CN117313950A - Building construction project manpower resource prediction selection system based on big data - Google Patents

Building construction project manpower resource prediction selection system based on big data Download PDF

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CN117313950A
CN117313950A CN202311383598.2A CN202311383598A CN117313950A CN 117313950 A CN117313950 A CN 117313950A CN 202311383598 A CN202311383598 A CN 202311383598A CN 117313950 A CN117313950 A CN 117313950A
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efficiency
constructor
building
work
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杨飞飞
穆明辉
吴祥祥
汪哲语
梁超
陈文尹
申志军
张静雯
张栋鹏
张石亮
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Anhui Shuzhi Construction Research Institute Co ltd
China Tiesiju Civil Engineering Group Co Ltd CTCE Group
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China Tiesiju Civil Engineering Group Co Ltd CTCE Group
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Abstract

The invention belongs to the technical field of building engineering manpower resource management, in particular to a large-data-based building construction project manpower resource prediction selection system.

Description

Building construction project manpower resource prediction selection system based on big data
Technical Field
The invention belongs to the technical field of human resource management of constructional engineering, and particularly relates to a human resource prediction and selection system for a construction project based on big data.
Background
Along with the acceleration of the urban process, more and more people are rushed to cities, the building engineering provides necessary housing and living solutions for the population growth of the cities, so that the building engineering has increasingly growing requirements on the construction of the cities, the construction of the building engineering is not separated from manpower, and the reasonable and efficient utilization of manpower resources is known to have important influence on guaranteeing the quality and efficiency of the construction project, in this case, the manpower resource management becomes an indispensable management direction in the construction management of the construction project, and particularly comprises the accurate prediction of the number of constructors before the construction, and the optimization selection of the constructors in the construction process.
Because the prediction of the number of constructors is carried out before building a building project and cannot be performed according to blank prediction, most of the prediction is carried out according to the construction data of the historical building project, but the existing prediction mode usually takes the planned building body quantity and the planned construction time length of the building project as parameters, the parameters are biased to subjectivity, the influence of the weather condition of the position of the building project on the prediction result is ignored, because the bad weather condition possibly causes the progress of the building project to be blocked, more manpower resources are needed to compensate for delay, the parameters according to the existing prediction mode are one-sided, objective and reasonable are not enough, the accuracy of the prediction result is influenced to a certain extent, the number of constructors is easy to predict too little or too much, and the construction of the building project is plagued.
In addition, most of constructors in the prior art are processed directly according to construction efficiency in the construction process, particularly constructors with lower construction efficiency, analysis on reasons of inefficiency is lacking, such as inefficiency of constructors is caused by bad construction environment, inefficiency of constructors is caused by incorrect construction attitude, unfair phenomenon is caused if the constructors are processed in the same mode, and therefore the optimization mode of the constructors with low efficiency in the prior art is too general and solidified, and the constructors with low efficiency are not specific, so that the optimization effect is poor.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the background art, a system for predicting and selecting human resources for a building construction project based on big data is now proposed.
The aim of the invention can be achieved by the following technical scheme: building construction project manpower resource prediction selection system based on big data includes: the basic information acquisition module is used for acquiring basic information of the target building project, wherein the basic information comprises building type, planned building body quantity, geographical position of the building, planned start date and planned construction duration.
And the work demand constructor number prediction module is used for predicting the number of the demand constructors of the target building project corresponding to various works from the historical building project based on the basic information of the target building project.
The construction association information recording module is used for acquiring the identity information of each constructor corresponding to each worker after the project manager performs construction selection according to the number of the constructors corresponding to each worker, numbering the constructors under each worker, and recording the construction association information of each constructor corresponding to each constructor in each analysis period at the same time to obtain the construction association information of each constructor corresponding to each constructor under the current analysis period.
The historical building library is used for storing building types, geographical positions of the buildings, starting dates, building body quantity, construction duration and the number of constructors used by each work in the construction process, which correspond to each historical building project.
And the work type construction efficiency analysis module is used for analyzing the construction efficiency corresponding to each work type based on the construction related information corresponding to each constructor of each work type in the current analysis period.
And the expected completion judging module of the target building project is used for judging whether the target building project can be expected to be completed or not according to the construction efficiency corresponding to each work type in the current analysis period.
The abnormal identification module is used for carrying out early warning when the target building project is judged to be unable to finish as expected, and identifying abnormal work types and low-efficiency constructors.
And the low-efficiency constructor optimizing module is used for analyzing the low-efficiency reasons of the low-efficiency constructors corresponding to the abnormal work types and carrying out optimized management on the low-efficiency constructors according to the low-efficiency reasons.
In an alternative embodiment, the number of constructors required by the prediction target building project corresponding to each work is as follows: the building type and the geographical position of the building are extracted from the basic information, and are matched with the building type and the geographical position of the building of each historical building item in the historical building library, and the successfully matched historical building item is screened out as an effective historical building item.
Extracting the planned construction volume and the planned construction time from the basic information, extracting the construction volume and the construction time corresponding to each effective historical building project from the historical building library, and further extracting the planned construction volume and the plan of the target building projectThe construction time length is compared with the construction volume and the construction time length corresponding to each effective historical building project, and the expression is used for expressing the construction time lengthCalculating the similarity eta of each effective historical building project relative to the target building project i Where i denotes the number of a valid history building project, i=1, 2, &.. i 、t i Respectively expressed as the building body quantity and the construction time length corresponding to the i effective history building project, q 0 、t 0 Expressed as the planned construction volume and the planned construction time length of the target building project, respectively, and e is expressed as a natural constant.
And comparing the similarity of each effective historical building item relative to the target building item with a set similarity threshold value, and extracting the effective historical building items which are larger than or equal to the similarity threshold value from the similarity threshold value as standby historical building items.
And extracting the start date corresponding to the standby history building project from the history building library, and combining the start date with the construction time of the standby history building project to form a construction period corresponding to the standby history building project, thereby obtaining the season to which the construction period belongs.
The planned construction date and the planned construction time are extracted from the basic information, and a planned construction period corresponding to the target building project is formed, so that seasons to which the planned construction period belongs are obtained accordingly.
And comparing the seasons of the construction period corresponding to the standby historical building project with the seasons of the planning construction period corresponding to the target building project, so that the standby historical building project successfully compared is screened out and used as the reference historical building project.
Extracting the number of constructors used by various works in the construction process of a reference history building project from a history building library, and importing a calculation formulaCalculating the number w of constructors required by each work corresponding to the target building project Demand j Where j is denoted as the job number, j=1,2,……,m，w j d is expressed as the number of constructors used by the jth work in the construction process of the jth reference history building item, d is expressed as the number of the reference history building items, d=1, 2, … …, z, z is expressed as the number of the reference history building items, η d Expressed as similarity of the d-th reference historical building item to the target building item.
In an alternative embodiment, the obtaining manner of each analysis period is: when the construction of the target building project is started, the construction date is divided backwards according to the set time interval, and each analysis period is obtained.
In an alternative embodiment, the construction-related information includes construction days and an engineering completion amount.
In an alternative embodiment, the specific analysis process of the construction efficiency corresponding to each work type is as follows: importing construction related information corresponding to each constructor of each work class under the current analysis period into a construction efficiency formulaCalculating the construction efficiency corresponding to each work type>In p j k represents the engineering completion amount of the k constructor corresponding to the j work under the current analysis period, k represents the constructor number corresponding to each work, and k=1, 2 j And k represents the construction days of the jth work class corresponding to the kth constructor in the current analysis period.
In an alternative embodiment, the assessment of whether the target building project can be completed as desired is described in the following procedure: and acquiring the total engineering quantity of each work corresponding to the target building project, and counting the completed engineering quantity of each work corresponding to the target building project in the current analysis period, so as to calculate the residual engineering quantity of each work.
And dividing the planned construction time length of the target building project according to the work types to obtain the planned construction time length corresponding to each work type, and simultaneously counting the constructed time length corresponding to each work type of the target building project in the current analysis period, so as to calculate the residual construction time length corresponding to each work type.
And calculating the engineering completion amount of the corresponding construction efficiency of each work under the current analysis period by combining the residual construction time length corresponding to each work with the corresponding construction efficiency of each work.
And comparing the engineering completion amount of the construction efficiency corresponding to each work in the current analysis period with the residual engineering amount corresponding to each work, and if the engineering completion amount of the construction efficiency corresponding to a certain work in the current analysis period is smaller than the residual engineering amount corresponding to the work, judging that the target building project cannot be completed as expected.
In an alternative embodiment, the specific operation mode of identifying the abnormal work category is to select the work category with the engineering completion amount smaller than the residual engineering amount from the work categories as the abnormal work category.
In an alternative embodiment, the specific identification process of the low-efficiency constructor is as follows, namely, the work attendance record and the construction record of the constructor corresponding to the abnormal work category under the current analysis period are extracted, the working time of the constructor on each construction day is extracted from the work attendance record, the engineering completion amount of the constructor on each construction day is extracted from the construction record, and the engineering completion amount is further expressed by the expressionAnd calculating the efficiency coefficient of each constructor on each construction day.
And carrying out normal analysis on the efficiency coefficient of each constructor corresponding to the abnormal work type on each construction day to obtain the normal efficiency coefficient of each constructor corresponding to the abnormal work type, comparing the normal efficiency coefficient with the set standard efficiency coefficient, and screening constructors smaller than the standard efficiency coefficient from the normal efficiency coefficient to serve as low-efficiency constructors.
In an alternative embodiment, the analysis of the inefficiency cause of the corresponding inefficiency constructor for the abnormal job is performed as follows: and acquiring the number of the low-efficiency constructor, thereby determining the identity information of the low-efficiency constructor, and further extracting the construction monitoring video of the low-efficiency constructor in the current analysis period from the construction monitoring record.
Identifying whether an abnormal construction behavior exists in the construction monitoring video by the low-efficiency constructor, if so, extracting occurrence frequency and occurrence time of the abnormal construction behavior, thereby utilizing the expressionCalculating a construction abnormality index corresponding to the low-efficiency constructor, comparing the construction abnormality index with a preset threshold, if the construction abnormality index corresponding to the low-efficiency constructor is larger than the preset threshold, predicting that the low-efficiency reason of the low-efficiency constructor is not correct in construction attitude, if the construction abnormality index corresponding to the low-efficiency constructor is smaller than or equal to the preset threshold, calling the weather state of the low-efficiency constructor on the construction day in the current analysis period from a weather platform, recognizing whether severe weather exists, if the severe weather exists, predicting that the low-efficiency reason of the low-efficiency constructor is poor in construction environment, otherwise, predicting that the low-efficiency reason of the constructor is poor in construction capability.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the method, the building type, the planned construction volume, the geographical position of the building, the planned construction date and the planned construction time length of the target building project are obtained, and the geographical position of the building, the planned construction date and the planned construction time length are used as the weather conditions of the building site of the target building project, so that the historical building project consistent with the weather conditions of the building site of the target building project is screened out from a historical building library and used as a prediction reference, the number of constructors is expanded, the prediction is more objective and reasonable, the accuracy of a prediction result is greatly improved, the situation that the number of constructors is too little or too much in prediction is avoided, and the trouble caused to the construction of the building project is reduced.
(2) According to the invention, in the construction process of the target building project, whether the target building project can be finished as expected is judged by analyzing the construction efficiency of each work, and abnormal work and low-efficiency constructors are identified when the target building project cannot be finished as expected, so that the low-efficiency reasons of the low-efficiency constructors are analyzed, the low-efficiency constructors are optimized according to the low-efficiency reasons, the targeted optimization of the low-efficiency constructors is realized, the defects of the existing optimization mode are effectively avoided, the optimization effect is improved to the maximum extent, and the optimization result is facilitated to be improved.
(3) According to the invention, when the low-efficiency constructor is identified, the construction period is divided into analysis time periods, and then the low-efficiency constructor is identified in each analysis time period, so that the dynamic identification of the low-efficiency constructor is realized, the low-efficiency constructor can be identified in real time in the construction process of the target building project, and the missing identification of the low-efficiency constructor is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the connection of the modules of the system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a large data-based construction project human resource prediction selection system, which comprises a target construction project basic information acquisition module, a construction type demand constructor number prediction module, a construction association information recording module, a historical construction library, a construction type construction efficiency analysis module, a target construction project completion judgment module, an abnormality identification module and an low-efficiency constructor optimization module, wherein the target construction project basic information acquisition module and the historical construction library are both connected with the construction type demand constructor number prediction module, the construction type demand constructor number prediction module is connected with the construction association information recording module, the construction association information recording module is connected with the construction type construction efficiency analysis module, the construction type construction efficiency analysis module is connected with the target construction project completion judgment module, the target construction project completion judgment module is connected with the abnormality identification module, and the abnormality identification module is connected with the low-efficiency constructor optimization module.
The basic information acquisition module of the target building project is used for acquiring basic information of the target building project, wherein the basic information comprises building types, planned building body quantity, geographical positions of the buildings, planned construction date and planned construction duration.
By way of example, the building types mentioned above may be residential buildings, commercial buildings, public buildings, etc.
The work demand constructor number prediction module is used for predicting the number of the demand constructors of the target building project corresponding to various works from the historical building project based on the basic information of the target building project, and the specific prediction process is as follows: the building type and the geographical position of the building are extracted from the basic information, and are matched with the building type and the geographical position of the building of each historical building item in the historical building library, and the successfully matched historical building item is screened out as an effective historical building item.
It should be added that the above-mentioned successful matching means that the building type and the geographical location of the building can be matched.
It should be noted that, the reason why the above-mentioned geographical location of the building is taken as the prediction parameter is that different geographical locations determine different climate types, and thus, different climate states are exhibited.
Extracting the planned construction volume and the planned construction time length from the basic information, extracting the construction volume and the construction time length corresponding to each effective historical building project from the historical building library, and further enabling the planned construction volume and the planned construction time length of the target building project to be corresponding to the construction volume and the construction time of each effective historical building projectLength is compared by expressionCalculating the similarity eta of each effective historical building project relative to the target building project i Where i denotes the number of a valid history building project, i=1, 2, &.. i 、t i Respectively expressed as the building body quantity and the construction time length corresponding to the i effective history building project, q 0 、t 0 The method comprises the steps of respectively representing the planned construction volume and the planned construction duration of a target building project, and e representing a natural constant, wherein the closer the construction volume and the construction duration corresponding to the effective historical building project are to the planned construction volume and the planned construction duration of the target building project, the greater the similarity of the effective historical building project to the target building project.
And comparing the similarity of each effective historical building item relative to the target building item with a set similarity threshold value, and extracting the effective historical building items which are larger than or equal to the similarity threshold value from the similarity threshold value as standby historical building items.
And extracting the start date corresponding to the standby history building project from the history building library, and combining the start date with the construction time of the standby history building project to form a construction period corresponding to the standby history building project, thereby obtaining the season to which the construction period belongs.
As a preferable mode of the above scheme, the specific operation mode of acquiring the season to which the construction period belongs is to acquire the climate type corresponding to the geographical location based on the geographical location of the target building project from the map, match the climate type with the month distribution of each season corresponding to each climate type, and match the month distribution of each season corresponding to the geographical location.
And comparing the construction period corresponding to the standby historical building project with the month distribution of each season corresponding to the geographic position, and obtaining the season to which the construction period corresponding to the standby historical building project belongs.
For example, the distribution of the months in each season of the geographic location is 3 months to 5 months, the distribution of the months in summer is 6 months to 8 months, the distribution of the months in autumn is 9 months to 11 months, the distribution of the months in winter is 12 months to 2 months in coming years, and if the construction period corresponding to the standby history building project is 4 months 3 days to 11 months 20 days, the seasons to which the construction period corresponding to the standby history building project belongs are spring, summer and autumn, respectively.
The method comprises the steps of extracting a planned starting date and a planned construction time from basic information, forming a planned construction period corresponding to a target building project, and further acquiring a season to which the planned construction period belongs according to the planned construction period, wherein the acquisition mode refers to an acquisition process of the season to which the construction period corresponding to a standby historical building project belongs.
And comparing the seasons of the construction period corresponding to the standby historical building project with the seasons of the planning construction period corresponding to the target building project, so that the standby historical building project successfully compared is screened out and used as the reference historical building project.
It should be understood that, because the construction period of a building project is generally longer, especially for a large building, the seasons to which the construction period corresponding to the building project belongs generally span multiple seasons, when the seasons to which the construction period belongs are compared, the distribution sequence of the seasons to which the construction period belongs is considered, and the comparison success not only requires that the names of the seasons to which the construction period belongs be consistent, but also requires that the distribution sequence of the seasons to which the construction period belongs be consistent, so that the screening of the reference history building project can be more reasonable and effective.
Extracting the number of constructors used by various works in the construction process of a reference history building project from a history building library, and importing a calculation formulaCalculating the number w of constructors required by each work corresponding to the target building project Demand j Wherein j is represented by a work number, j=1, 2, … …, m, w j d is expressed as the number of constructors used by the jth work in the construction process of the jth reference history building item, d is expressed as the number of the reference history building items, d=1, 2, … …, z, z is expressed as the number of the reference history building items, η d Expressed as the d-th reference history building item relative targetSimilarity of building projects.
According to the method, the building type, the planned construction volume, the geographical position of the building, the planned construction date and the planned construction time length of the target building project are obtained, and the geographical position of the building, the planned construction date and the planned construction time length are used as the weather conditions of the building site of the target building project, so that the historical building project consistent with the weather conditions of the building site of the target building project is screened out from a historical building library and used as a prediction reference, the number of constructors is expanded, the prediction is more objective and reasonable, the accuracy of a prediction result is greatly improved, the situation that the number of constructors is too little or too much in prediction is avoided, and the trouble caused to the construction of the building project is reduced.
According to the method, when the climate conditions of the building site where the target building project is located are considered, the climate conditions are represented by seasons by obtaining the seasons of the target building project corresponding to the planned construction period, so that the climate conditions are considered pertinently when the number of constructors is predicted.
According to the method, when the number of constructors of a target building project is predicted, the constructors are divided according to the types of the works and are converted into the number of constructors required by the corresponding types of the works, so that the number of constructors is predicted more specifically and carefully, and the method is practical for the constructors.
The construction association information recording module is used for acquiring identity information of each constructor corresponding to each worker after project management personnel perform construction selection according to the number of constructors corresponding to each worker, wherein the identity information comprises names and face images, the constructors under each worker are numbered, meanwhile, construction association information of each constructor corresponding to each constructor is recorded in each analysis period, construction association information of each constructor corresponding to each constructor under the current analysis period is obtained, and the construction association information comprises construction days and engineering completion amount.
It should be noted that the above-mentioned amount of engineering completion is the total amount of engineering completed in the number of construction days.
The above embodiment is applied to the above embodiment, and the acquisition mode of each analysis period is as follows: when the construction of the target building project is started, the construction date is divided backwards according to the set time interval, and each analysis period is obtained.
According to the invention, when the low-efficiency constructor is identified, the construction period is divided into analysis time periods, and then the low-efficiency constructor is identified in each analysis time period, so that the dynamic identification of the low-efficiency constructor is realized, the low-efficiency constructor can be identified in real time in the construction process of the target building project, and the missing identification of the low-efficiency constructor is avoided.
The historical building library is used for storing building types, geographical positions of the buildings, starting dates, building body quantity, construction duration and the number of constructors used by various works in the construction process, which correspond to each historical building project.
The construction efficiency analysis module is used for analyzing the construction efficiency corresponding to each work type based on the construction associated information of each constructor corresponding to each work type under the current analysis period, and the specific analysis process is as follows: importing construction related information corresponding to each constructor of each work class under the current analysis period into a construction efficiency formulaCalculating construction efficiency zeta corresponding to various work types j Wherein p is j k represents the engineering completion amount of the kth constructor corresponding to the jth work under the current analysis period, k represents the constructor numbers corresponding to the various work, and k=1, 2, … …, w and f j And k represents the construction days of the jth work class corresponding to the kth constructor in the current analysis period.
The on-schedule completion judging module of the target building project is used for judging whether the target building project can be on-schedule completed or not according to the construction efficiency corresponding to each work type in the current analysis period, and the specific judging process is as follows: and obtaining the total engineering quantity of each work corresponding to the target building project, and counting the completed engineering quantity of each work corresponding to the target building project in the current analysis period, so that the total engineering quantity of each work is subtracted from the completed engineering quantity to calculate the residual engineering quantity of each work.
Dividing the planned construction time length of the target building project according to the types of the works to obtain the planned construction time length corresponding to each work, and simultaneously counting the constructed time length corresponding to each work in the target building project until the current analysis period, so that the planned construction time length corresponding to each work is subtracted from the constructed time length to calculate the residual construction time length corresponding to each work.
The method is characterized in that the planned construction time length of the target building project is extracted from the construction plan of the target building project according to the planned construction time length corresponding to each work type obtained by dividing the work types.
And calculating the engineering completion amount of the corresponding construction efficiency of each work under the current analysis period by combining the corresponding residual construction time of each work with the corresponding construction efficiency of each work, wherein a specific calculation formula is the engineering completion amount = residual construction time x construction efficiency.
And comparing the engineering completion amount of the construction efficiency corresponding to each work in the current analysis period with the residual engineering amount corresponding to each work, and if the engineering completion amount of the construction efficiency corresponding to a certain work in the current analysis period is smaller than the residual engineering amount corresponding to the work, judging that the target building project cannot be completed as expected.
The abnormal recognition module is used for carrying out early warning when the target building project is judged to be unable to finish as expected, and recognizing abnormal work types and low-efficiency constructors at the same time, wherein the recognition mode of the abnormal work types is that the work types with the engineering completion quantity smaller than the residual engineering quantity are selected from various work types and used as the abnormal work types.
Further, the specific recognition process of the low-efficiency constructors is as follows, the work attendance record and the construction record of the constructors corresponding to the abnormal work types under the current analysis period are extracted, the working time of each constructor on each construction day is extracted from the work attendance record, and the engineering completion amount of each constructor on each construction day is extracted from the construction record, so that the work completion amount is expressed by the expressionAnd calculating the efficiency coefficient of each constructor on each construction day.
The reference engineering quantity per unit time in the calculation formula of the efficiency coefficient is preconfigured, and the reference engineering quantity per unit time corresponding to each work type is preconfigured.
And carrying out normal analysis on the efficiency coefficient of each constructor corresponding to the abnormal work type on each construction day to obtain the normal efficiency coefficient of each constructor corresponding to the abnormal work type, comparing the normal efficiency coefficient with the set standard efficiency coefficient, and screening constructors smaller than the standard efficiency coefficient from the normal efficiency coefficient to serve as low-efficiency constructors.
The specific process of the normal analysis in the above steps is as follows: and carrying out variance calculation on the efficiency coefficient of each constructor corresponding to the abnormal work class on each construction day, comparing the calculation result with a set value, carrying out mean value calculation on the efficiency coefficient of each constructor corresponding to the abnormal work class on each construction day if the calculation result is smaller than or smaller than the set value, obtaining an average efficiency coefficient as a normal efficiency coefficient, and selecting the median efficiency coefficient from the efficiency coefficients of each constructor corresponding to the abnormal work class on each construction day as the normal efficiency coefficient if the calculation result is larger than the set value.
The low-efficiency constructor optimizing module is used for analyzing the low-efficiency reasons of the low-efficiency constructors corresponding to the abnormal work types and optimizing the low-efficiency constructors according to the low-efficiency reasons.
Preferably, the analysis of the reasons for inefficiency of the constructor with the inefficiency corresponding to the abnormal species is performed as follows: and acquiring the number of the low-efficiency constructor, thereby determining the identity information of the low-efficiency constructor, and further extracting the construction monitoring video of the low-efficiency constructor in the current analysis period from the construction monitoring record.
Identifying whether an abnormal construction behavior exists in the construction monitoring video by the low-efficiency constructor, if so, extracting occurrence frequency and occurrence time of the abnormal construction behavior, thereby utilizing the expressionCalculating a construction abnormality index corresponding to the low-efficiency constructor, comparing the construction abnormality index with a preset threshold, if the construction abnormality index corresponding to the low-efficiency constructor is larger than the preset threshold, predicting that the low-efficiency reason of the low-efficiency constructor is that the construction attitude is not correct, and if the low-efficiency construction is performedAnd if the construction abnormality index corresponding to the personnel is smaller than or equal to a preset threshold value, the weather state of the construction day of the low-efficiency constructor in the current analysis period is called from the weather platform, whether severe weather exists is identified, if so, the low-efficiency reason of the low-efficiency constructor is predicted to be the poor construction environment, otherwise, the low-efficiency reason of the constructor is predicted to be the lack of construction capability.
It should be noted that the occurrence time period of the abnormal construction behavior mentioned in the above is the total time period at the occurrence frequency.
It should be noted that the abnormal construction behavior refers to a behavior unrelated to construction, specifically may be playing a mobile phone, making a call, boring, etc., and specifically may be identified from the action characteristics of the low-efficiency constructor corresponding to the head and the hand.
It is further to be appreciated that severe weather is particularly rainfall, strong wind, heavy snow, high temperature, etc.
In a further embodiment of the above solution, the following measures are taken to optimize the inefficient constructors: if the low efficiency reasons of the low efficiency constructors are that the construction attitude is not correct, education is carried out on the low efficiency constructors by personnel management staff of the target building project.
If the inefficiency of the low-efficiency constructor is caused by the lack of construction capability, the low-efficiency constructor is technically trained.
According to the invention, in the construction process of the target building project, whether the target building project can be finished as expected is judged by analyzing the construction efficiency of each work, and abnormal work and low-efficiency constructors are identified when the target building project cannot be finished as expected, so that the low-efficiency reasons of the low-efficiency constructors are analyzed, the low-efficiency constructors are optimized according to the low-efficiency reasons, the targeted optimization of the low-efficiency constructors is realized, the defects of the existing optimization mode are effectively avoided, the optimization effect is improved to the maximum extent, and the optimization result is facilitated to be improved.
It should be noted that the construction time length mentioned in the present invention is measured in days.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.

Claims (9)

1. Building construction project manpower resource prediction selection system based on big data, characterized by comprising:
the basic information acquisition module of the target building project is used for acquiring basic information of the target building project, wherein the basic information comprises building types, planned building body quantity, geographic positions of the buildings, planned construction date and planned construction duration;
the work demand constructor number prediction module is used for predicting the number of the demand constructors of the target building project corresponding to various works from the historical building project based on the basic information of the target building project;
the construction association information recording module is used for acquiring the identity information of each constructor corresponding to each worker after the project manager performs construction selection according to the number of the constructors corresponding to each worker, numbering the constructors under each worker, and recording the construction association information of each constructor corresponding to each constructor in each analysis period to obtain the construction association information of each constructor corresponding to each constructor under the current analysis period;
the historical building library is used for storing building types, geographical positions of the buildings, starting dates, building body quantity, construction time and the number of constructors used by each work in the construction process, which correspond to each historical building project;
the construction efficiency analysis module is used for analyzing the construction efficiency corresponding to each work type based on the construction related information corresponding to each constructor of each work type in the current analysis period;
the on-schedule completion judging module of the target building project is used for judging whether the target building project can be on-schedule completed or not according to the construction efficiency corresponding to each work type in the current analysis period;
the abnormal identification module is used for carrying out early warning when the target building project is judged to be unable to finish as expected, and identifying abnormal work types and low-efficiency constructors;
and the low-efficiency constructor optimizing module is used for analyzing the low-efficiency reasons of the low-efficiency constructors corresponding to the abnormal work types and carrying out optimized management on the low-efficiency constructors according to the low-efficiency reasons.
2. The big data based construction project human resources prediction selection system of claim 1, wherein: the number of construction staff required by the prediction target building project corresponding to various works is as follows:
extracting building types and geographical positions of buildings from the basic information, matching the building types and the geographical positions of the buildings with the building types and the geographical positions of the buildings of each historical building project in the historical building library, and screening the successfully matched historical building projects from the building types and the successfully matched geographical positions of the buildings as effective historical building projects;
extracting the planned construction volume and the planned construction time length from the basic information, extracting the construction volume and the construction time length corresponding to each effective historical building project from the historical building library, comparing the planned construction volume and the planned construction time length of the target building project with the construction volume and the construction time length corresponding to each effective historical building project, and expressing the results by the expressionCalculating the similarity eta of each effective historical building project relative to the target building project i Where i denotes the number of a valid history building project, i=1, 2, &.. i 、t i Respectively expressed as the building body quantity and the construction time length corresponding to the i effective history building project, q 0 、t 0 The planned construction volume and the planned construction time length are respectively expressed as target building projects, and e is expressed as a natural constant;
comparing the similarity of each effective historical building item relative to the target building item with a set similarity threshold value, and extracting the effective historical building items which are larger than or equal to the similarity threshold value from the similarity threshold value as standby historical building items;
extracting a start date corresponding to the standby history building project from the history building library, and combining the start date with the construction time of the standby history building project to form a construction period corresponding to the standby history building project, thereby obtaining seasons to which the construction period belongs;
extracting a planned construction date and a planned construction time from the basic information, and forming a planned construction period corresponding to the target building project, thereby obtaining seasons to which the planned construction period belongs;
comparing the seasons of the construction period corresponding to the standby historical building project with the seasons of the planning construction period corresponding to the target building project, thereby screening the standby historical building project successfully compared as a reference historical building project;
extracting the number of constructors used by various works in the construction process of a reference history building project from a history building library, and importing a calculation formulaCalculating the number of constructors required by each work corresponding to the target building project>Where j is denoted as work number, j=1, 2, &.. j d is expressed as the number of constructors used by the jth job in the construction process of the jth reference history building item, d is expressed as the number of reference history building items, d=1, 2 d Expressed as similarity of the d-th reference historical building item to the target building item.
3. The big data based construction project human resources prediction selection system of claim 1, wherein: the acquisition mode of each analysis period is as follows: when the construction of the target building project is started, the construction date is divided backwards according to the set time interval, and each analysis period is obtained.
4. The big data based construction project human resources prediction selection system of claim 1, wherein: the construction related information comprises construction days and engineering completion amount.
5. The big data based construction project human resources prediction selection system of claim 4, wherein: the specific analysis process of the construction efficiency corresponding to each work is as follows:
importing construction related information corresponding to each constructor of each work class under the current analysis period into a construction efficiency formulaCalculating the construction efficiency corresponding to each work type>In p j k represents the engineering completion amount of the kth constructor corresponding to the jth work under the current analysis period, k represents the constructor numbers corresponding to the various work, and k=1, 2, … …, w and f j And k represents the construction days of the jth work class corresponding to the kth constructor in the current analysis period.
6. The big data based construction project human resources prediction selection system of claim 1, wherein: the evaluation on whether the target building project can be finished as expected can be seen in the following procedures:
acquiring the total engineering quantity of each work corresponding to the target building project, and counting the completed engineering quantity of each work corresponding to the target building project in the current analysis period, so as to calculate the residual engineering quantity of each work;
dividing the planned construction time length of the target building project according to the work types to obtain the planned construction time length corresponding to each work type, and simultaneously counting the constructed time length corresponding to each work type of the target building project in the current analysis period, so as to calculate the residual construction time length corresponding to each work type;
calculating the engineering completion amount of the corresponding construction efficiency of each work type under the current analysis period by combining the corresponding residual construction time length of each work type with the corresponding construction efficiency of each work type;
and comparing the engineering completion amount of the construction efficiency corresponding to each work in the current analysis period with the residual engineering amount corresponding to each work, and if the engineering completion amount of the construction efficiency corresponding to a certain work in the current analysis period is smaller than the residual engineering amount corresponding to the work, judging that the target building project cannot be completed as expected.
7. The big data based construction project human resources prediction selection system of claim 6, wherein: the specific operation mode for identifying the abnormal work species is to select the work species with the engineering completion quantity smaller than the residual engineering quantity from various work species as the abnormal work species.
8. The big data based construction project human resources prediction selection system of claim 1, wherein: the specific identification process of the low-efficiency constructor is as follows:
the work attendance record and the construction record of each constructor under the current analysis period are extracted corresponding to the abnormal work types, the working time of each constructor on each construction day is extracted from the work attendance record, and the engineering completion amount of each constructor on each construction day is extracted from the construction record at the same time, so that the work attendance record is expressed by the expressionCalculating the efficiency coefficient of each constructor on each construction day;
and carrying out normal analysis on the efficiency coefficient of each constructor corresponding to the abnormal work type on each construction day to obtain the normal efficiency coefficient of each constructor corresponding to the abnormal work type, comparing the normal efficiency coefficient with the set standard efficiency coefficient, and screening constructors smaller than the standard efficiency coefficient from the normal efficiency coefficient to serve as low-efficiency constructors.
9. The big data based construction project human resources prediction selection system of claim 1, wherein: the analysis of the inefficiency reasons of the inefficiency constructors corresponding to the abnormal species is carried out by the following implementation process:
acquiring the number of the low-efficiency constructor, thereby determining the identity information of the low-efficiency constructor, and further extracting a construction monitoring video of the low-efficiency constructor in the current analysis period from the construction monitoring record;
identifying whether an abnormal construction behavior exists in the construction monitoring video by the low-efficiency constructor, if so, extracting occurrence frequency and occurrence time of the abnormal construction behavior, thereby utilizing the expressionCalculating a construction abnormality index corresponding to the low-efficiency constructor, comparing the construction abnormality index with a preset threshold, if the construction abnormality index corresponding to the low-efficiency constructor is larger than the preset threshold, predicting that the low-efficiency reason of the low-efficiency constructor is not correct in construction attitude, if the construction abnormality index corresponding to the low-efficiency constructor is smaller than or equal to the preset threshold, calling the weather state of the low-efficiency constructor on the construction day in the current analysis period from a weather platform, recognizing whether severe weather exists, if the severe weather exists, predicting that the low-efficiency reason of the low-efficiency constructor is poor in construction environment, otherwise, predicting that the low-efficiency reason of the constructor is poor in construction capability.
CN202311383598.2A 2023-10-24 2023-10-24 Building construction project manpower resource prediction selection system based on big data Pending CN117313950A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117217609A (en) * 2023-09-27 2023-12-12 中铁四局集团有限公司 Building engineering labor service provider analysis and evaluation method based on big data
CN117933733A (en) * 2024-03-25 2024-04-26 中交二公局东萌工程有限公司 Intelligent management system for planning information of building construction project
CN118395725A (en) * 2024-05-16 2024-07-26 广东中科建设工程有限公司 Engineering optimization design method driven by big data

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117217609A (en) * 2023-09-27 2023-12-12 中铁四局集团有限公司 Building engineering labor service provider analysis and evaluation method based on big data
CN117217609B (en) * 2023-09-27 2024-08-13 中铁四局集团有限公司 Building engineering labor service provider analysis and evaluation method based on big data
CN117933733A (en) * 2024-03-25 2024-04-26 中交二公局东萌工程有限公司 Intelligent management system for planning information of building construction project
CN117933733B (en) * 2024-03-25 2024-06-04 中交二公局东萌工程有限公司 Intelligent management system for planning information of building construction project
CN118395725A (en) * 2024-05-16 2024-07-26 广东中科建设工程有限公司 Engineering optimization design method driven by big data

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