A digital construction cost data evaluation and processing system and medium

Abstract

The present invention discloses a digital construction cost data evaluation and processing system and medium. The data digitization module constructs a digital cost database based on the time relationship and site relationship of the construction project data, the data analysis module analyzes the relevant data to obtain the relationship parameters, the data knowledge processing module uses the relationship parameters to perform knowledge data processing and then adds it to the digital cost database to construct a knowledge cost database, and the data intelligence module uses the data of the knowledge cost database combined with the real-time actual local cost level parameters to establish a model for intelligent cost evaluation, and finally obtains the cost evaluation score. The present invention can better evaluate the cost through information analysis and processing, thereby improving cost control, optimizing resource allocation and improving the efficiency of cost data processing, and can more efficiently and accurately realize the processing of computer cost data, realize intelligent prediction and feedback, give the best evaluation, and provide more intelligent data decision support for engineering cost.

Description

Technical Field

[0001] The invention relates to the field of computer processing of engineering cost data, and relates to a digital construction cost data evaluation processing system and medium. Background Art

[0002] With the rapid development and continuous innovation of digital technology, the digital economy has risen rapidly around the world. The country is accelerating the construction of "Digital China" and vigorously developing the digital economy. The rise of the digital economy has accelerated the progress of society and the development of business. Digitalization has become an inevitable choice for the transformation of traditional industries.

[0003] As one of the traditional industries, the construction industry is still in a state of extensive development, with backward production methods, low production efficiency and high energy and resource consumption as the prominent problems. In addition, compared with other industries, the application level of digital technology in the construction industry is still at a relatively low level, and there is an urgent need to implement the digital transformation of the construction industry.

[0004] Engineering data and cost data processing of engineering cost is an important profession in the construction field and an important part of construction management. The core means of construction is to evaluate and process the engineering cost. Improving the level of digitization and informatization of engineering cost data processing can promote the digital transformation of the construction industry. Summary of the invention

[0005] In order to solve the problems existing in the background technology, the present invention provides a digital construction cost data evaluation and processing system and medium, which performs intelligent data processing and evaluation through data digitization, information analysis, and knowledge processing.

[0006] The technical solution adopted by the present invention is:

[0007] 1. A digital construction cost assessment and processing system:

[0008] The system includes a data digitization module, a data storage module, a data analysis module, a data knowledge processing module and a data intelligence module placed in a computer.

[0009] The data digitization module is used to construct a digital cost database based on the historical and current construction project data according to the time relationship of collection and the classification relationship of the construction site;

[0010] The data analysis module analyzes the relevant data of the data digitization module to obtain the relational parameters used in the data knowledge processing module;

[0011] A data knowledge processing module uses the relationship parameters obtained by the data analysis module to perform knowledge data processing and then adds them to the digital cost database, thereby constructing a knowledge cost database;

[0012] The data intelligence module uses the data from the knowledge-based cost database combined with the real-time local cost level parameters to establish a model, conduct intelligent cost evaluation, and obtain cost evaluation scores.

[0013] Preferably, it also includes a data storage module placed in the computer, which is used to store the relevant database data obtained by the data digitization module and send it to the data analysis module.

[0014] Preferably, it also includes a data quality control module embedded in the data digitization module, which is used to perform data cleaning, deduplication and error repair on the historical construction project data in the relevant database obtained by the data digitization module to ensure the accuracy of the data. The data cleaning, deduplication and error repair are specifically as follows:

[0015] 1) Divide the construction site into non-main construction areas and main construction areas, and then remove the construction costs in the non-main construction areas from the database;

[0016] 2) Calculate the proportion of the construction cost of each major construction area to the construction cost of the construction site;

[0017] 3) Further analyze the proportion data obtained in the second step, list all the proportion data, identify outliers through the standard deviation method, eliminate the data of the main construction areas corresponding to the outliers, and finally use the box plot method to combine the proportion data of the remaining main construction areas to obtain the main construction areas under the current construction site that are greater than the preset proportion threshold.

[0018] The data digitization module specifically structures the historical and current construction project data according to the collected time and regional relationships, and performs modular processing according to the regional classification relationships of different construction sites, thereby constructing a digital cost database containing construction design data, construction site data, and cost data; the construction project data is collected online using the surveying and mapping equipment and sensors of the Internet of Things, and is classified and structured in the data digitization module according to the time and regional relationships.

[0019] The data analysis module performs hierarchical processing on the relevant data of the data digitization module according to different construction types to obtain attribute vectors of different levels, and the attribute vectors are used for subsequent accurate evaluation and correction of data.

[0020] In the data analysis module, the processing is specifically carried out in the following manner:

[0021] In view of the historical construction engineering data, the construction site is divided into different construction areas according to the different site functions according to the different construction conditions. The historical construction engineering data of different construction areas are processed separately to obtain their respective local attribute vectors, such as toilets, classrooms, offices, etc., and then the local attribute vectors of each construction area are processed simultaneously to obtain the global attribute vector of the entire construction site;

[0022] The local attribute vector includes the number of the current area, the area of ​​the current area, the coordinate position of the center of the current area on the construction plane, the numbers of the main construction method and the secondary construction method of the current area, and the construction correlation degree dnst of the current area; the construction method is the construction type.

[0023] The construction relevance dnst in the local attribute vector is calculated as:

[0024] dnst=(S cs +S ct ) / S w(cs+ct) ×P st

[0025] S w(cs+ct) =(max(cs.x max , ct.x max )- min(cs.x min , ct.x min ))×(max(cs.y max ,ct.y max )- min(cs.y min , ct.y min ))

[0026] In the formula, S cs With S ct are the areas of the current region in the main construction mode cs and the secondary construction mode ct, respectively. w(cs+ct) is the area of ​​the common bounding box of the current area in the construction plane area occupied by the main construction method and the secondary construction method: max() and min() are functions for finding the maximum and minimum values ​​respectively; cs.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct; cs.y maxIndicates the maximum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y max Indicates the maximum longitudinal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.y min Indicates the minimum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y min Indicates the minimum longitudinal coordinate of the construction plane area occupied by the current area on the secondary construction method ct; P st It represents the correlation coefficient between the main construction method cs and the secondary construction method ct;

[0027] The global attribute vector includes the total area of ​​the current construction site, the numbers of all major construction methods and all minor construction methods of the current construction site, and the construction relevance Y of the current construction site; the construction method is the construction type.

[0028] The construction relevance Y in the global attribute vector is obtained by processing the construction relevance dnst in the local attribute vector according to the following formula:

[0029] Y=Σ i (w i ×dnst i )

[0030] Among them, dnst i represents the construction association degree dnst in the local attribute vector of the i-th construction area, i=1-N, N represents the total number of construction areas, w i Represents the variable weight coefficient of each construction area, and different weight coefficients are preset for each construction area.

[0031] The knowledge-based data processing of the data knowledge processing module is to distribute the attribute vectors to the digital data corresponding to different construction areas and convert them into knowledge, and automatically update them when the construction site and engineering design change to form a self-growing knowledge base.

[0032] The data intelligence module obtains local cost level parameters based on the latest engineering cost trends, and uses the data of the knowledgeable cost database combined with the local cost level parameters actually obtained in real time to establish a factor model for cost evaluation that is affected by relationship parameters and local cost level parameters. Through technologies such as big data and artificial intelligence, intelligent cost evaluation is performed through associative intelligent quantity calculation, intelligent pricing, and intelligent material selection and pricing. Associative evaluation is performed to obtain a single cost score and an overall cost score.

[0033] In the data intelligence module, the overall site cost result is obtained by processing the construction relevance dnst updated in real time in the data knowledge processing module according to the model of the following formula:

[0034] T i =S i ×dnst i ×Mp+Rm i ×Mm

[0035] Among them, T i represents the cost assessment result of the ith area, S i represents the area of ​​the i-th construction area, i=1-N, N represents the total number of construction areas, Mp represents the local cost level parameter, Rm i represents the total number of people accommodated in the i-th construction area, and Mm represents the unit cost parameter;

[0036] The overall site cost result is obtained by processing the construction correlation degree dnst updated in real time in the data knowledge processing module according to the model of the following formula:

[0037] T=(Σ i (S i ×dnst i ))×Mp+Rm×Mm

[0038] Among them, T represents the cost assessment result of the entire construction site, S i It represents the area of ​​the i-th construction area, i=1-N, N represents the total number of construction areas, Mp represents the local cost level parameter, Rm represents the total number of people accommodated in the construction site, and Mm represents the unit cost parameter.

[0039] 2. A computer storage and processing medium:

[0040] at least one processor; and

[0041] A memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the above method.

[0042] The innovation of the present invention is to use digital, knowledge-based and intelligent data processing, and introduce the consideration of the internal relationship between construction methods, and then refine the local relationship and mutual relationship within each construction area, so as to enable faster and more efficient intelligent evaluation.

[0043] The beneficial effects of the present invention are:

[0044] The present invention can better evaluate the cost through information analysis and processing, thereby improving cost control, optimizing resource allocation and improving the efficiency of cost data processing, and can realize computer cost data processing more efficiently and accurately.

[0045] The decision support system based on the knowledge base and intelligent algorithm of the present invention can make more accurate, efficient and reliable decisions. It also combines the analysis results of the data analysis module and the results of the data knowledge processing module to make intelligent predictions and real-time feedback, give the best evaluation, and provide more intelligent data decision support for engineering cost.

[0046] In summary, the solution of the present invention includes four stages from data digitization, information analysis, knowledge processing to intelligent processing. The four stages complement each other and can be continuously iterated. The iterative process helps to continuously accumulate knowledge and wisdom to support continuous improvement and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a connection block diagram of each module of the present invention.

[0048] Figure 2 It is a hierarchical logical relationship diagram of the four major modules of the present invention. DETAILED DESCRIPTION

[0049] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] Embodiments of the present invention are as follows:

[0051] Embodiment For the cost engineering construction of Hope Primary School, after establishing the engineering construction design, a computer program such as Figure 1 The data digitization module, data storage module, data analysis module, data knowledge processing module and data intelligence module of the relationship shown in the figure realize the following Figure 2 The data digitization, data analysis, data knowledge and data intelligence are processed in sequence. Figure 1 As shown, control each module according to the following processing:

[0052] A. The data digitization module constructs a digital cost database based on the time relationship of historical construction project data and the classification relationship of construction sites and regions; and at the same time, the construction project data of the current construction site is also added to the digital cost database based on the time relationship of collection and the classification relationship of construction sites and regions. Specifically, all sample data can be entered in a fixed standard format (including standard format list, standard format configuration data, standard format construction process data, standard format brand data, standard format cost data, etc.).

[0053] The data digitization module specifically processes the historical and current construction project data in a structured manner according to the time and regional relationships of the collection, and performs modular processing according to the regional classification relationships of different construction sites and the cost relationships of different engineering stages, thereby achieving digitization and building a digital cost database containing construction design data, construction site data, and cost data;

[0054] Construction project data can be collected online using surveying and mapping equipment and sensors of the Internet of Things, and classified and structured data processed in the data digitization module according to time and regional relationships.

[0055] The specific construction project data includes construction design data, construction site data, cost data, etc., but is not limited to these.

[0056] Data digitization makes data visible, applicable, and empowering, which is conducive to timely understanding of the project situation and finding problems in the project in the later stage, and making corresponding adjustments within a reasonable time, which can reduce resource consumption, save costs, and ensure the smooth progress of the project.

[0057] B. The relevant database data obtained by the data digitization module is stored in the data storage module in the computer, which can be subsequently sent to the data analysis module, the data knowledge processing module, the data intelligence module and so on.

[0058] C. In the specific implementation, a data quality control module is also set up which is embedded in the data digitization module to perform data cleaning, deduplication and error repair on the historical construction project data obtained by the data digitization module and stored in the relevant database to ensure the accuracy of the data.

[0059] The purpose of the data quality control module is to find and clean up the data with large deviations through indicator comparison and analysis after the construction sample data of Hope Primary School cost is digitized.

[0060] In the embodiment, after completing the data digitization in the first step for the built Hope Primary School, the second step of quality control processing is carried out. The data cleaning, deduplication and error repair are specifically as follows:

[0061] 1. Screen out schools with construction areas outside the eight major construction areas, and exclude the construction costs (including furniture costs) of other construction areas outside the eight major construction areas of the school from the total construction costs (including furniture costs) of the school.

[0062] All the construction areas that have been built are summarized as follows: student dormitories, teacher dormitories, public washrooms, public showers, public corridors, activity rooms, restaurants, public toilets, kitchens, and drying areas. Through repeated inspections, it was found that each built Hope Primary School includes the following eight major construction areas: student dormitories, teacher dormitories, public washrooms, public showers, public corridors, activity rooms, public toilets, and drying areas.

[0063] 2. Calculate the proportion of the construction cost (including furniture cost) of the above eight major construction areas in each school to the total construction cost of the school (excluding data outside the eight major construction areas).

[0064] 3. Further analyze the percentage data obtained in the second step, list the percentage data of the construction area construction cost (including furniture cost) of all schools in the same construction area to the total construction cost (including furniture cost) of the school, identify outliers through the standard deviation method, remove the outliers, and use the box plot method to combine the remaining proportion data of each major construction area to obtain the main construction area under the current construction site that is greater than the preset proportion threshold as the better data.

[0065] D. Then, the construction engineering data of the current construction site processed by the data quality control module and stored in the data storage module is sent to the data analysis module for processing.

[0066] The data analysis module is for the relevant data of the data digitization module. According to the time-series activities in progress of different construction types, it performs hierarchical processing to obtain attribute vectors of different levels. The attribute vectors are used for subsequent data correction.

[0067] The data analysis module needs to conduct information analysis, which is to analyze the data, analyze the trend of project cost and the records of related activities in the project, establish a digital model for prediction and evaluation, and obtain attribute vectors that can be used to accurately reflect the classification probability of each level. It is used to correct the knowledge and intelligent processing, realize the management and control of knowledge data, and finally provide a scientific basis for cost evaluation.

[0068] The data analysis module uses data mining, dynamic analysis of the relationship between construction and site, and cost factors to visualize the analysis results in the form of attribute vectors. The actual presentation can help discover potential problems and optimization space in production cost control in different regions and different construction methods.

[0069] Only through information analysis and prediction can we better specify cost control, optimize resource allocation and improve the efficiency of cost data processing.

[0070] In the data analysis module, the specific processing is as follows:

[0071] According to the historical construction project data, the construction site is divided into different construction areas according to the different site functions based on the different construction conditions. The historical construction project data of different construction areas are processed separately to obtain their respective local attribute vectors, and then the local attribute vectors of each construction area are integrated at the same time to obtain the global attribute vector of the entire construction site.

[0072] The local attribute vector includes the number of the current area, the area of ​​the current area, the coordinate position of the center of the current area on the construction plane, the numbers of the main construction method and the secondary construction method of the current area, and the construction correlation degree dnst of the current area;

[0073] The construction relevance dnst in the local attribute vector is calculated as:

[0074] dnst=(S cs +S ct ) / S w(cs+ct) ×P st

[0075] S w(cs+ct) =(max(cs.x max , ct.x max )- min(cs.x min , ct.x min ))×(max(cs.y max ,ct.y max )- min(cs.y min , ct.y min ))

[0076] In the formula, S cs With S ct are the areas of the current region in the main construction mode cs and the secondary construction mode ct, respectively. w(cs+ct) is the area of ​​the common bounding box of the current area in the construction plane area occupied by the main construction method and the secondary construction method: max() and min() are functions for finding the maximum and minimum values ​​respectively; cs.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct; cs.y max Indicates the maximum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y maxIndicates the maximum longitudinal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.y min Indicates the minimum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y min Indicates the minimum longitudinal coordinate of the construction plane area occupied by the current area on the secondary construction method ct; P st It represents the correlation coefficient between the main construction method cs and the secondary construction method ct, which is related to the construction type and construction materials. This parameter is a preset parameter between the two construction methods, indicating the correlation of construction costs between the main construction method cs and the secondary construction method ct.

[0077] The above-mentioned construction plane area of ​​the present invention may be all planes of the construction area, and may include all planes such as ground surfaces and wall surfaces after being flattened in the construction area.

[0078] When establishing the relationship between the main construction method CS and the secondary construction method CT, the cost relationship between the main construction method CS and the secondary construction method CT in terms of construction work types (such as plastering, carpentry, plumbing and electrical work) and construction materials (such as plates, metal parts, accessories, construction tools, etc.) is taken into consideration, and then the local cost relationship within a single construction area is refined, which enables faster and more efficient cost evaluation.

[0079] The global attribute vector includes the total area of ​​the current construction site, the numbers of all major construction methods and all minor construction methods of the current construction site, and the construction relevance Y of the current construction site; the construction method is the construction type.

[0080] The construction relevance Y in the global attribute vector is obtained by processing the construction relevance dnst in the local attribute vector according to the following formula:

[0081] Y=Σ i (w i ×dnst i )

[0082] Among them, dnst i represents the construction association degree dnst in the local attribute vector of the i-th construction area, i=1-N, N represents the total number of construction areas, w i Represents the variable weight coefficient of each construction area, and different weight coefficients are preset for each construction area.

[0083] In the specific implementation, the benchmark construction area configuration of the Hope Primary School can be established, and then the construction work types, construction processes, construction materials, construction costs, etc. can be allocated. Specifically, the following construction area configuration can be obtained:

[0084] E. The knowledge-based data processing module distributes attribute vectors to digital data corresponding to different construction areas and converts them into knowledge through technologies such as machine learning and natural language processing. It automatically updates when the construction site and engineering design change, forming a self-growing knowledge base.

[0085] The data knowledge processing module is based on the understanding and analysis of the acquired data by the data analysis module, obtains guiding parameters of cost experience and insights, summarizes the professional knowledge and experience in the field of engineering cost into refined characterization parameters and integrates them into the actual engineering data, thereby establishing a complete knowledge system, and then coordinating comprehensive and systematic data management and processing, aiming to improve the efficiency of the project and the level of data processing.

[0086] The data obtained through knowledge-based processing can be easily circulated and knowledge can be shared, thus meeting the needs of multiple parties.

[0087] F. The data intelligence module obtains local cost level parameters based on the latest engineering cost trends, and uses the data of the knowledge-based cost database combined with the local cost level parameters actually obtained in real time to establish a factor model for cost evaluation that is affected by relationship parameters and local cost level parameters. Through technologies such as big data and artificial intelligence, it conducts intelligent cost evaluation of correlation intelligent quantity calculation, intelligent pricing, and intelligent material selection and pricing, and conducts correlation evaluation to obtain a single cost score and an overall cost score.

[0088] In the data intelligence module, the overall site cost result is obtained by processing according to the construction correlation degree dnst updated in real time in the data knowledge processing module, and the overall site cost result is obtained by processing according to the construction correlation degree dnst updated in real time in the data knowledge processing module, and T i =S i ×dnst i ×Mp+Rm i ×Mm,T=(Σ i (S i ×dnst i ))×Mp+Rm×Mm.

[0089] Thus, through the implementation of the above embodiments, it can be seen that the present invention constructs a digital cost system for engineering construction at the data, information, knowledge and wisdom levels, such as Figure 2 As shown, it demonstrates how data is gradually transformed into information and knowledge, explores the differences between construction methods in different construction areas, establishes the inherent data processing relationship of engineering digital cost, and finally achieves real-time intelligent update processing during the construction process.

Claims

1. A digital construction cost assessment and processing system, characterized in that: It includes a data digitization module, a data storage module, a data analysis module, a data knowledge processing module and a data intelligence module placed in the computer; The data digitization module is used to construct a digital cost database based on the time relationship of the construction project data collected and the classification relationship of the construction site; The data analysis module analyzes the relevant data of the data digitization module to obtain the relational parameters used in the data knowledge processing module; In the data analysis module, the processing is specifically carried out in the following manner: According to the historical construction project data, the construction site is divided into different construction areas according to the different site functions according to the different construction conditions. The historical construction project data of different construction areas are processed separately to obtain their respective local attribute vectors, and then the local attribute vectors of each construction area are processed simultaneously to obtain the global attribute vector of the entire construction site; The local attribute vector includes the number of the current area, the area of ​​the current area, the coordinate position of the center of the current area on the construction plane, the numbers of the main construction method and the secondary construction method of the current area, and the construction correlation degree dnst of the current area; The construction relevance dnst in the local attribute vector is calculated as: dnst=(S cs +S ct ) / S w(cs+ct) ×P st S w(cs+ct) =(max(cs.x max ,ct.x max )-min(cs.x min ,ct.x min ))×(max(cs.y max ,ct.y max )- min(cs.y min ,ct.y min )) In the formula, S cs With S ct are the areas of the current region in the main construction mode cs and the secondary construction mode ct, respectively. w(cs+ct) is the area of ​​the common bounding box of the current area in the construction plane area occupied by the main construction method and the secondary construction method: max() and min() are functions for finding the maximum and minimum values ​​respectively; cs.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x max Indicates the maximum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area in the main construction method, ct.x min Indicates the minimum horizontal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct; cs.y max Indicates the maximum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y max Indicates the maximum longitudinal coordinate value of the construction plane area occupied by the current area on the secondary construction method ct, cs.y min Indicates the minimum vertical coordinate value of the construction plane area occupied by the current area in the main construction method, ct.y min Indicates the minimum longitudinal coordinate of the construction plane area occupied by the current area on the secondary construction method ct; P st It represents the correlation coefficient between the main construction method cs and the secondary construction method ct; The global attribute vector includes the total area of ​​the current construction site, the numbers of all major construction methods and all minor construction methods of the current construction site, and the construction correlation Y of the current construction site; the construction correlation Y in the global attribute vector is obtained by processing the construction correlation dnst in the local attribute vector according to the following formula: Y=S i (w i ×dnst i ) Among them, dnst i represents the construction association degree dnst in the local attribute vector of the i-th construction area, i = 1 to N, i represents the sequence number of the construction area, N represents the total number of construction areas, w i Represents the variable weight coefficient of each construction area, and different weight coefficients are preset for each construction area; A data knowledge processing module uses the relationship parameters obtained by the data analysis module to perform knowledge data processing and then adds them to the digital cost database, thereby constructing a knowledge cost database; The knowledge data processing of the data knowledge processing module is to distribute the attribute vectors to the digital data corresponding to different construction areas and convert them into knowledge, and automatically update them when the construction site and engineering design change, forming a self-growing knowledge base; The data intelligence module uses the data from the knowledge-based cost database combined with the local cost level parameters actually obtained in real time to establish a model, conduct intelligent cost evaluation, and obtain cost evaluation scores; The data intelligence module uses the data of the knowledgeable cost database combined with the local cost level parameters actually obtained in real time to establish a factor model affected by the relationship parameters and the local cost level parameters, conducts a correlation intelligent cost evaluation, and obtains a single cost score and an overall cost score; In the data intelligence module, the overall site cost result is obtained by processing the construction relevance dnst updated in real time in the data knowledge processing module according to the model of the following formula: T i =S i ×dnst i ×Mp+Rm i ×Mm Among them, T i represents the cost assessment result of the ith area, S i represents the area of ​​the i-th construction area, i = 1 to N, i represents the serial number of the construction area, N represents the total number of construction areas, Mp represents the local cost level parameter, Rm i represents the total number of people accommodated in the i-th construction area, and Mm represents the unit cost parameter; The overall site cost result is obtained by processing the construction correlation degree dnst updated in real time in the data knowledge processing module according to the model of the following formula: T=(Σ i (S i ×dnst i ))×Mp+Rm×Mm Among them, T represents the cost assessment result of the entire construction site, S i It represents the area of ​​the i-th construction area, i=1 to N, i represents the serial number of the construction area, N represents the total number of construction areas, Mp represents the local cost level parameter, Rm represents the total number of people accommodated in the construction site, and Mm represents the cost parameter per unit number of people.

2. A digital construction cost assessment and processing system according to claim 1, characterized in that: It also includes a data storage module placed in the computer, which is used to store the relevant data obtained by the data digitization module and send it to the data analysis module.

3. A digital construction cost assessment and processing system according to claim 1, characterized in that: It also includes a data quality control module embedded in the data digitization module, which is used to perform data cleaning, deduplication and error repair on the historical construction project data obtained by the data digitization module. The data cleaning, deduplication and error repair are specifically as follows: 1) Divide the construction site into non-main construction areas and main construction areas, and then eliminate the construction costs in the non-main construction areas; 2) Calculate the proportion of the construction cost of each major construction area to the construction cost of the construction site; 3) Further analyze the proportion data obtained in the second step, list all the proportion data, identify outliers through the standard deviation method, eliminate the data of the main construction areas corresponding to the outliers, and finally obtain the main construction areas under the current construction site that are greater than the preset proportion threshold by combining the remaining proportion data of each main construction area through the box plot method.

4. A digital construction cost assessment processing system according to claim 1, characterized in that: The data digitization module specifically structures the historical and current construction project data according to the collected time and regional relationships, and performs modular processing according to the regional classification relationships of different construction sites, thereby constructing a digital cost database containing construction design data, construction site data, and cost data; the construction project data is collected online using the surveying and mapping equipment and sensors of the Internet of Things, and is classified and structured in the data digitization module according to the time and regional relationships.

5. A digital construction cost evaluation and processing system according to claim 1, characterized in that: The data analysis module performs hierarchical processing on the relevant data of the data digitization module according to different construction types to obtain attribute vectors of different levels.

6. A computer storage and processing medium, characterized in that at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the system according to any one of claims 1 to 5.

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