Engineering supervision system and method based on green engineering construction

Abstract

The invention discloses an engineering supervision system and method based on green engineering construction, relates to the technical field of engineering project management, and is used for solving the problems that process data cannot be analyzed in real time and key projects needing to be emphatically supervised are difficult to effectively screen out. The risk of each project is comprehensively assessed by acquiring the number of engineering projects, acquiring processing time, calculating a processing time ratio, acquiring the number of participants, recording conference frequency and the like, and the project completion degree is calculated by counting the amount of completed events. And judging whether a multi-project parallel condition exists in combination with the project risk and the completion degree, and if so, entering a project supervision optimization process. And in the optimization process, key supervision engineering projects are screened out in combination with project interaction deadlines and processing time change data, so that the engineering supervision efficiency and management accuracy under the multi-project parallel condition are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering project management, and more specifically, to an engineering supervision system and method based on green engineering construction. Background Art

[0002] In large-scale enterprise or government engineering projects, multiple concurrent projects often involve extensive resource allocation, progress coordination, and personnel scheduling. Traditional project management methods rely on static schedules, manual judgment, and manual reporting, lacking dynamic, quantitative, and intelligent mechanisms for concurrent project risk monitoring and completion assessment.

[0003] The existing technology has the following deficiencies:

[0004] At present, especially when multiple projects are being promoted in parallel, if the process data such as the processing time allocation, personnel input status and meeting frequency of each project cannot be analyzed in real time, it is easy to lead to management blind spots, resource conflicts, construction delays and even quality risks. It is difficult to effectively screen out key projects that require key supervision. Therefore, an engineering supervision system and method based on green engineering construction is proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an engineering supervision system and method based on green engineering construction, which solves the problems raised in the above-mentioned background technology by applying multi-source data fusion modeling, project risk intelligent assessment and dynamic completion determination algorithm.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a system and method for project supervision based on green engineering construction, comprising the following steps:

[0008] Step S1: Obtain the number of currently ongoing projects, call the processing time of each project to calculate the processing time ratio, collect the number of participants in each project and the number of recorded meetings, and generate the recorded meeting frequency based on the number of recorded meetings;

[0009] Step S2: Evaluate the project risk of each project based on the processing time ratio, the number of participants, and the frequency of recorded meetings, count the number of completed events for each project, and calculate the project completion degree of each project based on the number of completed events;

[0010] Step S3: judging whether the current project appears the multi-project parallel situation according to the project completion degree of each project and the project risk of the corresponding project, and selecting whether to enter the engineering supervision optimization according to the judgment result;

[0011] Step S4: when entering the engineering supervision optimization, calling the interaction deadline of each project to calculate the reserved time, collecting the processing time change data of each project, and screening the key supervision project in combination with the reserved time.

[0012] In a preferred embodiment, in step S1, the processing time of each project and the standard processing time are called, and the ratio of the processing time to the standard processing time is taken as the processing time ratio of each project;

[0013] The standard processing time is the project interaction time recorded by the project engineering last time, and the processing time of the project engineering is the time that has been processed by the project engineering.

[0014] In a preferred embodiment, in step S1, when the project engineering starts processing, the project meeting during the processing period is recorded to obtain the recorded meeting times, and the recorded meeting times of each project engineering are divided by the maximum value of the recorded meeting times of all project engineering currently conducted to generate the recorded meeting frequency of the corresponding project engineering.

[0015] In a preferred embodiment, in step S2, the processing time ratio, the number of participants and the recorded meeting frequency are combined to evaluate the project risk of each project engineering by using the MAD algorithm, and the specific steps are as follows:

[0016] Merging data sets: the processing time ratio, the number of participants and the recorded meeting frequency of each project engineering are respectively merged into the processing time data set, the number of participants data set and the meeting frequency data set;

[0017] Calculating the median: the median of each data set is calculated;

[0018] Calculating the absolute deviation: the difference between the data in each data set and the median of the corresponding data set is calculated to obtain a plurality of absolute deviations;

[0019] Calculating the median absolute deviation: the median absolute deviation MAD is obtained by taking the median of the absolute deviations of all data in the data set: MAD = Median(|S i -Median(s)|), wherein S i is the i-th data in each data set, and Median(s) is the median of each data set;

[0020] Calculate the risk assessment index: First, calculate the ratio of the processing time ratio, the number of participants, and the recorded meeting frequency of the same engineering project in each data set to the median absolute deviation calculated for each corresponding data set, and then sum the ratios to obtain the risk assessment index of each engineering project.

[0021] In a preferred embodiment, in step S2, the number of events completed in each engineering project is counted as the completed event volume of the corresponding engineering project, and the ratio of the completed event volume of each engineering project to the total event volume of the corresponding engineering project is used as the project completion degree of the corresponding engineering project.

[0022] In a preferred embodiment, in step S3, the completion degree of each project and the risk assessment index of each project are standardized and substituted into the ideal solution closeness ranking model to obtain the closeness score of the current project;

[0023] The ideal solution proximity ranking model constructs a standardized decision matrix for each project with two standardized results. The specific implementation steps are as follows:

[0024] A1: Construct ideal solutions and negative ideal solutions;

[0025] A2: Calculate the Euclidean distance between each item and the ideal solution and the negative ideal solution respectively;

[0026] A3: Calculate the closeness score for each item;

[0027] The closeness score of each project is weighted averaged to obtain the global multi-project parallel score.

[0028] In a preferred embodiment, in step S3, the global multi-project parallel score is compared with a preset parallel threshold. If the global multi-project parallel score is greater than or equal to the parallel threshold, the project supervision optimization is selected. If the global multi-project parallel score is less than the parallel threshold, the project resource allocation and risk control are in normal state.

[0029] In a preferred embodiment, in step S4, when entering the project supervision optimization, the interaction deadline of each project and the processing time change data of each project are called to obtain the reserved time and the time reduction frequency;

[0030] Obtain the reserved time by obtaining the project deadline of each parallel project and calculating the difference between it and the current time;

[0031] The number of time changes of the project at the current time is obtained through the project management log, and then the ratio of the current project interaction period to the interaction period preset when the project was launched is calculated, and then weighted with the number of time changes to obtain the time reduction frequency.

[0032] In a preferred embodiment, in step S4, the reserved time and the time shortening frequency are defined as input variables, and are divided into different fuzzy sets respectively;

[0033] The key supervision results of each engineering project are defined as output variables and divided into fuzzy sets;

[0034] Formulate fuzzy rules to describe the impact of reserved time and time reduction frequency on the key supervision results of each engineering project;

[0035] Perform fuzzy reasoning based on fuzzy rules to determine the key supervision results of each engineering project.

[0036] The engineering supervision system based on green engineering construction includes project data collection module, risk assessment and completion statistics module, multi-project parallel judgment module and engineering supervision optimization module;

[0037] The project data collection module is used to retrieve the processing time, number of participants, and number of meetings for each project, and transmit them to the risk assessment and completion statistics modules;

[0038] The risk assessment and completion statistics module generates a processing time ratio based on the processing time, generates a recorded meeting frequency based on the number of recorded meetings, and assesses the project risk based on the number of participants. The module then calculates the number of completed events for each project and sends the risk assessment results to the multi-project parallel judgment module.

[0039] The multi-project parallel judgment module receives the completion event volume and risk assessment results of each project to determine whether multi-project parallelism occurs. If multi-project parallelism occurs, the collected signal is set to be transmitted to the project supervision optimization module;

[0040] After receiving the collection signal, the engineering supervision optimization module calls the interaction deadline of each engineering project and collects the processing time change data of each engineering project. It comprehensively selects key supervision engineering projects from each engineering project based on the interaction deadline and processing time change data of each engineering project.

[0041] The technical effects and advantages of the present invention are as follows:

[0042] 1. The present invention obtains the number of engineering projects, collects the processing time of each engineering project and calculates the processing time ratio, collects the number of participants in each engineering project, records the number of meetings for each engineering project and generates a recorded meeting frequency, comprehensively evaluates the project risk of each engineering project based on the processing time ratio, the number of participants and the recorded meeting frequency, counts the number of completed events of each engineering project and calculates the project completion degree of each engineering project, and judges whether there are multiple projects running in parallel in the current project in combination with the project risk assessment results of each engineering project. According to the judgment result, it is selected whether to enter the engineering supervision optimization. When entering the engineering supervision optimization, the interaction deadline of each engineering project is called and the processing event change data is collected, and the key supervision engineering projects are screened out in each engineering project, thereby greatly improving the supervision efficiency of each engineering project when multiple projects are running in parallel. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention is a method flow chart of the engineering supervision method based on green engineering construction.

[0044] Figure 2 It is a module diagram of the engineering supervision system based on green engineering construction of the present invention. DETAILED DESCRIPTION

[0045] 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 the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0046] Example 1, a project supervision method based on green engineering construction, such as Figure 1 As shown, the following steps are included:

[0047] Step S1: Obtain the number of currently ongoing projects, call the processing time of each project to calculate the processing time ratio, collect the number of participants in each project and the number of recorded meetings, and generate the recorded meeting frequency based on the number of recorded meetings;

[0048] Step S2: Evaluate the project risk of each project based on the processing time ratio, the number of participants, and the frequency of recorded meetings, count the number of completed events for each project, and calculate the project completion degree of each project based on the number of completed events;

[0049] Step S3: Determine whether the current project has multiple projects running in parallel based on the project completion rate and the project risk of each project, and decide whether to enter the project supervision optimization process based on the determination result.

[0050] Step S4: When entering the project supervision optimization, the interactive deadline of each project is called to calculate the reserved time, the processing time change data of each project is collected, and the key supervision projects are screened out based on the reserved time.

[0051] The specific implementation is as follows:

[0052] In step S1, the number of currently ongoing projects, the total number of events within the project, and the number of completed events are obtained by accessing the resource management system;

[0053] The resource management system stores the total number of engineering projects and the number of currently ongoing engineering projects. Each engineering project records multiple completed events and pending events. The total number of events in the engineering project is the sum of the number of completed events and pending events.

[0054] Call the processing time and standard processing time of each project. The standard processing time is the project interaction time recorded most recently. The processing time of the project is the time when the project has been processed. The ratio of the processing time to the standard processing time is used as the processing time ratio of each project.

[0055] The greater the processing time ratio of the project, the more urgent the project, and the greater the project risk, the more focused supervision is needed.

[0056] When a project begins processing, the project participants and project meetings during the processing period will be recorded. The number of participants and the number of recorded meetings for each project will be collected. The number of recorded meetings for each project will be divided by the maximum number of recorded meetings for all currently ongoing projects to generate the recorded meeting frequency for the corresponding project.

[0057] The more people involved in a project or the more frequent the recorded meetings, the more important the project is and the more focused supervision is needed.

[0058] It should be noted that the resource management system is a system for planning, allocating and managing resources within engineering projects, which includes the number of currently ongoing engineering projects, the total number of events within the engineering projects, the number of completed events, and basic information of each project, such as project interaction time, the number of participants, and the number of recorded meetings.

[0059] In step S2, the project risk of each project is assessed using the MAD algorithm based on the processing time ratio, the number of participants, and the frequency of recorded meetings. The specific steps are as follows:

[0060] Merge datasets: Merge the processing time ratio, number of participants, and recorded meeting frequency of each project into a processing time dataset, a participant number dataset, and a meeting frequency dataset respectively;

[0061] Calculate the median: Calculate the median of each data set;

[0062] Calculate absolute deviation: Calculate the difference between the data in each data set and the median of the corresponding data set to obtain multiple absolute differences;

[0063] Calculate the median absolute deviation: take the median of the absolute difference of all data in the data set to get the median absolute deviation MAD: MAD = Median(|S i -Median(s)|), where S i is the i-th data in each data set, and Median(s) is the median of each data set.

[0064] Calculate the risk assessment index: First, calculate the ratio of the processing time ratio, the number of participants, and the recorded meeting frequency of the same engineering project in each data set to the median absolute deviation calculated for each corresponding data set, and then sum the ratios to obtain the risk assessment index of each engineering project.

[0065] The number of events processed and completed for each project is counted as the completed event volume of the corresponding project, and the ratio of the completed event volume of each project to the total event volume of the corresponding project is taken as the project completion degree of the corresponding project.

[0066] The lower the project completion rate, the longer the processing time, the more likely other projects will start during the processing period, and the more likely it is that multiple projects will be carried out in parallel. The greater the risk assessment index of the engineering project, the more likely it is that the plan will be revised after changes, and the more likely it is that multiple projects will be carried out in parallel.

[0067] It should be noted that the MAD algorithm is a statistical method for detecting outliers. In this example, it is used to reduce data anomalies for comprehensive analysis of engineering risks. There is no unique method for calculating the risk assessment index of engineering projects. In this example, only the MAD algorithm is used as an example, and the specific calculation method is not limited.

[0068] In step S3, the completion degree of each project and the risk assessment index of each project are standardized and substituted into the ideal solution closeness ranking model to obtain the closeness score of the current project;

[0069] It should be noted that the standardization methods include but are not limited to standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application methods of standardization are not described in detail here.

[0070] Further, the ideal solution closeness ranking model is the TOPSIS method, which can reflect the multi-index collaborative evaluation capability without relying on the weight set by people, and has certain nonlinear discrimination ability to adapt to the heterogeneity of multi-dimensional indicators, which will not be repeated here.

[0071] Among them, after the risk assessment index of each project is standardized and processed, it is processed in reverse mapping, and converted into a "the bigger the better" type to adapt to the closeness score calculation;

[0072] Further, the higher the completion degree of each project, the higher the current project single project closeness score, the higher the risk assessment index of each project, and the lower the current project single project closeness score. It can be understood that the current project single project closeness score is integrated to determine the global multi-project parallel score.

[0073] Specifically, there are m projects, and each project corresponds to two standardized indexes X i,1 and X i,2 .

[0074] Then, the standardized decision matrix is constructed:

[0075]

[0076] The specific implementation steps are as follows:

[0077] A1: Construct ideal solution and negative ideal solution;

[0078] Among them, the ideal solution is X + =(max X i,1 ,max X i,2 );

[0079] The negative ideal solution is X - =(min X i,1 ,min X i,2 );

[0080] A2: Calculate the Euclidean distance of each project and ideal solution and negative ideal solution respectively;

[0081] Specifically, the Euclidean distances of ideal solution and negative ideal solution are respectively:

[0082]

[0083] A3: Calculate the closeness score of each project;

[0084]

[0085] In the formula, R i is the current project single project closeness score;

[0086] Further, R i ∈[0,1], the closer the current engineering single project closeness score is to 1, the higher the project completion degree is, the lower the project risk is, and the stable the comprehensive index performance is;

[0087] The closeness scores of each project are weighted and averaged to obtain a global multi-project parallel score; wherein the weighted average calculation is common knowledge of the experimenters, and the specific calculation formula is: This will not be elaborated here;

[0088] The global multi-project parallel score is compared with the preset parallel threshold value, if the global multi-project parallel score is greater than or equal to the parallel threshold value, it means that there are currently multiple projects in a low completion degree and risk not removed concurrent promotion state, and the engineering supervision optimization is selected, if the global multi-project parallel score is less than the parallel threshold value, it means that the current project promotion rhythm is reasonable, and there is no typical multi-project parallel conflict, and the engineering resource allocation and risk control are in a normal state;

[0089] It should be noted that the parallel threshold value is obtained by the experimenters according to the multi-project historical progress data analysis results and the project risk trigger threshold value model and the engineering intervention tolerance standard, which will not be elaborated here;

[0090] Among them, the engineering supervision optimization refers to a comprehensive optimization strategy based on intelligent scheduling, progress control and risk intervention triggered in the case of identifying low completion degree and high risk concurrent situation in multi-project parallel promotion process, and the specific implementation strategy mode is not limited, which will not be elaborated here;

[0091] In step S4, when entering the engineering supervision optimization, the interaction deadline of each engineering project and the processing time change data of each engineering project are called to obtain the reserved time and the time shortening frequency;

[0092] Among them, the reserved time is obtained by obtaining the engineering deadline of each parallel project, and the difference between the current time is calculated to obtain the reserved time;

[0093] It should be noted that the engineering deadline of each parallel project is obtained by the experimenters according to the historical project progress data analysis and the historical similar project experience analysis, which will not be elaborated here;

[0094] The acquisition logic of time shortening frequency is to obtain the number of time changes of the project at the current time through the project management log, and then the interaction deadline of the current project is compared with the interaction deadline preset when the project starts, and the weighted calculation is carried out with the number of time changes to obtain the time shortening frequency;

[0095] Among them, the project management log includes meeting decision records, change approval documents, progress adjustment reports and the like, which will not be elaborated here;

[0096] Use fuzzy logic to determine the key supervision results of each project based on the reserved time and time reduction frequency;

[0097] For example, "long" and "short" for reservation time;

[0098] "Fast" and "slow" shorten the frequency of time;

[0099] Formulate a set of fuzzy rules to describe the impact of different input variables on the output variable. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0100] Mark the reserved time as T, the time reduction frequency as P, and the key supervision results of each project as C_results;

[0101] Then we can define:

[0102] Rule 1: If the reserved time is "short" and the time reduction frequency is "fast", then (the key supervision result of each project is "high");

[0103] Rule 2: If the reserved time is "long" and the time reduction frequency is "slow", then (the key supervision result of each project is "low"); ...

[0105] Carry out fuzzy reasoning based on fuzzy rules to determine the key supervision results of each engineering project;

[0106] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although this embodiment uses two fuzzy sets as an example, the reserved time and the time reduction frequency can actually be divided into two or more sets to facilitate better precise adjustment based on different similarities.

[0107] Furthermore, for the judgment of the reservation time and the time reduction frequency, thresholds can be set according to actual conditions. For example, when the reservation time exceeds 61% of the preset threshold, it is marked as "long", and when the time reduction frequency exceeds 70% of the preset threshold, it is marked as "fast", etc., which will not be elaborated here.

[0108] It should be noted that the preset thresholds for reserved time and time reduction frequency were obtained by our experimenters based on the statistical analysis of time behavior during project execution and the tolerance model for dynamic allocation of engineering resources. They will not be elaborated here.

[0109] The key supervision results of each engineering project marked as "high" will be marked as key supervision engineering projects.

[0110] Example 2, a project supervision system based on green engineering construction, such as Figure 2 As shown, it includes project data acquisition module, risk assessment and completion statistics module, multi-project parallel judgment module and engineering supervision optimization module, and each module is connected with electrical signals;

[0111] The functions of each module are as follows:

[0112] The project data collection module is used to retrieve the processing time, number of participants, and number of meetings for each project, and transmit them to the risk assessment and completion statistics modules;

[0113] The risk assessment and completion statistics module generates a processing time ratio based on the processing time, generates a recorded meeting frequency based on the number of recorded meetings, and assesses the project risk based on the number of participants. The module then calculates the number of completed events for each project and sends the risk assessment results to the multi-project parallel judgment module.

[0114] The multi-project parallel judgment module receives the completion event volume and risk assessment results of each project to determine whether multi-project parallelism occurs. If multi-project parallelism occurs, the collected signal is set to be transmitted to the project supervision optimization module;

[0115] After receiving the collection signal, the engineering supervision optimization module calls the interaction deadline of each engineering project and collects the processing time change data of each engineering project. It comprehensively selects key supervision engineering projects from each engineering project based on the interaction deadline and processing time change data of each engineering project.

[0116] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0117] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0118] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0119] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0120] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0121] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0122] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0124] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0125] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0126] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0127] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. The engineering supervision method based on green engineering construction is characterized by: The following steps are included: Step S1: Obtain the number of currently ongoing projects, call the processing time of each project to calculate the processing time ratio, collect the number of participants in each project and the number of recorded meetings, and generate the recorded meeting frequency based on the number of recorded meetings; Step S2: Evaluate the project risk of each project based on the processing time ratio, the number of participants, and the frequency of recorded meetings, count the number of completed events for each project, and calculate the project completion degree of each project based on the number of completed events; Step S3: Determine whether the current project has multiple projects running in parallel based on the project completion rate and the project risk of each project, and decide whether to enter the project supervision optimization process based on the determination result. Step S4: When entering the project supervision optimization, the interactive deadline of each project is called to calculate the reserved time, the processing time change data of each project is collected, and the key supervision projects are screened out based on the reserved time.

2. The engineering supervision method based on green engineering construction according to claim 1 is characterized in that: In step S1, the processing time and standard processing time of each project are called, and the ratio of the processing time to the standard processing time is used as the processing time ratio of each project; The standard processing time is the time of the most recent recorded project interaction for the project project, and the processing time for the project project is the time when the project project has been processed.

3. The engineering supervision method based on green engineering construction according to claim 1 is characterized in that: In step S1, when the project starts to be processed, the project meetings during the processing period are recorded to obtain the number of recorded meetings, and the number of recorded meetings of each project is divided by the maximum number of recorded meetings of all currently ongoing projects to generate the recorded meeting frequency of the corresponding project.

4. The engineering supervision method based on green engineering construction according to claim 3 is characterized in that: In step S2, the project risk of each project is assessed using the MAD algorithm based on the processing time ratio, the number of participants, and the frequency of recorded meetings. The specific steps are as follows: Merge datasets: Merge the processing time ratio, number of participants, and recorded meeting frequency of each project into a processing time dataset, a participant number dataset, and a meeting frequency dataset respectively; Calculate the median: Calculate the median of each data set; Calculate absolute deviation: Calculate the difference between the data in each data set and the median of the corresponding data set to obtain multiple absolute differences; Calculate the median absolute deviation: take the median of the absolute difference of all data in the data set to get the median absolute deviation MAD: MAD = Median(|S i -Median(s)|), where S i is the i-th data in each data set, and Median(s) is the median of each data set; Calculate the risk assessment index: First, calculate the ratio of the processing time ratio, the number of participants, and the recorded meeting frequency of the same engineering project in each data set to the median absolute deviation calculated for each corresponding data set, and then sum the ratios to obtain the risk assessment index of each engineering project.

5. The engineering supervision method based on green engineering construction according to claim 1 is characterized in that: In step S2, the number of events processed by each project is counted as the completed event volume of the corresponding project, and the ratio of the completed event volume of each project to the total event volume of the corresponding project is taken as the project completion degree of the corresponding project.

6. The engineering supervision method based on green engineering construction according to claim 5 is characterized in that: In step S3, the completion degree of each project and the risk assessment index of each project are standardized and substituted into the ideal solution closeness ranking model to obtain the closeness score of the current project; The ideal solution proximity ranking model constructs a standardized decision matrix for each project with two standardized results. The specific implementation steps are as follows: A1: Construct ideal solutions and negative ideal solutions; A2: Calculate the Euclidean distance between each item and the ideal solution and the negative ideal solution respectively; A3: Calculate the closeness score for each item; The closeness score of each project is weighted averaged to obtain the global multi-project parallel score.

7. The engineering supervision method based on green engineering construction according to claim 6 is characterized in that: In step S3, the global multi-project parallel score is compared with the preset parallel threshold. If the global multi-project parallel score is greater than or equal to the parallel threshold, the project supervision optimization is selected. If the global multi-project parallel score is less than the parallel threshold, the project resource allocation and risk control are in normal state.

8. The engineering supervision method based on green engineering construction according to claim 7 is characterized in that: In step S4, when entering the project supervision optimization, the interaction deadline of each project and the processing time change data of each project are called to obtain the reserved time and time reduction frequency; Obtain the reserved time by obtaining the project deadline of each parallel project and calculating the difference between it and the current time; The number of time changes of the project at the current time is obtained through the project management log, and then the ratio of the current project interaction period to the interaction period preset when the project was launched is calculated, and then weighted with the number of time changes to obtain the time reduction frequency.

9. The engineering supervision method based on green engineering construction according to claim 8 is characterized in that: In step S4, the reserved time and the time shortening frequency are defined as input variables, and they are divided into different fuzzy sets respectively; The key supervision results of each engineering project are defined as output variables and divided into fuzzy sets; Formulate fuzzy rules to describe the impact of reserved time and time reduction frequency on the key supervision results of each engineering project; Perform fuzzy reasoning based on fuzzy rules to determine the key supervision results of each engineering project.

10. An engineering supervision system based on green engineering construction, used to implement the engineering supervision method based on green engineering construction according to any one of claims 1 to 9, characterized in that: It includes project data collection module, risk assessment and completion statistics module, multi-project parallel judgment module and engineering supervision optimization module; The project data collection module is used to retrieve the processing time, number of participants, and number of meetings for each project, and transmit them to the risk assessment and completion statistics modules; The risk assessment and completion statistics module generates a processing time ratio based on the processing time, generates a recorded meeting frequency based on the number of recorded meetings, and assesses the project risk based on the number of participants. The module then calculates the number of completed events for each project and sends the risk assessment results to the multi-project parallel judgment module. The multi-project parallel judgment module receives the completion event volume and risk assessment results of each project to determine whether multi-project parallelism occurs. If multi-project parallelism occurs, the collected signal is set to be transmitted to the project supervision optimization module; After receiving the collection signal, the engineering supervision optimization module calls the interaction deadline of each engineering project and collects the processing time change data of each engineering project. It comprehensively selects key supervision engineering projects from each engineering project based on the interaction deadline and processing time change data of each engineering project.

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