:

[0069] Conduct effectiveness screening for all targets of the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform;

[0070] The policy data analysis and management module is used to conduct impact assessment on the innovation service policy based on the screening-failed data and screening-passed data obtained through screening, and dynamically adjust and improve the innovation service policy based on the assessment results.

[0071] 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.

[0072] In the several embodiments provided by the present invention, it should be understood that the disclosed system and method 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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 innovative service policy matching service supervision and processing system based on artificial intelligence, characterized by: include: The policy implementation preprocessing module is used to screen the effectiveness of all targets for the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform; The policy data analysis and management module is used to evaluate the impact of the innovation service policy based on the screening failure data and screening pass data obtained through screening, and dynamically adjust and improve the innovation service policy based on the evaluation results; Among them, the preliminary screening influence corresponding to the innovation service policy is obtained based on the first total number of failed screening targets and the selected policy items corresponding to all failed screening targets according to the failed screening data statistics; And, a follow-up statistical analysis is performed on all the targets that have passed the screening in the screening data, and all the targets that have passed the screening are evaluated according to the preset evaluation rules to obtain the targets that have passed the evaluation and the targets that have not passed the evaluation; Obtain the subsequent failure impact of the innovation service policy based on the total number of second failures of the failed evaluation targets and the total number of all targets; Determine the overall impact identifier corresponding to the innovation service policy based on the calculated initial screening impact and the subsequent failure impact; analyze the overall impact identifier to evaluate the impact of the implementation of the innovation service policy, as well as provide dynamic prompts and adjustments.

2. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 1 is characterized in that: Obtain all policy items and corresponding policy conditions included in the innovation service policy, sort and combine the policy items and corresponding policy conditions to obtain a policy item sequence; Sort and combine all normal item sequences to obtain a set of policy conditions; According to the policy items corresponding to all policy item sequences in the policy condition set, target conditions corresponding to different targets are obtained in sequence, and all target conditions corresponding to the targets are arranged and combined with the corresponding policy items in order to obtain a target condition set.

3. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 2 is characterized in that: When screening and analyzing the matching situations between the target and different policy items in the innovation service policy, the different target conditions in the target condition set corresponding to the target are subjected to data analysis through the policy item matching piecewise function and the corresponding policy item identifiers are output. The policy item identifiers corresponding to all target conditions of the target are sorted and combined to obtain a policy item screening sequence.

4. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 3 is characterized in that: The expression of the policy term matching piecewise function is: Where Mi is the target condition corresponding to different policy items associated with the target; Ui is the policy condition corresponding to different policy items in the innovation service policy.

5. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 3 is characterized in that: When determining the matching between the target and the innovation service policy according to the policy item sequence, the policy item screening sequence is traversed and analyzed. If there is no element with a value of 1 in the policy item screening sequence, the target is marked as a target that has passed the screening. If there is an element with a value of 1 in the policy item screening sequence, the target is marked as a target that fails the screening, and the policy item corresponding to the element with a value of 1 is marked as a selected policy item; All the targets that have passed the screening are sorted and combined to obtain the data that have passed the screening; and all the targets that have not passed the screening and their corresponding selected policy items are sorted and combined to obtain the data that have not passed the screening.

6. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 5 is characterized in that: According to the screening failure data, the total number of first failures n of the screening failure targets is counted, and the selected policy items corresponding to all the screening failure targets are obtained; When all selected policy items are digitized, all selected policy items are traversed and matched with the pre-built policy item impact table in turn to obtain the corresponding policy item impact value Yi, i = 1, 2, 3, ..., n; n is a positive integer; according to the total number of unsuccessful screening data and the impact values ​​of different policy items, the formula Calculate the preliminary screening impact YQ corresponding to the innovation service policy; N is the total number of all targets.

7. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 6 is characterized in that: Performing follow-up statistics on all the screening-passing targets in the screening-passing data, evaluating all the screening-passing targets according to preset evaluation rules, marking the screening-passing targets that have passed the evaluation as evaluation-passing targets, and marking the screening-passing targets that have failed the evaluation as evaluation-failed targets; The total number of second failures n′ that do not pass the target is statistically evaluated and the formula is used Calculate the subsequent failure impact YH corresponding to the innovation service policy; where N′ is the total number of all targets that passed the screening.

8. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 7 is characterized in that: When the overall impact status of the innovation service policy is determined by integrating the calculated pre-screening impact YQ and the post-screening impact YH, the formula Calculate and obtain the overall impact identifier YZ corresponding to the innovation service policy; where α and β are different impact weights, 0<α<β, α+β=1; A is the standard value of the overall impact status.

9. The artificial intelligence-based innovative service policy matching service supervision and processing system according to claim 8 is characterized in that: When implementing the impact assessment of the innovation service policy based on the overall impact indicator, if the overall impact indicator is 0, a policy service effective instruction is generated and prompted; If the overall impact flag is not 0, an invalid policy service instruction will be generated and prompted, and targeted adjustments and improvements will be made to the subsequent implementation of the same innovative service policy.

10. An artificial intelligence-based innovative service policy matching service supervision processing method, using an artificial intelligence-based innovative service policy matching service supervision processing system as described in any one of claims 1 to 9, characterized in that: include: Conduct effectiveness screening for all targets of the implementation of the innovation service policy, obtain the data that passed the screening and the data that failed the screening and upload them to the cloud platform; The policy data analysis and management module is used to conduct impact assessment on the innovation service policy based on the screening-failed data and screening-passed data obtained through screening, and dynamically adjust and improve the innovation service policy based on the assessment results.

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