Project progress evaluation method and system

Abstract

The invention discloses a project progress evaluation method and system, and the method comprises the steps: obtaining the historical task data of a target project in each stage in a full life cycle, extracting the stage task index data of each stage, and carrying out the comparative analysis of the stage task index data and pre-established standardized index data, obtaining a deviation value of task index data of each stage, calculating according to the deviation value to obtain a priority sequence of short-term deviation correction of the target project in each stage, extracting real-time progress data of each stage from a project monitoring system, and calculating the real-time progress data through time sequence analysis to obtain a monitoring vector group of each stage; and according to each monitoring vector group, performing calculation by adopting a staged scoring model to obtain a progress score of each stage, correcting each progress score by adopting a dynamic weight adjustment algorithm, and evaluating the project progress of the target project. According to the invention, the project progress can be monitored in a segmented manner to realize whole-course tracking, and the accuracy of project progress evaluation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of project management, and in particular to a project progress evaluation method and system. Background Art

[0002] As the complexity of enterprise management and project advancement continues to increase, the role of progress evaluation in improving efficiency, optimizing resource allocation and achieving strategic goals is becoming increasingly prominent.

[0003] However, existing progress assessment methods have significant limitations. Many traditional approaches tend to conduct a one-time, comprehensive evaluation after the project is completed, neglecting ongoing monitoring and making it difficult to promptly correct short-term deviations. Furthermore, existing methods often focus on fixed indicators and weights, lacking adaptability to the actual conditions at different stages and making it difficult to balance long-term goals with short-term progress. This static and single-minded evaluation model is no longer able to meet the dynamic development needs of modern enterprises.

[0004] It can be seen that how to dynamically evaluate the progress of each stage of the target project according to the entire project life cycle has become a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the Invention

[0005] The present invention provides a project progress evaluation method and system for comprehensively evaluating project progress.

[0006] In order to solve the above technical problems, an embodiment of the present invention provides a project progress evaluation method, comprising:

[0007] Obtain historical task data for each stage of the target project's life cycle, and extract stage task indicator data for each stage from each of the historical task data.

[0008] By comparing and analyzing the stage task indicator data with pre-established standardized indicator data, the deviation value of each stage task indicator data is obtained.

[0009] A priority sequence for short-term deviation correction of the target project at each stage is calculated based on the deviation value.

[0010] The real-time progress data of each stage is extracted from the project monitoring system according to the priority sequence, and the monitoring vector group of each stage is obtained by calculating the real-time progress data through time series analysis.

[0011] A first progress score for each stage is calculated based on each monitoring vector group using a staged scoring model, and each first progress score is corrected using a dynamic weight adjustment algorithm to obtain a second progress score.

[0012] The project progress of the target project is evaluated according to each of the second progress scores.

[0013] Furthermore, the stage task indicator data includes several task subsets of the corresponding stage, and the timestamp and completion status of each task subset.

[0014] The step of obtaining historical task data of each stage of the target project in its entire life cycle and extracting stage task indicator data of each stage from each of the historical task data includes:

[0015] Obtain historical task data of the target project at each stage in its entire life cycle, and extract the task decomposition structure from the historical task data at each stage.

[0016] According to the task decomposition structure, the tasks of the corresponding stage are divided into a number of task subsets, and the timestamp and completion status of each task subset are obtained.

[0017] Furthermore, the comparative analysis of the stage task indicator data with pre-established standardized indicator data to obtain the deviation value of each stage task indicator data includes:

[0018] Obtain standardized indicator data for each stage from a pre-built standardized indicator database.

[0019] The stage task index data and the standardized index data are compared and analyzed item by item to obtain the deviation value of each stage task index data, and the deviation value is D:

[0020] D=(RA) / R

[0021] Among them, R is the standardized indicator data, and A is the stage task indicator data.

[0022] Furthermore, the priority sequence of short-term deviation correction of the target project at each stage is calculated based on the deviation value, including:

[0023] The total deviation value of the corresponding stage is calculated based on the deviation values corresponding to each task subset in each stage.

[0024] The total deviation values of each stage are sorted to obtain a priority sequence for short-term deviation correction of the target project at each stage.

[0025] Furthermore, extracting the real-time progress data of each stage from the project monitoring system according to the priority sequence and calculating the monitoring vector group of each stage by time series analysis on the real-time progress data includes:

[0026] According to the priority sequence, the real-time progress data of each stage corresponding to the priority is sequentially extracted from the project monitoring system.

[0027] A time series analysis method is used to perform trend analysis and fluctuation analysis on the real-time progress data to obtain key characteristic parameters of each stage.

[0028] Feature vectors are extracted from the key feature parameters to obtain monitoring vector groups for each stage.

[0029] Another embodiment of the present invention provides a project progress evaluation system, including:

[0030] The data acquisition module is used to obtain the historical task data of the target project at each stage in the entire life cycle, and extract the stage task indicator data of each stage from each of the historical task data.

[0031] The deviation calculation module is used to compare and analyze the stage task indicator data with pre-established standardized indicator data to obtain the deviation value of each stage task indicator data.

[0032] A priority sorting module is used to calculate the priority sequence of short-term deviation correction of the target project at each stage based on the deviation value.

[0033] The vector calculation module is used to extract the real-time progress data of each stage from the project monitoring system according to the priority sequence, and calculate the real-time progress data through time series analysis to obtain the monitoring vector group of each stage.

[0034] The progress scoring module is configured to calculate a first progress score for each stage using a stage scoring model according to each monitoring vector group, and to modify each first progress score using a dynamic weight adjustment algorithm to obtain a second progress score.

[0035] A progress evaluation module is used to evaluate the project progress of the target project according to each second progress score.

[0036] Furthermore, the stage task indicator data includes several task subsets of the corresponding stage, and the timestamp and completion status of each task subset.

[0037] The data acquisition module is used for:

[0038] Obtain historical task data of the target project at each stage in its entire life cycle, and extract the task decomposition structure from the historical task data at each stage.

[0039] According to the task decomposition structure, the tasks of the corresponding stage are divided into a number of task subsets, and the timestamp and completion status of each task subset are obtained.

[0040] Furthermore, the deviation calculation module is used to:

[0041] Obtain standardized indicator data for each stage from a pre-built standardized indicator database.

[0042] The stage task index data and the standardized index data are compared and analyzed item by item to obtain the deviation value of each stage task index data. The deviation value D is:

[0043] D=(RA) / R

[0044] Among them, R is the standardized indicator data, and A is the stage task indicator data.

[0045] Furthermore, the priority sorting module is used to:

[0046] The total deviation value of the corresponding stage is calculated based on the deviation values corresponding to each task subset in each stage.

[0047] The total deviation values of each stage are sorted to obtain a priority sequence for short-term deviation correction of the target project at each stage.

[0048] Furthermore, the vector calculation module is used to:

[0049] According to the priority sequence, the real-time progress data of each stage corresponding to the priority is sequentially extracted from the project monitoring system.

[0050] A time series analysis method is used to perform trend analysis and fluctuation analysis on the real-time progress data to obtain key characteristic parameters of each stage.

[0051] Feature vectors are extracted from the key feature parameters to obtain monitoring vector groups for each stage.

[0052] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0053] By acquiring historical task data from each stage of the project lifecycle and extracting progress data for each stage from the project monitoring system in real time, we can dynamically track project progress throughout its lifecycle. By using time series analysis to calculate monitoring vector groups for each stage and prioritizing short-term deviation corrections based on deviation values, we can promptly identify deviations in the project progress and quickly implement targeted corrective measures. Using a phased scoring model combined with a dynamic weight adjustment algorithm to calculate progress scores for each stage makes each stage's assessment more realistic, helping project managers to promptly adjust project plans and resource allocation to ensure effective project progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flowchart of a project progress evaluation method according to one embodiment of the present invention;

[0055] Figure 2 This is a structural block diagram of a project progress evaluation system in one embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0057] In the description of this application, the terms "first," "second," "third," etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first," "second," "third," etc. may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0058] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the two components. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0059] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meanings as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. For those skilled in the art, the specific meanings of the above terms in this application can be understood by those skilled in the art in specific circumstances.

[0060] An embodiment of the present invention provides a project progress evaluation method. For details, see Figure 1 , Figure 1 The figure shows a flowchart of the steps of a project progress evaluation method in one embodiment of the present invention.

[0061] Traditional project progress assessment methods mainly rely on an overall review after the project is completed. This method has obvious limitations: for example, there is a lack of real-time monitoring, static evaluation, and post-event remediation. The real-time progress of the project cannot be fed back in time, resulting in a backlog of problems and difficulty in discovering and correcting deviations at an early stage.

[0062] Modern projects are usually divided into multiple stages, each with its own unique tasks and goals. Traditional single evaluation methods are difficult to adapt to such multi-stage management needs. In order to improve the efficiency and success rate of project management, a dynamic evaluation method that can run through the entire life cycle of the project is needed.

[0063] Step S11: Obtain historical task data of each stage of the target project in its entire life cycle, and extract stage task indicator data of each stage from each historical task data.

[0064] Historical task data throughout a project's lifecycle records the entire process from project initiation to completion. By acquiring this data, you can gain a comprehensive understanding of the project's execution at each stage, providing a foundation for subsequent progress assessments.

[0065] Each stage in a project typically includes multiple task subsets, which are the basic units of project execution. Therefore, this embodiment decomposes the tasks of each stage into several task subsets. The specific process is as follows:

[0066] Obtain the historical task data of the target project at each stage throughout its life cycle, and extract the task decomposition structure from the historical task data at each stage. The task decomposition structure can decompose the project into multiple manageable task subsets. By extracting the task decomposition structure, you can clearly understand the specific task composition of the project at each stage.

[0067] The tasks of each stage are divided into several task subsets through the extracted task decomposition structure of each stage, and the timestamp, completion status, previous and next nodes and other information of each task subset are obtained through the task decomposition structure.

[0068] By further dividing tasks into task subsets, the execution status of each task can be monitored more carefully. The timestamp and completion status of the task subset are key data for evaluating task progress. By obtaining this data, the completion status of tasks in each stage and the specific node progress distribution can be obtained more accurately.

[0069] Step S12: Compare and analyze the stage task indicator data with the pre-established standardized indicator data to obtain the deviation value of the stage task indicator data.

[0070] Standardized indicator data is an important benchmark for evaluating project progress. By obtaining standardized indicator data for each stage from a pre-built standardized indicator database, a unified and objective reference standard can be provided for project progress evaluation.

[0071] Obtain the standardized indicator data of each stage from the pre-built standardized indicator database, compare and analyze the stage task indicator data with the standardized indicator data item by item, and obtain the deviation value of the task indicator data of each stage. The deviation value D is:

[0072] D=(RA) / R

[0073] Among them, R is the standardized indicator data, and A is the stage task indicator data.

[0074] By using the historical task data of the target project and the standardized indicator data to calculate the deviation value, we can obtain the historical progress of each stage of the target project as reflected in the historical completion records, helping project managers understand the nodes in the historical operation of the project that are prone to deviation from the standard indicators, so as to better specify the supervision strategy.

[0075] Step S13: Calculate the priority sequence of short-term deviation correction for the target project at each stage based on the deviation value.

[0076] The tasks of each stage are composed of several task subsets, and multiple task subsets together constitute the projects of each stage. The deviation value of each task subset reflects the gap between the task subset and the standardized indicators. By calculating the total deviation value of all task subsets in each stage, the overall deviation situation of the stage can be comprehensively evaluated.

[0077] By calculating the total deviation value, we can identify stages with large deviations. These stages may be bottlenecks or key points of delay in project progress. The total deviation value can be used to identify and handle these stages in a timely manner, and can also help project managers gain an in-depth understanding of the causes of project delays.

[0078] When the project progress deviates from the standard progress, it is necessary to make short-term deviation corrections for the stage where the deviation occurs. However, in the actual project management process, due to limited project management resources, deviations in all stages cannot be handled at the same time. Therefore, it is necessary to sort the total deviation values of each stage to obtain the priority sequence for short-term deviation correction of the target project in each stage.

[0079] By sorting the total deviation values of each stage, we can determine which stages have the most serious deviations and need to be addressed first, which helps to allocate resources reasonably and ensure that key issues are resolved in a timely manner.

[0080] Step S14: extracting the real-time progress data of each stage from the project monitoring system according to the priority sequence, and calculating the real-time progress data through time series analysis to obtain the monitoring vector group of each stage.

[0081] Since the extraction of real-time progress data has high requirements for data real-time in actual operations, the progress data of each stage have real-time dynamic influences on each other, and the order of data extraction in each stage has a great influence on the accuracy of the data. Therefore, it is necessary to give priority to extracting the data of the stage with the largest deviation and the most need for short-term deviation correction. According to the priority sequence, the real-time progress data of each stage of corresponding priority is extracted from the project monitoring system in turn.

[0082] A time series analysis method is used to perform trend analysis and fluctuation analysis on the real-time progress data to obtain key characteristic parameters of each stage. The time series analysis method can help identify long-term trends and short-term fluctuations in the data, wherein the key characteristic parameters include information such as the rate of change and the amplitude of fluctuation.

[0083] Key characteristic parameters may contain a large amount of information. By extracting feature vectors, this information can be condensed into a set of key features, simplifying the data structure and facilitating subsequent analysis and processing. Feature vectors are extracted from these key characteristic parameters to obtain monitoring vector groups for each stage. Monitoring vector groups provide a standardized format for data analysis, allowing direct comparison and analysis of progress data from different stages.

[0084] Step S15: Calculate the first progress score of each stage using the staged scoring model according to each monitoring vector group, and modify each first progress score using the dynamic weight adjustment algorithm to obtain a second progress score.

[0085] In actual project management, the progress timeliness requirements for each stage are different, and different stages need to be scored according to their own standards. Although the progress difference in some stages is large, the tolerance value for progress deviation in this stage is high. Although the progress deviation in some stages is already very small, due to the particularity of the stage, further progress control is still required. Therefore, each stage needs to be scored in stages.

[0086] Specifically, the phased scoring model is a method used to evaluate project progress. It divides the entire project life cycle into multiple stages and sets specific scoring criteria and weights for each stage. Each stage of the project can be evaluated independently, thereby gaining a more comprehensive and detailed understanding of the overall progress of the project.

[0087] The staged scoring model is used to score each stage according to the monitoring vector group, and a first progress score reflecting the score of each stage is obtained.

[0088] Preferably, after obtaining the first progress score, this embodiment readjusts the weights of each stage according to the historical situation of the target project using the deviation values corresponding to the task indicator data of each stage, and corrects the first progress score based on the readjustment result to obtain the second progress score.

[0089] Step S16: Evaluate the project progress of the target project according to each second progress score.

[0090] The second progress score includes the scoring data of each stage of the target project and the total score data of the project. The current status of the project can be evaluated based on the second progress score, so that the project can be supervised and managed based on the evaluation results, and the lagging parts of the project can be checked.

[0091] The project progress evaluation method of the present invention can dynamically track the project progress throughout the entire life cycle by obtaining historical task data from each stage of the project and extracting the progress data of each stage from the project monitoring system in real time. By calculating the monitoring vector group of each stage with the help of time series analysis and determining the priority sequence for correcting short-term deviations based on the deviation value, deviations in the project progress can be discovered in a timely manner and targeted measures can be taken quickly to correct them. The use of a staged scoring model combined with a dynamic weight adjustment algorithm to calculate the progress score of each stage makes the evaluation of each stage more realistic, helping project managers to adjust project plans and resource allocation in a timely manner to ensure the effective advancement of the project.

[0092] The embodiment of the present invention further provides a project progress evaluation method system for executing the project progress evaluation method as described above. Figure 2 This is a structural block diagram of a project progress evaluation method system according to an embodiment of the present invention, wherein the system includes:

[0093] The data acquisition module is used to obtain the historical task data of the target project at each stage in the entire life cycle, and extract the stage task indicator data of each stage from each of the historical task data.

[0094] The deviation calculation module is used to compare and analyze the stage task indicator data with pre-established standardized indicator data to obtain the deviation value of each stage task indicator data.

[0095] A priority sorting module is used to calculate the priority sequence of short-term deviation correction of the target project at each stage based on the deviation value.

[0096] The vector calculation module is used to extract the real-time progress data of each stage from the project monitoring system according to the priority sequence, and calculate the real-time progress data through time series analysis to obtain the monitoring vector group of each stage.

[0097] The progress scoring module is configured to calculate a first progress score for each stage using a stage scoring model according to each monitoring vector group, and to modify each first progress score using a dynamic weight adjustment algorithm to obtain a second progress score.

[0098] A progress evaluation module is used to evaluate the project progress of the target project according to each second progress score.

[0099] The stage task indicator data includes several task subsets of the corresponding stage, and the timestamp and completion status of each task subset.

[0100] The data acquisition module is used for:

[0101] Obtain historical task data of the target project at each stage in its entire life cycle, and extract the task decomposition structure from the historical task data at each stage.

[0102] According to the task decomposition structure, the tasks of the corresponding stage are divided into a number of task subsets, and the timestamp and completion status of each task subset are obtained.

[0103] The deviation calculation module is used to:

[0104] Obtain standardized indicator data for each stage from a pre-built standardized indicator database.

[0105] The stage task index data and the standardized index data are compared and analyzed item by item to obtain the deviation value of each stage task index data, and the deviation value is D:

[0106] D=(RA) / R

[0107] Among them, R is the standardized indicator data, and A is the stage task indicator data.

[0108] The prioritization module is used to:

[0109] The total deviation value of the corresponding stage is calculated based on the deviation values corresponding to each task subset in each stage.

[0110] The total deviation values of each stage are sorted to obtain a priority sequence for short-term deviation correction of the target project at each stage.

[0111] The vector calculation module is used for:

[0112] According to the priority sequence, the real-time progress data of each stage corresponding to the priority is sequentially extracted from the project monitoring system.

[0113] A time series analysis method is used to perform trend analysis and fluctuation analysis on the real-time progress data to obtain key characteristic parameters of each stage.

[0114] Feature vectors are extracted from the key feature parameters to obtain monitoring vector groups for each stage.

[0115] The technical features and technical effects of the system proposed in the embodiment of the present invention are the same as those of the method proposed in the embodiment of the present invention and are not described in detail here. Each module in the above system can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software so that the processor can call and execute the operations corresponding to the above modules.

[0116] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A project progress evaluation method, characterized in that: include: Obtain historical task data of each stage of the target project throughout its life cycle, and extract stage task indicator data of each stage from each of the historical task data; Comparing and analyzing the stage task indicator data with pre-established standardized indicator data to obtain deviation values of the stage task indicator data; Calculate the priority sequence of short-term deviation correction of the target project at each stage based on the deviation value; Extracting real-time progress data of each stage from the project monitoring system according to the priority sequence, and calculating the real-time progress data through time series analysis to obtain a monitoring vector group for each stage; Calculating a first progress score for each stage using a staged scoring model based on each monitoring vector group, and correcting each first progress score using a dynamic weight adjustment algorithm to obtain a second progress score; The project progress of the target project is evaluated according to each of the second progress scores.

2. The project progress evaluation method according to claim 1, wherein: The stage task indicator data includes several task subsets of the corresponding stage, and the timestamp and completion status of each task subset; The step of obtaining historical task data of each stage of the target project in its entire life cycle and extracting stage task indicator data of each stage from each of the historical task data includes: Obtain historical task data of the target project at each stage in its entire life cycle, and extract the task decomposition structure from the historical task data at each stage; According to the task decomposition structure, the tasks of the corresponding stage are divided into a number of task subsets, and the timestamp and completion status of each task subset are obtained.

3. The project progress evaluation method according to claim 1, wherein: The comparative analysis of the stage task indicator data with pre-established standardized indicator data to obtain the deviation value of each stage task indicator data includes: Obtain standardized indicator data for each stage from a pre-built standardized indicator database; The stage task index data and the standardized index data are compared and analyzed item by item to obtain the deviation value of each stage task index data. The deviation value D is: D=(RA) / R Among them, R is the standardized indicator data, and A is the stage task indicator data.

4. The project progress evaluation method according to claim 2, wherein: The priority sequence of short-term deviation correction of the target project at each stage is calculated based on the deviation value, including: Calculating the total deviation value of the corresponding stage according to the deviation values corresponding to each task subset in each stage; The total deviation values of each stage are sorted to obtain a priority sequence for short-term deviation correction of the target project at each stage.

5. The project progress evaluation method according to claim 1, wherein: The method of extracting the real-time progress data of each stage from the project monitoring system according to the priority sequence and calculating the monitoring vector group of each stage by time series analysis on the real-time progress data includes: According to the priority sequence, the real-time progress data of each stage corresponding to the priority is sequentially extracted from the project monitoring system; Using time series analysis to perform trend analysis and fluctuation analysis on the real-time progress data, and obtain key characteristic parameters of each stage; Feature vectors are extracted from the key feature parameters to obtain monitoring vector groups for each stage.

6. A project progress evaluation system, characterized in that: include: A data acquisition module is used to obtain historical task data of each stage of the target project in the entire life cycle, and extract the stage task indicator data of each stage from each of the historical task data; a deviation calculation module, configured to compare and analyze the stage task indicator data with pre-established standardized indicator data to obtain a deviation value of each stage task indicator data; A priority sorting module, configured to calculate a priority sequence for short-term deviation correction of the target project at each stage based on the deviation value; a vector calculation module, configured to extract the real-time progress data of each stage from the project monitoring system according to the priority sequence, and calculate the real-time progress data through time series analysis to obtain a monitoring vector group for each stage; a progress scoring module, configured to calculate a first progress score for each stage using a staged scoring model based on each monitoring vector group, and to modify each first progress score using a dynamic weight adjustment algorithm to obtain a second progress score; A progress evaluation module is used to evaluate the project progress of the target project according to each second progress score.

7. The project progress evaluation system according to claim 6, wherein: The stage task indicator data includes several task subsets of the corresponding stage, and the timestamp and completion status of each task subset; The data acquisition module is used for: Obtain historical task data of the target project at each stage in its entire life cycle, and extract the task decomposition structure from the historical task data at each stage; According to the task decomposition structure, the tasks of the corresponding stage are divided into a number of task subsets, and the timestamp and completion status of each task subset are obtained.

8. The project progress evaluation system according to claim 6, wherein: The deviation calculation module is used to: Obtain standardized indicator data for each stage from a pre-built standardized indicator database; The stage task index data and the standardized index data are compared and analyzed item by item to obtain the deviation value of each stage task index data, and the deviation value is D: D=(RA) / R Among them, R is the standardized indicator data, and A is the stage task indicator data.

9. The project progress evaluation system according to claim 7, wherein: The prioritization module is used to: Calculating the total deviation value of the corresponding stage according to the deviation values corresponding to each task subset in each stage; The total deviation values of each stage are sorted to obtain a priority sequence for short-term deviation correction of the target project at each stage.

10. The project progress evaluation system according to claim 6, wherein: The vector calculation module is used for: According to the priority sequence, the real-time progress data of each stage corresponding to the priority is sequentially extracted from the project monitoring system; Using time series analysis to perform trend analysis and fluctuation analysis on the real-time progress data, and obtain key characteristic parameters of each stage; Feature vectors are extracted from the key feature parameters to obtain monitoring vector groups for each stage.

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