CN115496362A - Engineering supervision project evaluation system and method based on big data - Google Patents
Engineering supervision project evaluation system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of big data, in particular to a project supervision project evaluation system and a method based on big data, which comprises the following steps: the project supervision system comprises a supervision information acquisition module, a data storage management module, a database, a project analysis module and a project supervision management module, wherein project information needing project supervision and historical supervision information of supervision projects are acquired through the supervision information acquisition module, personnel for supervision projects are sequenced through the data storage management module, the personnel information is stored in the database after sequencing, all received data are stored in the database, the number of supervision personnel needed by different project is analyzed through the project analysis module, the supervision and evaluation are carried out on different project through the distribution personnel of the project supervision management module, and the reliability of supervision results obtained by arranging supervision personnel to participate in the project under different conditions is improved.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a project supervision project evaluation system and method based on big data.
Background
In the building engineering, especially large-scale capital construction engineering, a large amount of different engineering planning data, engineering implementation detection data and the like are needed in different stages before, during and after construction, the data can be ensured to be successfully completed through corresponding supervision work, the engineering supervision refers to the entrustment of a supervision unit with related qualification to a party A, a professional service activity for representing the party A to monitor the engineering construction of the party B in real time according to related regulations, and supervision personnel often need to inspect and evaluate the progress and quality of an engineering project so as to smoothly promote the construction of the building engineering;
however, the existing engineering supervision method has the following disadvantages: firstly, the work efficiency of project supervision is reduced due to improper allocation of the supervision personnel, the real capacity data of the supervision personnel cannot be obtained independently depending on the self qualification of the supervision personnel, the prior art cannot perform big data analysis on the historical assessment supervision project of the supervision personnel to obtain the real capacity data of the supervision personnel, and the reasonability of the allocation result cannot be improved; secondly, when a plurality of tasks of project supervision and project evaluation are entrusted at the same time, the prior art cannot reasonably distribute the number of supervision personnel and specific supervision personnel in each project, cannot further optimize the distribution mode, and cannot improve the reliability of all project supervision results on the whole.
Therefore, a need exists for a big data based project supervision project evaluation system and method to solve the above problems.
Disclosure of Invention
The invention aims to provide a project supervision project evaluation system and method based on big data, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a big data based project administration project assessment system, the system comprising: the system comprises a supervision information acquisition module, a data storage management module, a database, an engineering project analysis module and an engineering supervision management module;
the output end of the supervision information acquisition module is connected with the input ends of the data storage management module and the database, the output end of the data storage management module is connected with the input end of the database, the output end of the database is connected with the input end of the engineering project analysis module, and the output end of the engineering project analysis module is connected with the input end of the engineering supervision management module;
the supervision information acquisition module is used for acquiring project information needing project supervision and personnel historical supervision information of supervision projects, transmitting the supervision information to the data storage management module and transmitting the project information to the database;
the data storage management module is used for sequencing the personnel for supervising the project and storing the personnel information into the database after sequencing;
the database is used for storing all received data;
the engineering project analysis module is used for analyzing the number of supervision personnel required by different engineering projects;
the project supervision management module is used for supervision and evaluation of different project by distribution personnel.
Furthermore, the supervision information acquisition module comprises a project information acquisition unit and a supervision information acquisition unit;
the output end of the project information acquisition unit is connected with the input end of the database;
the project information acquisition unit is used for acquiring project commission time and project engineering quantity information which need to be managed by a project and transmitting the acquired information to the database;
the supervision information acquisition unit is used for acquiring historical supervision data of different personnel and transmitting the acquired data to the data storage management module.
Further, the data storage management module comprises a proctoring level analysis unit and a data storage sorting unit;
the input end of the supervision level analysis unit is connected with the output end of the supervision information acquisition unit, the output end of the supervision level analysis unit is connected with the input end of the data storage and sorting unit, and the output end of the data storage and sorting unit is connected with the input end of the database;
the supervision level analysis unit is used for analyzing engineering supervision level coefficients of different personnel;
the data storage and sorting unit is used for sorting the personnel in the order from large to small according to the engineering supervision level coefficient and storing the sorted personnel information into the database.
Further, the engineering project analysis module comprises a project data calling unit and a quantity analysis unit;
the input end of the project data calling unit is connected with the input end of the database, and the output end of the project data calling unit is connected with the input end of the quantity analysis unit;
the project data calling unit is used for calling project commission time data needing project supervision;
and the quantity analysis unit is used for analyzing the quantity of supervision personnel needed by the corresponding project according to the project quantity information of the project when the projects needing project supervision with the same consignment time exist.
Further, the project supervision management module comprises a personnel distribution management unit and a project evaluation unit;
the input end of the personnel allocation management unit is connected with the output ends of the database and the quantity analysis unit, and the output end of the personnel allocation management unit is connected with the input end of the project evaluation unit;
the personnel allocation management unit is used for allocating the quantity of project supervision personnel required by a project and optimizing an allocation mode;
and the project evaluation unit is used for arranging project supervision personnel corresponding to project distribution according to the optimal distribution mode to supervise the project and submit a project quality evaluation report.
A project supervision project evaluation method based on big data comprises the following steps:
z1: collecting project information needing project supervision and historical supervision information of supervision personnel;
z2: sequencing the personnel for supervising the project, and storing the personnel information according to the sequence;
z3: when project commission time needing project supervision is different, distributing personnel according to an arrangement sequence;
z4: when projects needing project supervision with the same entrusting time exist, the number of personnel needed by the projects is distributed, and the distribution mode is optimized;
z5: and allocating personnel to supervise and evaluate different engineering projects according to the allocation result.
Further, in step Z1: the method comprises the following steps of collecting a project consignment time set which needs project supervision as T = { T1, T2, \8230;, tm }, wherein the project quantity set corresponding to a project is G = { G1, G2, \8230;, gm }, wherein m represents the project quantity entrusted to project supervision, and collecting An employment age set of supervisors as A = { A1, A2, \8230;, an }, wherein n represents the supervisor quantity, and randomly collecting k project supervision data which are previously supervised by the supervisors: collecting random supervision personnel in the past supervision-participating engineering project: the set of delay time duration for proctoring work completion is t = { t1, t2, \8230;, tk }, the set of quality evaluation values of the corresponding proctoring personnel for engineering projects is Q = { Q1, Q2, \8230;, qk }, and the set of actual quality evaluation values after verification is Q = { Q1, Q2, \8230;, qk }.
Further, in step Z2: calculating the project supervision level coefficient Wj of a random supervision personnel according to the following formula:
the method comprises the steps that Aj represents the working age of a random proctoring person, ti represents the delay time of the corresponding proctoring person for finishing the proctoring work of a random engineering project, qi represents the quality assessment value of the corresponding proctoring person on the random engineering project, qi represents the actual quality assessment value of the random engineering project after being verified, the engineering proctoring level coefficient set of the proctoring person is obtained through calculation in the same calculation mode and is W = { W1, W2, \ 8230, wj, \ 8230, wn }, the proctoring persons are arranged according to the sequence of the engineering proctoring level coefficients from large to small, proctoring person information is stored according to the arrangement sequence, the engineering proctoring level of the proctoring person is analyzed by combining the self-qualification and the real proctoring data of the history, the proctoring persons are arranged according to the level, and the accuracy of the arrangement result is improved;
in step Z3: calling project commission time needing project supervision, and when the project commission time needing project supervision is different: and preferentially arranging the personnel with high project supervision level coefficient to participate in the supervision work of the corresponding project according to the number of the supervision personnel required by the project, and preferentially arranging the personnel with high project supervision level to participate in the supervision work when project commission time is not coincident, so that the reliability of a single project supervision result is improved.
Further, in step Z4: when projects with the same commission time and needing project supervision are available: counting f projects with the same consignation time, and calling the engineering quantity set of the f projects as G ’ ＝{G1 ’ ，G2 ’ ，…，Gf ’ }，
Acquiring the project engineering quantity g of the past supervision completed randomly on time at one time and the supervision personnel quantity h of the corresponding project arrangement, and according to a formula
Calculating to obtain the number xi of proctoring personnel needing to be arranged in a random project, rounding xi, obtaining a set of the number xi of the proctoring personnel needing to be arranged in f projects in the same calculation mode as x = { x1, x2, \ 8230;, xf }, and randomly dividing n proctoring personnel into f groups, wherein f is the number xi of the proctoring personnel needing to be arranged in f projects, and f is the number xi of the proctoring personnel needing to be arranged in f projects<n, acquiring to a random distribution mode: the average value set of the engineering supervision level coefficients of each group of supervision personnel is
Calculating the suitability E of the supervisors distributed according to the corresponding distribution mode according to the following formula u ：
Wherein,
representing the average value of project supervision level coefficients of a random group of supervisors, and obtaining the adaptation degree set of the supervisors distributed according to different distribution modes as E = { E = (E) } through the same calculation mode 1 ，E 2 ，…， E u ，…，E v And when the project consignment time is coincident, analyzing the data of the project supervision work normally completed in the past and reasonably distributing the number of supervision personnel required by projects with different project quantities, after the quantity distribution is completed, distributing specific supervision personnel, and distributing the supervision personnel according to the mode corresponding to the maximum suitability degree, thereby being beneficial to integrally improving the reliability of project supervision results of project supervision at the same time consigned for project supervision.
Further, in step Z5: if the project commission time required to carry out project supervision is different: arranging supervisors to participate in the project according to the sequence of the engineering supervision level coefficient from large to small; if the project needing project supervision with the same consignment time exists: allocating a corresponding number of supervision personnel to participate in the corresponding project according to the optimal allocation mode, and performing quality evaluation on the engineering project and submitting an engineering project quality evaluation report by the supervision personnel.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the project supervision level of the supervision personnel is analyzed by collecting and analyzing the project data which the supervision personnel has participated in the past through big data and combining the self-qualification data of the supervision personnel, the supervision personnel are sequenced according to the level, the accuracy of sequencing results is improved, when project consignment time is not coincident, the personnel with high project supervision level are preferentially arranged to participate in supervision work, and the reliability of a single project supervision result is improved; when project entrusting time is coincident, the number of the supervision personnel participating in the project is preferentially distributed, the supervision personnel specifically distributed in each project are optimized after distribution is completed, and the distribution mode is optimized according to the adaptation degree, so that the reliability of project supervision results of project supervision performed by entrusting at the same time is integrally improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram of a big data based project administration project evaluation system of the present invention;
FIG. 2 is a flow chart of a big data-based project supervision evaluation method according to the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Referring to fig. 1-2, the present invention provides a technical solution: a big data-based project supervision evaluation system comprises: the system comprises a supervision information acquisition module, a data storage management module, a database, an engineering project analysis module and an engineering supervision management module;
the output end of the supervision information acquisition module is connected with the input ends of the data storage management module and the database, the output end of the data storage management module is connected with the input end of the database, the output end of the database is connected with the input end of the engineering project analysis module, and the output end of the engineering project analysis module is connected with the input end of the engineering supervision management module;
the supervision information acquisition module is used for acquiring project information needing project supervision and personnel historical supervision information of supervision projects, transmitting the supervision information to the data storage management module and transmitting the project information to the database;
the data storage management module is used for sequencing the personnel for supervising the project and storing the personnel information into the database after sequencing;
the database is used for storing all received data;
the engineering project analysis module is used for analyzing the number of supervision personnel needed by different engineering projects;
the project supervision management module is used for supervision and evaluation of different project by distribution personnel.
The supervision information acquisition module comprises a project information acquisition unit and a supervision information acquisition unit;
the output end of the project information acquisition unit is connected with the input end of the database;
the project information acquisition unit is used for acquiring project commission time and project engineering quantity information which need to be managed by a project and transmitting the acquired information to the database;
the supervision information acquisition unit is used for acquiring historical supervision data of different personnel and transmitting the acquired data to the data storage management module.
The data storage management module comprises a supervision level analysis unit and a data storage sequencing unit;
the input end of the supervision level analysis unit is connected with the output end of the supervision information acquisition unit, the output end of the supervision level analysis unit is connected with the input end of the data storage sorting unit, and the output end of the data storage sorting unit is connected with the input end of the database;
the supervision level analysis unit is used for analyzing engineering supervision level coefficients of different personnel;
and the data storage sorting unit is used for sorting the personnel according to the sequence of the engineering supervision level coefficients from large to small and storing the sorted personnel information into a database.
The engineering project analysis module comprises a project data calling unit and a quantity analysis unit;
the input end of the project data calling unit is connected with the input end of the database, and the output end of the project data calling unit is connected with the input end of the quantity analysis unit;
the project data calling unit is used for calling project entrusting time data needing project supervision;
and the quantity analysis unit is used for analyzing the quantity of supervision personnel needed by the corresponding project according to the project quantity information of the project when the projects needing project supervision with the same consignment time exist.
The project supervision management module comprises a personnel distribution management unit and a project evaluation unit;
the input end of the personnel allocation management unit is connected with the output ends of the database and the quantity analysis unit, and the output end of the personnel allocation management unit is connected with the input end of the project evaluation unit;
the personnel allocation management unit is used for allocating the quantity of project supervision personnel required by a project and optimizing the allocation mode;
and the project evaluation unit is used for arranging project supervision personnel corresponding to project distribution according to the optimal distribution mode to supervise the project and submit a project quality evaluation report.
A project supervision project evaluation method based on big data comprises the following steps:
z1: collecting project information needing project supervision and historical supervision information of supervision personnel;
z2: sequencing the personnel for supervising the project, and storing the personnel information according to the sequencing sequence;
z3: when project commission time needing project supervision is different, distributing personnel according to an arrangement sequence;
z4: when projects needing project supervision with the same entrusting time exist, the number of personnel needed by the projects is distributed, and the distribution mode is optimized;
z5: and allocating personnel to supervise and evaluate different engineering projects according to the allocation result.
In step Z1: the method comprises the following steps of collecting a project consignment time set which needs project supervision as T = { T1, T2, \8230;, tm }, wherein the project quantity set corresponding to a project is G = { G1, G2, \8230;, gm }, wherein m represents the project quantity entrusted to project supervision, and collecting An employment age set of supervisors as A = { A1, A2, \8230;, an }, wherein n represents the supervisor quantity, and randomly collecting k project supervision data which are previously supervised by the supervisors: collecting random supervision personnel in the past supervision-participating engineering project: the set of delay time duration for proctoring work completion is t = { t1, t2, \8230;, tk }, the set of quality evaluation values corresponding to proctoring personnel on engineering projects is Q = { Q1, Q2, \8230;, qk }, and the set of actual quality evaluation values after verification is Q = { Q1, Q2, \8230;, qk }.
In step Z2: calculating the project supervision level coefficient Wj of a random supervision person according to the following formula:
wherein Aj represents the working age of a random proctoring person, ti represents the delay time of the corresponding proctoring person for completing the proctoring work of a random engineering project, qi represents the quality assessment value of the corresponding proctoring person on the random engineering project, qi represents the actual quality assessment value of the random engineering project after the inspection, the engineering proctoring level coefficient set of the proctoring person is obtained by calculation in the same calculation mode and is W = { W1, W2, \ 8230, wj, \8230, wn }, the proctoring persons are arranged according to the sequence of the engineering proctoring level coefficients from large to small, the proctoring person information is stored according to the arrangement sequence, the working age of the proctoring person can mainly embody the self-qualification of the proctoring person, and the engineering project data which the proctoring person has participated in the past are collected and analyzed through big data: the shorter the delay time of the supervision work is, the smaller the quality evaluation result deviation is, and the higher the engineering supervision level of the corresponding supervision personnel is;
in step Z3: calling project commission time needing project supervision, and when the project commission time needing project supervision is different: and preferentially arranging the personnel with large project supervision level coefficient to participate in supervision work of the corresponding project according to the number of supervision personnel required by the project.
In step Z4: when projects needing project supervision with the same consignment time exist: counting f projects with the same consignation time, and calling the engineering quantity set of the f projects as G ’ ＝{G1 ’ ， G2 ’ ，…，Gf ’ }，
Acquiring the project engineering quantity g of the past project supervision completed randomly and one time on time, acquiring the supervision personnel quantity h corresponding to the project arrangement, and performing supervision according to a formula
Calculating to obtain the number xi of proctoring personnel needing to be arranged in a random project, rounding xi, obtaining a set of the number xi of the proctoring personnel needing to be arranged in f projects in the same calculation mode as x = { x1, x2, \ 8230;, xf }, and randomly dividing n proctoring personnel into f groups, wherein f is the number xi of the proctoring personnel needing to be arranged in f projects, and f is the number xi of the proctoring personnel needing to be arranged in f projects<n, acquiring a random distribution mode: the average value set of the engineering supervision level coefficients of each group of supervision personnel is
Calculating the degree of adaptation E of allocating proctoring personnel according to the corresponding allocation mode according to the following formula u ：
Wherein,
representing the average value of project supervision level coefficients of a random group of supervisors, and obtaining the adaptation degree set of the supervisors distributed according to different distribution modes as E = { E = (E) } through the same calculation mode 1 ，E 2 ，…，
E u ，…，E v And h, sharing a v-distribution formula, comparing the adaptation degrees of the proctoring personnel distributed in different modes, selecting the distribution mode with the maximum adaptation degree as the optimal distribution mode, distributing the proctoring personnel to participate in the corresponding items according to the optimal distribution mode, distributing specific proctoring personnel after the quantity distribution is finished, randomly grouping the proctoring personnel according to the number of people required by each item, judging the adaptation degree of the distribution mode by analyzing the deviation degree between the average proctoring levels of each group of proctoring personnel generated in different distribution modes, wherein the lower the deviation degree is, the larger the adaptation degree is.
In step Z5: if the project commission time required to carry out project supervision is different: arranging supervisors to participate in the project according to the sequence of the engineering supervision level coefficient from large to small; if the project which needs project supervision and has the same entrusting time is available: allocating a corresponding number of proctoring personnel to participate in the corresponding project according to the optimal allocation mode, and performing quality evaluation on the project by the proctoring personnel and submitting a project quality evaluation report.
The first embodiment is as follows: the project commission time needing project supervision is collected, the collection of the working years of supervision personnel is A = { A1, A2, A3, A4, A5} = {8,5,3,6, 10}, and random supervision personnel are collected in the project which participates in supervision in the past: the set of delay time duration for finishing supervision work is t = { t1, t2, t3} = {5,3,1}, and the unit is: and in days, the quality evaluation value set of the engineering project by the corresponding supervisor is Q = { Q1, Q2, Q3} = {95, 87, 93}, the actual quality evaluation value set after verification is Q = { Q1, Q2, Q3} = {90, 80, 90}, and the quality evaluation value set is obtained according to the formula
Calculating the project supervision level coefficient Wj of a random supervisor about 0.78,the set of engineering supervision level coefficients of the supervision personnel is calculated in the same calculation mode, wherein W = { W1, W2, W3, W4, W5} = {0.78,0.8,0.5,0.6,0.92}, and W5 is the set of engineering supervision level coefficients of the supervision personnel>W2>W1>W4>W3, arranging supervision personnel according to the sequence of the engineering supervision horizontal coefficients from large to small, wherein project commission time required for engineering supervision is different: arranging supervisors to participate in the project according to the sequence of the engineering supervision level coefficient from large to small;
example two: collecting project commission time required to be managed, counting f =2 projects with the same commission time, and calling the set of the quantities of the projects with f =2 projects as G ’ ＝{G1 ’ ，G2 ’ The method comprises the steps of = {200, 300}, obtaining the project engineering quantity of previous projects which are randomly subjected to supervision on time at one time in the past to be g =100, obtaining the number of supervision personnel arranged corresponding to the projects to be h =1, and obtaining the project engineering quantity according to a formula
Calculating to obtain a set of prisoners number to be arranged for f items, wherein x = { x1, x2} = {2,3}, randomly dividing n =5 prisoners into f =2 groups, and acquiring a random distribution mode: the average value set of the engineering supervision level coefficients of each group of supervision personnel is
According to the formula
Calculating the degree of adaptation E of allocating proctoring personnel in a corresponding allocation manner u (ii) =17 (c) =17, the adaptation degree set of the supervisors distributed according to different distribution modes is obtained by the same calculation mode and is E = { E = { E } 1 ， E 2 ，E 3 ，E 4 ，E 5 ，E 6 ，E 7 ，E 8 ，E 9 ，E 10 = {17, 200, 20, 30, 19, 102, 25, 36, 21, 15}, the allocation mode with the largest adaptation degree is selected as the optimal allocation mode: the second distribution mode is that the supervision personnel with the corresponding quantity are distributed to participate in the corresponding project according to the optimal distribution mode, and the supervision personnel carry out project planningAnd (5) evaluating the line quality and submitting an engineering project quality evaluation report.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides an engineering supervision project evaluation system based on big data which characterized in that: the system comprises: the system comprises a supervision information acquisition module, a data storage management module, a database, an engineering project analysis module and an engineering supervision management module;
the output end of the supervision information acquisition module is connected with the input ends of the data storage management module and the database, the output end of the data storage management module is connected with the input end of the database, the output end of the database is connected with the input end of the engineering project analysis module, and the output end of the engineering project analysis module is connected with the input end of the engineering supervision management module;
the supervision information acquisition module is used for acquiring project information needing project supervision and personnel historical supervision information of supervision projects, transmitting the supervision information to the data storage management module and transmitting the project information to the database;
the data storage management module is used for sequencing the personnel for supervising the project and storing the personnel information into the database after sequencing;
the database is used for storing all received data;
the engineering project analysis module is used for analyzing the number of supervision personnel required by different engineering projects;
the project supervision management module is used for supervision and evaluation of different project by distribution personnel.
2. The big data based project supervision project evaluation system according to claim 1, wherein: the supervision information acquisition module comprises a project information acquisition unit and a supervision information acquisition unit;
the output end of the project information acquisition unit is connected with the input end of the database;
the project information acquisition unit is used for acquiring project commission time and project engineering quantity information which need to be managed by a project and transmitting the acquired information to the database;
the supervision information acquisition unit is used for acquiring historical supervision data of different personnel and transmitting the acquired data to the data storage management module.
3. The big data based project supervision project evaluation system according to claim 2, wherein: the data storage management module comprises a proctoring level analysis unit and a data storage sequencing unit;
the input end of the supervision level analysis unit is connected with the output end of the supervision information acquisition unit, the output end of the supervision level analysis unit is connected with the input end of the data storage sorting unit, and the output end of the data storage sorting unit is connected with the input end of the database;
the supervision level analysis unit is used for analyzing engineering supervision level coefficients of different personnel;
the data storage and sorting unit is used for sorting the personnel in the order from large to small according to the engineering supervision level coefficient and storing the sorted personnel information into the database.
4. The big data based project supervision project evaluation system according to claim 1, wherein: the engineering project analysis module comprises a project data calling unit and a quantity analysis unit;
the input end of the project data calling unit is connected with the input end of the database, and the output end of the project data calling unit is connected with the input end of the quantity analysis unit;
the project data calling unit is used for calling project entrusting time data needing project supervision;
and the quantity analysis unit is used for analyzing the quantity of supervision personnel needed by the corresponding project according to the project quantity information of the project when the projects needing project supervision with the same consignment time exist.
5. The big data based project supervision project evaluation system according to claim 4, wherein: the project supervision management module comprises a personnel distribution management unit and a project evaluation unit;
the input end of the personnel allocation management unit is connected with the output ends of the database and the quantity analysis unit, and the output end of the personnel allocation management unit is connected with the input end of the project evaluation unit;
the personnel allocation management unit is used for allocating the number of project supervision personnel required by a project and optimizing the allocation mode;
and the project evaluation unit is used for arranging project supervision personnel corresponding to project distribution according to the optimal distribution mode to supervise the project and submit a project quality evaluation report.
6. A big data-based project supervision evaluation method is characterized by comprising the following steps: the method comprises the following steps:
z1: collecting project information needing project supervision and historical supervision information of supervision personnel;
z2: sequencing the personnel for supervising the project, and storing the personnel information according to the sequencing sequence;
z3: when project commission time required to be managed by a project is different, distributing personnel according to the arrangement sequence;
z4: when projects needing project supervision with the same entrusting time exist, the number of personnel needed by the projects is distributed, and the distribution mode is optimized;
z5: and allocating personnel to supervise and evaluate different engineering projects according to the allocation result.
7. The big data-based project supervision evaluation method according to claim 6, characterized in that: in step Z1: the method comprises the following steps of collecting a project consignment time set which needs project supervision as T = { T1, T2, \8230;, tm }, wherein the project quantity set corresponding to a project is G = { G1, G2, \8230;, gm }, wherein m represents the project quantity entrusted to project supervision, and collecting An employment age set of supervisors as A = { A1, A2, \8230;, an }, wherein n represents the supervisor quantity, and randomly collecting k project supervision data which are previously supervised by the supervisors: collecting the following projects that a proctoring person randomly participates in proctoring in the past: the set of delay time duration for proctoring work completion is t = { t1, t2, \8230;, tk }, the set of quality evaluation values corresponding to proctoring personnel on engineering projects is Q = { Q1, Q2, \8230;, qk }, and the set of actual quality evaluation values after verification is Q = { Q1, Q2, \8230;, qk }.
8. The big data-based project supervision evaluation method according to claim 7, wherein: in step Z2: calculating the project supervision level coefficient Wj of a random supervision person according to the following formula:
wherein Aj represents the working age of a random proctoring person, ti represents the delay time of the corresponding proctoring person for finishing the proctoring work of a random engineering project, qi represents the quality assessment value of the corresponding proctoring person on the random engineering project, qi represents the actual quality assessment value of the random engineering project after the inspection, the engineering proctoring level coefficient set of the proctoring person is obtained by calculation in the same calculation mode and is W = { W1, W2, \ 8230, wj, \8230, wn }, the proctoring persons are arranged according to the sequence of the engineering proctoring level coefficients from large to small, and the proctoring person information is stored according to the arrangement sequence;
in step Z3: calling project commission time needing project supervision, and when the project commission time needing project supervision is different: and preferentially arranging the personnel with large project supervision level coefficient to participate in supervision work of the corresponding project according to the number of supervision personnel required by the project.
9. The big data based project supervision evaluation method according to claim 7, wherein: in step Z4: when projects needing project supervision with the same consignment time exist: counting f projects with the same consignation time, and calling the engineering quantity set of the f projects as G ’ ={G1 ’ ，G2 ’ ，…，Gf ’ }，G ’ 8834G, acquiring project quantity G for finishing supervision at one time at random and supervision personnel quantity h corresponding to project arrangement, and calculating according to formula
Calculating to obtain the number xi of proctoring personnel needing to be arranged in a random project, rounding the xi, obtaining a set of the number xi of proctoring personnel needing to be arranged in f projects in the same calculation mode, wherein the set is x = { x1, x2, \8230;, xf }, and randomly dividing n proctoring personnel into f groups, and f<n, acquiring a random distribution mode: the average value set of the engineering supervision level coefficients of each group of supervision personnel is
={
，
，…，
，…，
According to the following disclosureFormula calculation Adaptation E for allocating proctorial staff according to corresponding allocation mode u ：
Wherein,
representing the average value of project supervision level coefficients of a random group of supervisors, and obtaining the adaptation degree set of the supervisors distributed according to different distribution modes as E = { E = (E) } through the same calculation mode 1 ，E 2 ，…，E u ，…，E v And h, sharing a v distribution formula, comparing the adaptation degrees of the supervision personnel distributed in different modes, selecting the distribution mode with the maximum adaptation degree as an optimal distribution mode, and distributing the supervision personnel to participate in the corresponding project according to the optimal distribution mode.
10. The big data-based project supervision project evaluation method according to claim 8 or 9, wherein: in step Z5: if the project commission time required to carry out project supervision is different: arranging supervisors to participate in the project according to the sequence of the engineering supervision level coefficient from large to small; if the project which needs project supervision and has the same entrusting time is available: allocating a corresponding number of proctoring personnel to participate in the corresponding project according to the optimal allocation mode, and performing quality evaluation on the project by the proctoring personnel and submitting a project quality evaluation report.
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| CN115796563A (en) * | 2023-02-10 | 2023-03-14 | 中建安装集团有限公司 | Steel structure list checking and verifying management system based on big data |
| CN117173613A (en) * | 2023-09-15 | 2023-12-05 | 中国铁路广州局集团有限公司 | Intelligent management system and method for whole process informatization of engineering construction project |
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| CN115796563A (en) * | 2023-02-10 | 2023-03-14 | 中建安装集团有限公司 | Steel structure list checking and verifying management system based on big data |
| CN115796563B (en) * | 2023-02-10 | 2023-04-11 | 中建安装集团有限公司 | Steel structure list checking and verifying management system based on big data |
| CN117173613A (en) * | 2023-09-15 | 2023-12-05 | 中国铁路广州局集团有限公司 | Intelligent management system and method for whole process informatization of engineering construction project |
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