Execution progress rationality evaluation system and method based on supervision process data

Abstract

The invention discloses an execution progress rationality evaluation system and method based on supervision process data, and belongs to the technical field of progress evaluation, and the system comprises an acquisition storage module, a data processing module, a model training module, a model optimization module, a prediction evaluation module and an early warning management and control module. According to the invention, the problems that the execution progress is slow and the quality and efficiency of project management are reduced due to the fact that the execution progress rationality cannot be effectively evaluated based on supervision process data, the project execution progress cannot be known in time and the project execution progress cannot be effectively managed and controlled in the prior art are solved. The supervision process feature data is predicted and evaluated based on the optimal execution process rationality evaluation model, the execution process rationality can be effectively evaluated based on the supervision process data, the execution process of the project can be known in time, the execution process of the project can be effectively controlled, the execution process of the project can be accelerated, and the project execution efficiency is improved. And the project management quality and efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of progress evaluation, and in particular to a system and method for evaluating the rationality of execution progress based on supervision process data. Background Art

[0002] In many industries, such as finance, healthcare, and education, regulators usually develop a set of complex regulatory processes to ensure compliance with relevant regulations and standards; these processes may include multiple tasks and nodes, each of which has specific completion conditions and time requirements. However, in actual operations, the execution of tasks is often affected by various factors, such as personnel changes, resource constraints, etc. Therefore, how to reasonably evaluate these impacts to ensure the effectiveness and compliance of regulatory processes has become an urgent problem to be solved.

[0003] The Chinese patent with publication number CN111429118B discloses a financial cloud business process engine and a business process processing method. The financial cloud business process engine includes a business processing process engine and a business approval process engine, wherein each engine includes: a process execution command class, which executes and calls a standard interface through a command mode to complete the operation instruction, complete the process node flow, business data verification and recording; a standard interface, which has an implementation class of the standard interface written by SOFARPC, so that data can be obtained by calling the corresponding standard interface during the execution of the business processing process and the business approval process; wherein each business in the business processing process formed by the business processing process engine corresponds to a processing node ID, and each approval task in the business approval process formed by the business approval process engine corresponds to a progress node ID, and the processing of the same business is associated by the same processing node ID and progress node ID; however, the patent has the following defects:

[0004] The existing system cannot effectively evaluate the rationality of the execution progress based on the supervision process data, cannot timely understand the execution progress of the project, and cannot effectively control the execution progress of the project, resulting in slow project execution progress and reducing the quality and efficiency of project management. Summary of the invention

[0005] The purpose of the present invention is to provide an execution progress rationality evaluation system and method based on supervision process data, which can effectively evaluate the rationality of the execution progress based on the supervision process data, timely understand the execution progress of the project, and effectively control the execution progress of the project, thereby speeding up the execution progress of the project, improving the quality and efficiency of project management, and solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The execution progress rationality evaluation system based on the supervision process data includes:

[0008] The collection and storage module is used to collect and store real-time data of the supervision process;

[0009] The data processing module is used to process the real-time data of the supervision process and determine the characteristic data of the supervision process;

[0010] Model training module, used to build an execution progress rationality assessment model based on regulatory process data;

[0011] The model optimization module is used to optimize the execution progress rationality evaluation model and determine the best execution progress rationality evaluation model;

[0012] The prediction and evaluation module is used to predict and evaluate the characteristic data of the regulatory process and determine the evaluation results of the rationality of the execution progress based on the regulatory process data;

[0013] Visually display the real-time data of the supervision process and the evaluation results of the rationality of the execution progress to users, providing a basis for subsequent users to allocate, monitor and adjust projects;

[0014] The early warning and control module is used to conduct intelligent early warning and control of the project execution progress.

[0015] Preferably, the acquisition and storage module includes:

[0016] The data collection unit is used to collect project information in the supervision process in real time and determine the real-time data of the supervision process;

[0017] The data storage unit is used to store the collected real-time data of the supervision process, providing a basis for the subsequent evaluation of the rationality of the execution progress.

[0018] Preferably, the data processing module includes:

[0019] Data retrieval unit, used to retrieve real-time data of the regulatory process;

[0020] Obtain real-time data on regulatory processes;

[0021] Retrieve real-time data of regulatory processes based on sequential retrieval methods;

[0022] Conduct consistency checks on real-time data for regulatory processes;

[0023] Check whether the real-time data of the regulatory process meets the requirements based on the reasonable value range and mutual relationship of each variable in the real-time data of the regulatory process;

[0024] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of the regulatory process;

[0025] Process invalid and missing values ​​in real-time data of regulatory processes;

[0026] Remove invalid and missing data in the real-time data of the regulatory process that are of no value to the evaluation of the rationality of the execution progress;

[0027] Identify real-time data of the supervisory process that is valuable for evaluating the reasonableness of execution progress;

[0028] A feature extraction unit, used for extracting features from the retrieved real-time data of the regulatory process;

[0029] Obtaining real-time data on the supervisory process that is valuable for evaluating the reasonableness of execution progress;

[0030] Extract features from real-time data of regulatory processes that are valuable for evaluating the rationality of execution progress;

[0031] Determine the characteristic data of the regulatory process.

[0032] Preferably, the model training module includes:

[0033] A collection and division unit is used to collect and divide historical data of the supervision process;

[0034] According to the need for reasonableness assessment of execution progress based on regulatory process data, a large amount of historical regulatory process data that can reflect the characteristics of the regulatory process is collected;

[0035] Divide the collected historical data of regulatory processes into training sets and test sets;

[0036] Model training unit, used to build an execution progress rationality assessment model;

[0037] According to the needs of execution progress rationality assessment based on regulatory process data, a neural network model framework suitable for execution progress rationality assessment is selected;

[0038] Based on the training set, the neural network model framework selected for the execution progress rationality assessment is trained to build an execution progress rationality assessment model based on the regulatory process data.

[0039] Preferably, the model optimization module includes:

[0040] Model testing unit, used to test the execution progress rationality assessment model;

[0041] Obtain an execution progress rationality assessment model based on regulatory process data;

[0042] Based on the test set, the execution progress rationality assessment model based on the regulatory process data is tested;

[0043] Determine the performance test results based on the execution schedule rationality assessment model;

[0044] Model optimization unit, used to optimize the execution progress rationality evaluation model;

[0045] Obtain performance test results based on the execution progress rationality assessment model;

[0046] Mining and analyzing the performance test results based on the execution progress rationality evaluation model;

[0047] Determine the optimization adjustment method based on the execution progress rationality evaluation model;

[0048] Optimize the execution progress rationality assessment model according to the optimization adjustment method;

[0049] Determine the best execution schedule rationality assessment model.

[0050] Preferably, the prediction and evaluation module includes:

[0051] A data extraction unit, used to extract characteristic data of the supervision process;

[0052] According to the requirements of execution progress rationality assessment based on regulatory process data, the regulatory process characteristic data is extracted to provide data support for subsequent execution progress rationality assessment;

[0053] A prediction and evaluation unit, used to perform prediction and evaluation on the characteristic data of the regulatory process;

[0054] Obtain the best execution schedule rationality assessment model;

[0055] Input the regulatory process characteristics data into the optimal execution schedule reasonableness assessment model;

[0056] Predict and evaluate the characteristic data of the regulatory process based on the optimal execution progress rationality assessment model;

[0057] Determine the reasonableness of the execution progress assessment results based on the regulatory process data;

[0058] Among them, the evaluation result of the rationality of the execution progress is that the execution progress is reasonable or the execution progress is unreasonable.

[0059] Preferably, the prediction and evaluation module further includes:

[0060] The interface display unit is used to visually display the real-time data of the supervision process and the rationality evaluation results of the execution progress to the user;

[0061] Obtain real-time data on the regulatory process and evaluation results of the rationality of the execution progress;

[0062] Conduct mining and analysis on real-time data of regulatory processes and evaluation results of rationality of execution progress;

[0063] Determine the visual report of the supervision process, and upload the visual report of the supervision process to the user terminal in real time.

[0064] Visually display the real-time data of the supervision process and the rationality assessment results of the execution progress to users, providing a basis for subsequent users to allocate, monitor and adjust projects.

[0065] Preferably, the early warning control module includes:

[0066] Strategy formulation unit, used to formulate execution progress early warning control plan;

[0067] Obtain the reasonableness assessment results of execution progress based on regulatory process data;

[0068] Conduct mining and analysis on the evaluation results of the rationality of the execution progress;

[0069] Determine the early warning and control plan for execution progress;

[0070] Early warning control unit, used to conduct early warning control of the project execution progress;

[0071] Obtain the execution progress early warning control plan;

[0072] Based on the execution progress early warning control plan, the project execution progress is intelligently warned and controlled.

[0073] Preferably, intelligent early warning control is performed on the execution progress, and the following operations are performed:

[0074] Provide timely warnings for projects with unreasonable execution progress, and promptly investigate the reasons for the unreasonable project execution progress. Based on the reasons for the unreasonable project execution progress, formulate project improvement measures, and accelerate the project execution progress based on the project improvement measures.

[0075] According to another aspect of the present invention, a method for evaluating the rationality of execution progress based on regulatory process data is provided, which is implemented based on the above-mentioned system for evaluating the rationality of execution progress based on regulatory process data, and includes the following steps:

[0076] S1: Collect and process real-time data of the supervision process to determine the characteristic data of the supervision process;

[0077] S2: Construct an execution progress rationality evaluation model based on regulatory process data, optimize the execution progress rationality evaluation model, and determine the best execution progress rationality evaluation model;

[0078] S3: Predict and evaluate the regulatory process characteristic data based on the optimal execution progress rationality evaluation model, and determine the execution progress rationality evaluation results based on the regulatory process data;

[0079] S4: Based on the results of the execution progress rationality assessment, formulate an execution progress early warning and control plan, and conduct intelligent early warning and control of the project's execution progress based on the execution progress early warning and control plan.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] The present invention collects real-time data of the supervision process, processes the real-time data of the supervision process, determines the characteristic data of the supervision process, constructs an execution progress rationality evaluation model based on the supervision process data according to the execution progress rationality evaluation demand based on the supervision process data, optimizes the execution progress rationality evaluation model, determines the best execution progress rationality evaluation model, predicts and evaluates the characteristic data of the supervision process based on the best execution progress rationality evaluation model, determines the execution progress rationality evaluation result based on the supervision process data, formulates an execution progress early warning control plan based on the execution progress rationality evaluation result, and performs intelligent early warning control on the execution progress of the project based on the execution progress early warning control plan. The rationality of the execution progress can be effectively evaluated based on the supervision process data, the execution progress of the project can be understood in time, and the execution progress of the project can be effectively controlled, so as to speed up the execution progress of the project and improve the quality and efficiency of project management. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 It is a structural diagram of the execution progress rationality evaluation system based on supervision process data of the present invention;

[0083] Figure 2 The present invention is a flowchart of the method for evaluating the rationality of execution progress based on regulatory process data. DETAILED DESCRIPTION

[0084] 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.

[0085] In order to solve the existing problems of not being able to effectively evaluate the rationality of the execution progress based on the supervision process data, not being able to timely understand the execution progress of the project, and not being able to effectively control the execution progress of the project, resulting in slow project execution progress and reducing the quality and efficiency of project management, please refer to Figure 1-Figure 2, this embodiment provides the following technical solutions:

[0086] The execution progress rationality evaluation system based on regulatory process data includes a collection and storage module, a data processing module, a model training module, a model optimization module, a prediction and evaluation module, and an early warning control module.

[0087] It should be noted that through the interactive communication between the collection and storage module, data processing module, model training module, model optimization module, prediction and evaluation module and early warning control module, the rationality of the execution progress can be effectively evaluated based on the supervision process data, the execution progress of the project can be understood in time, and the execution progress of the project can be effectively controlled, which can speed up the execution progress of the project and improve the quality and efficiency of project management.

[0088] Among them, the collection and storage module is used to collect and store real-time data of the supervision process;

[0089] In this embodiment, the acquisition and storage module includes:

[0090] The data collection unit is used to collect project information in the supervision process in real time and determine the real-time data of the supervision process;

[0091] The data storage unit is used to store the collected real-time data of the supervision process, providing a basis for the subsequent evaluation of the rationality of the execution progress.

[0092] Among them, the data processing module is used to process the real-time data of the supervision process and determine the characteristic data of the supervision process;

[0093] In this embodiment, the data processing module includes:

[0094] Data retrieval unit, used to retrieve real-time data of the regulatory process;

[0095] Obtain real-time data on regulatory processes;

[0096] Retrieve real-time data of regulatory processes based on sequential retrieval methods;

[0097] Conduct consistency checks on real-time data for regulatory processes;

[0098] Check whether the real-time data of the regulatory process meets the requirements based on the reasonable value range and mutual relationship of each variable in the real-time data of the regulatory process;

[0099] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of the regulatory process;

[0100] Process invalid and missing values ​​in real-time data of regulatory processes;

[0101] Remove invalid and missing data in the real-time data of the regulatory process that are of no value to the evaluation of the rationality of the execution progress;

[0102] Identify real-time data of the supervisory process that is valuable for evaluating the reasonableness of execution progress;

[0103] A feature extraction unit, used for extracting features from the retrieved real-time data of the regulatory process;

[0104] Obtaining real-time data on the supervisory process that is valuable for evaluating the reasonableness of execution progress;

[0105] Extract features from real-time data of regulatory processes that are valuable for evaluating the rationality of execution progress;

[0106] Determine the characteristic data of the regulatory process.

[0107] Among them, the model training module is used to build an execution progress rationality assessment model based on regulatory process data;

[0108] In this embodiment, the model training module includes:

[0109] A collection and division unit is used to collect and divide historical data of the supervision process;

[0110] According to the need for reasonableness assessment of execution progress based on regulatory process data, a large amount of historical regulatory process data that can reflect the characteristics of the regulatory process is collected;

[0111] Divide the collected historical data of regulatory processes into training sets and test sets;

[0112] Model training unit, used to build an execution progress rationality assessment model;

[0113] According to the needs of execution progress rationality assessment based on regulatory process data, a neural network model framework suitable for execution progress rationality assessment is selected;

[0114] Based on the training set, the neural network model framework selected for the execution progress rationality assessment is trained to build an execution progress rationality assessment model based on the regulatory process data.

[0115] Among them, the model optimization module is used to optimize the execution progress rationality evaluation model and determine the best execution progress rationality evaluation model;

[0116] In this embodiment, the model optimization module includes:

[0117] Model testing unit, used to test the execution progress rationality assessment model;

[0118] Obtain an execution progress rationality assessment model based on regulatory process data;

[0119] Based on the test set, the execution progress rationality assessment model based on the regulatory process data is tested;

[0120] Determine the performance test results based on the execution schedule rationality assessment model;

[0121] Model optimization unit, used to optimize the execution progress rationality evaluation model;

[0122] Obtain performance test results based on the execution progress rationality assessment model;

[0123] Mining and analyzing the performance test results based on the execution progress rationality evaluation model;

[0124] Determine the optimization adjustment method based on the execution progress rationality evaluation model;

[0125] Optimize the execution progress rationality assessment model according to the optimization adjustment method;

[0126] Determine the best execution schedule rationality assessment model.

[0127] Among them, the prediction and evaluation module is used to predict and evaluate the characteristic data of the supervision process and determine the evaluation results of the rationality of the execution progress based on the supervision process data;

[0128] In this embodiment, the prediction and evaluation module includes:

[0129] A data extraction unit, used to extract characteristic data of the supervision process;

[0130] According to the requirements of execution progress rationality assessment based on regulatory process data, the regulatory process characteristic data is extracted to provide data support for subsequent execution progress rationality assessment;

[0131] A prediction and evaluation unit, used to perform prediction and evaluation on the characteristic data of the regulatory process;

[0132] Obtain the best execution schedule rationality assessment model;

[0133] Input the regulatory process characteristics data into the optimal execution schedule reasonableness assessment model;

[0134] Predict and evaluate the characteristic data of the regulatory process based on the optimal execution progress rationality assessment model;

[0135] Determine the reasonableness of the execution progress assessment results based on the regulatory process data;

[0136] Among them, the evaluation result of the rationality of the execution progress is that the execution progress is reasonable or the execution progress is unreasonable.

[0137] In this embodiment, the prediction and evaluation module further includes:

[0138] The interface display unit is used to visually display the real-time data of the supervision process and the rationality evaluation results of the execution progress to the user;

[0139] Obtain real-time data on the regulatory process and evaluation results of the rationality of the execution progress;

[0140] Conduct mining and analysis on real-time data of regulatory processes and evaluation results of rationality of execution progress;

[0141] Determine the visual report of the supervision process, and upload the visual report of the supervision process to the user terminal in real time.

[0142] Visually display the real-time data of the supervision process and the rationality assessment results of the execution progress to users, providing a basis for subsequent users to allocate, monitor and adjust projects.

[0143] Among them, the early warning and control module is used to carry out intelligent early warning and control of the project execution progress.

[0144] In this embodiment, the early warning control module includes:

[0145] Strategy formulation unit, used to formulate execution progress early warning control plan;

[0146] Obtain the reasonableness assessment results of execution progress based on regulatory process data;

[0147] Conduct mining and analysis on the evaluation results of the rationality of the execution progress;

[0148] Determine the early warning and control plan for execution progress;

[0149] Early warning control unit, used to conduct early warning control of the project execution progress;

[0150] Obtain the execution progress early warning control plan;

[0151] Based on the execution progress early warning control plan, the project execution progress is intelligently warned and controlled.

[0152] In this embodiment, intelligent early warning control is performed on the execution progress, and the following operations are performed:

[0153] Provide timely warnings for projects with unreasonable execution progress, and promptly investigate the reasons for the unreasonable project execution progress. Based on the reasons for the unreasonable project execution progress, formulate project improvement measures, and accelerate the project execution progress based on the project improvement measures.

[0154] In order to better present the execution progress rationality evaluation process based on the supervision process data, this embodiment now provides an execution progress rationality evaluation method based on the supervision process data, which is implemented based on the above-mentioned execution progress rationality evaluation system based on the supervision process data, including the following steps:

[0155] S1: Collect and process real-time data of the supervision process to determine the characteristic data of the supervision process;

[0156] S2: Construct an execution progress rationality evaluation model based on regulatory process data, optimize the execution progress rationality evaluation model, and determine the best execution progress rationality evaluation model;

[0157] S3: Predict and evaluate the regulatory process characteristic data based on the optimal execution progress rationality evaluation model, and determine the execution progress rationality evaluation results based on the regulatory process data;

[0158] S4: Based on the results of the execution progress rationality assessment, formulate an execution progress early warning and control plan, and conduct intelligent early warning and control of the project's execution progress based on the execution progress early warning and control plan.

[0159] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0160] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An execution progress rationality evaluation system based on supervision process data, characterized in that: include: The collection and storage module is used to collect and store real-time data of the supervision process; The data processing module is used to process the real-time data of the supervision process and determine the characteristic data of the supervision process; Model training module, used to build an execution progress rationality assessment model based on regulatory process data; The model optimization module is used to optimize the execution progress rationality evaluation model and determine the best execution progress rationality evaluation model; The prediction and evaluation module is used to predict and evaluate the characteristic data of the regulatory process and determine the evaluation results of the rationality of the execution progress based on the regulatory process data; Visually display the real-time data of the supervision process and the evaluation results of the rationality of the execution progress to users, providing a basis for subsequent users to allocate, monitor and adjust projects; The early warning and control module is used to conduct intelligent early warning and control of the project execution progress.

2. The execution progress rationality evaluation system based on supervision process data according to claim 1 is characterized in that: The acquisition storage module comprises: The data collection unit is used to collect project information in the supervision process in real time and determine the real-time data of the supervision process; The data storage unit is used to store the collected real-time data of the supervision process, providing a basis for the subsequent evaluation of the rationality of the execution progress.

3. The execution progress rationality evaluation system based on supervision process data according to claim 2 is characterized in that: The data processing module comprises: Data retrieval unit, used to retrieve real-time data of the regulatory process; Obtain real-time data on regulatory processes; Retrieve real-time data of regulatory processes based on sequential retrieval methods; Conduct consistency checks on real-time data for regulatory processes; Check whether the real-time data of the regulatory process meets the requirements based on the reasonable value range and mutual relationship of each variable in the real-time data of the regulatory process; Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of the regulatory process; Process invalid and missing values ​​in real-time data of regulatory processes; Remove invalid and missing data in the real-time data of the regulatory process that are of no value to the evaluation of the rationality of the execution progress; Identify real-time data of the supervisory process that is valuable for evaluating the reasonableness of execution progress; A feature extraction unit, used for extracting features from the retrieved real-time data of the regulatory process; Obtaining real-time data on the supervisory process that is valuable for evaluating the reasonableness of execution progress; Extract features from real-time data of regulatory processes that are valuable for evaluating the rationality of execution progress; Determine the characteristic data of the regulatory process.

4. The execution progress rationality evaluation system based on supervision process data according to claim 3 is characterized in that: The model training module includes: A collection and division unit is used to collect and divide historical data of the supervision process; According to the need for reasonableness assessment of execution progress based on regulatory process data, a large amount of historical regulatory process data that can reflect the characteristics of the regulatory process is collected; Divide the collected historical data of regulatory processes into training sets and test sets; Model training unit, used to build an execution progress rationality assessment model; According to the needs of execution progress rationality assessment based on regulatory process data, a neural network model framework suitable for execution progress rationality assessment is selected; Based on the training set, the neural network model framework selected for the execution progress rationality assessment is trained to build an execution progress rationality assessment model based on the regulatory process data.

5. The execution progress rationality evaluation system based on supervision process data according to claim 4 is characterized in that: The model optimization module includes: Model testing unit, used to test the execution progress rationality assessment model; Obtain an execution progress rationality assessment model based on regulatory process data; Based on the test set, the execution progress rationality assessment model based on the regulatory process data is tested; Determine the performance test results based on the execution schedule rationality assessment model; Model optimization unit, used to optimize the execution progress rationality evaluation model; Obtain performance test results based on the execution progress rationality assessment model; Mining and analyzing the performance test results based on the execution progress rationality evaluation model; Determine the optimization adjustment method based on the execution progress rationality evaluation model; Optimize the execution progress rationality assessment model according to the optimization adjustment method; Determine the best execution schedule rationality assessment model.

6. The execution progress rationality evaluation system based on supervision process data according to claim 5 is characterized in that: The prediction and evaluation module comprises: A data extraction unit, used to extract characteristic data of the supervision process; According to the requirements of execution progress rationality assessment based on regulatory process data, the regulatory process characteristic data is extracted to provide data support for subsequent execution progress rationality assessment; A prediction and evaluation unit, used to perform prediction and evaluation on the characteristic data of the regulatory process; Obtain the best execution schedule rationality assessment model; Input the regulatory process characteristics data into the optimal execution schedule reasonableness assessment model; Predict and evaluate the characteristic data of the regulatory process based on the optimal execution progress rationality assessment model; Determine the reasonableness of the execution progress assessment results based on the regulatory process data; Among them, the evaluation result of the rationality of the execution progress is that the execution progress is reasonable or the execution progress is unreasonable.

7. The execution progress rationality evaluation system based on supervision process data according to claim 6 is characterized in that: The prediction and evaluation module also includes: The interface display unit is used to visually display the real-time data of the supervision process and the rationality evaluation results of the execution progress to the user; Obtain real-time data on the regulatory process and evaluation results of the rationality of the execution progress; Conduct mining and analysis on real-time data of regulatory processes and evaluation results of rationality of execution progress; Determine the visual report of the supervision process, and upload the visual report of the supervision process to the user terminal in real time. Visually display the real-time data of the supervision process and the rationality assessment results of the execution progress to users, providing a basis for subsequent users to allocate, monitor and adjust projects.

8. The execution progress rationality evaluation system based on supervision process data according to claim 7 is characterized in that: The early warning control module includes: Strategy formulation unit, used to formulate execution progress early warning control plan; Obtain the reasonableness assessment results of execution progress based on regulatory process data; Conduct mining and analysis on the evaluation results of the rationality of the execution progress; Determine the early warning and control plan for execution progress; Early warning control unit, used to conduct early warning control of the project execution progress; Obtain the execution progress early warning control plan; Based on the execution progress early warning control plan, the project execution progress is intelligently warned and controlled.

9. The execution progress rationality evaluation system based on supervision process data according to claim 8 is characterized in that: To conduct intelligent early warning control of execution progress, perform the following operations: Provide timely warnings for projects with unreasonable execution progress, and promptly investigate the reasons for the unreasonable project execution progress. Based on the reasons for the unreasonable project execution progress, formulate project improvement measures, and accelerate the project execution progress based on the project improvement measures.

10. The method for evaluating the rationality of execution progress based on regulatory process data is implemented based on the system for evaluating the rationality of execution progress based on regulatory process data according to claim 9, characterized in that: The steps include: S1: Collect and process real-time data of the supervision process to determine the characteristic data of the supervision process; S2: Construct an execution progress rationality evaluation model based on regulatory process data, optimize the execution progress rationality evaluation model, and determine the best execution progress rationality evaluation model; S3: Predict and evaluate the regulatory process characteristic data based on the optimal execution progress rationality evaluation model, and determine the execution progress rationality evaluation results based on the regulatory process data; S4: Based on the results of the execution progress rationality assessment, formulate an execution progress early warning and control plan, and conduct intelligent early warning and control of the project's execution progress based on the execution progress early warning and control plan.

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