Bill of quantity comprehensive unit price rationality detection method and system

Abstract

The invention discloses an engineering quantity list comprehensive unit price rationality detection method and system, and belongs to the technical field of engineering cost. The invention discloses a bill of quantity comprehensive unit price rationality detection method and system. The method comprises the steps of extracting key factor features; obtaining a comprehensive unit price corresponding to the project name; constructing a project recognition library; s4, correcting and perfecting the prices of the abnormal items; calculating the comprehensive unit price of the new engineering project; the system comprises a unit price calculation module, a database construction module, a comprehensive unit price identification module and a new engineering project determination module. The problem that the comprehensive unit price of the new engineering project cannot be determined in the prior art is solved, the comprehensive unit price of the new engineering project can be calculated, pricing dispute caused by fuzzy feature description of the new engineering project can be reduced, the abnormal quotation can be effectively identified, and by correcting the abnormal quotation deviating from the rationality interval, the pricing efficiency of the new engineering project is improved. The construction period delay or claim risk caused by pricing errors can be reduced.

Description

Technical Field

[0001] This invention relates to the field of engineering cost technology, specifically to a method and system for detecting the rationality of the comprehensive unit price in a bill of quantities. Background Technology

[0002] The existing methods for reviewing the comprehensive unit price of a bill of quantities mainly include the inquiry and verification method, the drawing verification method, and the invitation and negotiation method. The current status of each method is as follows: The inquiry and verification method mainly verifies the prices of the bill of quantities (materials, equipment, and labor) through various means such as inquiring about market prices, consultation prices, and suppliers, to ensure their rationality and accuracy; the drawing verification method mainly calculates the quantities of work based on the construction drawings to determine whether there are any errors or unreasonable aspects, thereby reviewing the comprehensive unit price; the invitation and negotiation method mainly invites suppliers, contractors, and consulting units to participate in the joint consultation to determine whether the comprehensive unit price is reasonable.

[0003] Chinese patent CN117575158A discloses a method, device, and equipment for determining the reasonableness of comprehensive unit prices in engineering bills of quantities. This method involves establishing an engineering cost index database; parsing user-uploaded pricing documents to obtain engineering bills of quantities and corresponding comprehensive unit price tables; matching engineering bills of quantities in pricing documents with similar types based on preset screening conditions according to the engineering cost index database and processing them to obtain corresponding unit price ranges; comparing each comprehensive unit price in the comprehensive unit price table with the unit price range; judging the comprehensive unit price as reasonable if it falls within the range, and judging it as unreasonable if it does not, and outputting an abnormal engineering bill of quantities. This enables comprehensive management and analysis of engineering cost data, improves the efficiency and accuracy of engineering cost management, provides relevant departments with a basis for review and comparison, broadens the service area for the cost industry, effectively solves problems such as cost overruns, disputes, and project delays, and ensures smooth project implementation and effective cost control.

[0004] In practical use, the aforementioned patent applications fail to meet current needs when new engineering projects arise due to the lack of corresponding price standards, making it difficult to determine the reasonableness of the comprehensive unit price and consequently, the comprehensive unit price for new engineering projects cannot be determined. Therefore, we propose a method and system for detecting the reasonableness of the comprehensive unit price in the bill of quantities. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for detecting the reasonableness of the comprehensive unit price in a bill of quantities, enabling rapid adaptation to new engineering projects and avoiding the lag of traditional manual review. It generates a reasonableness range for the comprehensive unit price of new engineering projects using historical data, providing a quantitative basis for decision-making. This reduces pricing disputes caused by ambiguous descriptions of new engineering project features. The automatic comparison of quoted prices with the reasonableness range effectively identifies abnormal quotes, allowing for early detection of omissions in the bill of quantities and deviations in feature descriptions, thus avoiding settlement disputes due to pricing errors. By correcting abnormal quotes that deviate from the reasonableness range, it reduces the risk of project delays or claims due to pricing errors. The automatic generation of a comprehensive unit price analysis table through correction records clarifies the cost composition and adjustment basis, thus solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for detecting the reasonableness of the comprehensive unit price in a bill of quantities, comprising the following steps: Collect relevant data for the engineering project, perform data cleaning, and extract key factor features after cleaning; The price range for relevant items in the project is calculated using the pricing documents to obtain the comprehensive unit price corresponding to the item name; Build a project identification library and store the calculated project-related data according to templates such as project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source; After the project identification library is built, the projects in the project identification library are scanned, and projects with pricing abnormalities are quickly identified. When a project with pricing abnormalities is identified, the project pricing is corrected and improved. When a new project is encountered during the scanning process, its features are extracted and compared with historical related project data to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the project is stored in the project identification library.

[0007] Preferably, relevant data for the engineering project is collected and cleaned. After cleaning, key factor features are extracted, including: Collect relevant data for the project, including bill of quantities, pricing documents, quota information, and personnel, material, and equipment information; Preprocessing of project-related data includes: cleaning project-related data, preprocessing missing and outlier values ​​in project-related data, removing irrelevant noise, improving the data quality of multi-source business data, and standardizing measurement units. After the cleaning is completed, key factor features are extracted, including project name, project characteristics, unit of measurement, region, contract type, and project source.

[0008] Preferably, after calculation, the relevant data of the project are stored according to templates for project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source, including: The project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source are fixed into a template. The project characteristics include the project materials and project processes corresponding to the project name. Fill in the template with the calculated comprehensive unit price corresponding to the project name and the extracted key factor features; Save the completed template, lock the key fields, and use standardized coding for the project.

[0009] Preferably, after the project identification library is built, the projects in the library are scanned, and projects with pricing anomalies are quickly identified. When a project with pricing anomalies is identified, the pricing of the project is corrected and improved, specifically including: After the project identification library is built, the reasonable range of historical comprehensive unit prices is calculated, and then the projects in the project identification library are scanned. The comprehensive unit price of the project in the project identification database is compared with the reasonable range to determine whether the comprehensive unit price of the project exceeds the reasonable range. When the comprehensive unit price of a project exceeds the reasonable range, the comprehensive unit price of the project shall be revised and improved.

[0010] Preferably, the reasonable range for calculating the historical comprehensive unit price specifically includes: Extract the historical comprehensive unit price of similar lists and verify the historical comprehensive unit price using the normal distribution method; It also determines whether there is any abnormal data in the historical comprehensive unit price. If there is abnormal data, it removes the abnormal data until there is no abnormal data. After the exclusion is completed, the reasonable range of historical comprehensive unit prices is calculated, and the comprehensive unit prices of projects that exceed the reasonable range are marked as abnormal.

[0011] Preferably, the comprehensive unit price of projects that exceeds the reasonable range is marked as abnormal: Abnormal unit prices exceeding the highest threshold of the reasonable range are marked in red, and those below the lowest threshold of the reasonable range are marked in green. Output a list of abnormal items with composite unit prices, including the abnormal list code, item characteristics, unit of measurement, composite unit price, confidence interval for comparison, and deviation rate.

[0012] Preferably, when a new project is encountered during the scanning process, the features of the new project are extracted, and these features are compared with historical related project data to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the project is stored in the project identification database. Specifically, this includes: When a new project is encountered during the scanning process, relevant features of the new project are extracted, and the relevant features are used to search in the project identification database. When relevant features are retrieved from the project identification database, the random forest algorithm is used for statistical classification analysis. The engineering projects related to the new engineering project are classified according to price, project name, project materials corresponding to the project name, and project process; Identify historical engineering project data that closely matches the new engineering project, use the historical engineering project data to predict the cost of the new engineering project, and generate the actual cost of the new engineering project. A deviation analysis was performed on the unit price of the new project, and the index weights were adjusted according to the analysis results to obtain the comprehensive unit price of the new project. Match the unit price of the new project to the corresponding project code, project name, project characteristics, unit of measurement, region, contract type and project source, and store it in the project identification database.

[0013] Preferred methods for constructing the project identification library include: Obtain historical project datasets and extract features to obtain project features; Project characteristics are stratified and classified based on industry type to generate a project characteristic classification standard table; the classification standard table defines project characteristic coding rules, mapping each project characteristic to a unique characteristic code; Extract data corresponding to project characteristics, region, and contract type from the historical project contribution event database as the first data; Calculate the contribution value of the first data and the average unit price of the region corresponding to the combination of project characteristics, region, and contract type; Obtain the expert evaluation values ​​of the industry expert evaluation node set for the combination of project characteristics, region, and contract type; The basic value of the project characteristics-region-contract type combination is calculated based on the contribution value and expert evaluation value of the combination. Real-time regional economic correction coefficients are obtained from the national regional economic index platform. The final value of the project characteristics-region-contract type combination is calculated based on the basic value of the combination and the real-time regional economic correction coefficient. Obtain the average unit price for the region; Calculate the reference unit price of the project characteristics-region-contract type combination based on the final value of the combination and the average unit price of the region; A correlation table is constructed using project feature code, region code, contract type code, basic value, correction coefficient, final value, reference unit price, and update timestamp as core fields to obtain a correlation database of project features, region, and contract value. The system pre-defines six major conflict scenarios: code-name conflict, feature-unit price conflict, contract type-unit of measurement conflict, data source-parameter conflict, cross-time parameter conflict, and region-unit price logic conflict. Construct a three-axis data system; the three-axis data system includes a project code-time-parameter time axis constructed according to the entry timestamp, a project feature-region-parameter region axis constructed according to the project region code, and a field axis constructed according to the field-related field of the project data field; Calculate the degree of difference in the combination of project characteristics, region, and contract type; Introduce a time decay coefficient and a regional weight; The conflict value of the project characteristics-region-contract type combination is calculated based on the difference degree, time decay coefficient and regional weight of the project characteristics-region-contract type combination. Conflict levels are determined based on conflict values; The project data conflict intelligent judgment library is obtained by using the combination coding of project characteristics, region, and contract type, conflict type, three-axis coordinates, difference degree, conflict value, and conflict level as a control group. A project identification database is constructed based on a project characteristics-region-contract value association database and a project data conflict intelligent judgment database.

[0014] Preferably, before storing the project-related data after the calculation is completed, the method further includes: calculating the comprehensive unit price rationality assessment value of the project-related data, and storing the project-related data when the assessment value is determined to be greater than or equal to a preset assessment threshold. The comprehensive unit price reasonableness assessment value of the calculation project-related data includes: The environmental impact coefficient of a project is determined based on project type data from relevant engineering project data. Based on the project's pre-set basic rationality score and environmental impact coefficient, the first evaluation value of the project is determined. Obtain the absolute deviation values ​​of core elements and non-core elements of the relevant data of the engineering project and the preset benchmark data of the engineering project. The amplification factor of the absolute deviation value of the core element is determined based on the sum of the absolute deviation values ​​of the non-core elements and a preset constant. The second evaluation value of the project is determined based on the absolute deviation value and amplification factor of the core elements of the project-related data. The influence coefficient of each non-core element in the acquisition of relevant data for engineering projects and the influence coefficient of non-core elements on rationality; The third evaluation value of the project is determined based on the influence coefficient and impact factor of each non-core element. Based on the first, second, and third evaluation values ​​of the project, determine the comprehensive unit price rationality assessment value of the relevant data of the project.

[0015] The bill of quantities unit price rationality testing system, applied in the bill of quantities unit price rationality testing methods, includes: The unit price calculation module is used to collect relevant data of engineering projects, preprocess the relevant data, extract key factor features after cleaning, and use the pricing file to calculate the price range of relevant items of the project to obtain the comprehensive unit price corresponding to the project name. The database construction module is used to build a project identification library. It fills the template with the comprehensive unit price corresponding to the calculated project name and the extracted key factor features, stores the filled template, locks the key fields, and uniformly encodes the projects. The comprehensive unit price identification module is used to calculate the reasonable range of historical comprehensive unit prices. After the calculation is completed, it scans the projects in the project identification database, compares the comprehensive unit price of the projects in the project identification database with the reasonable range, and determines whether the comprehensive unit price of the project exceeds the reasonable range. The new project identification module is used to extract relevant features from new projects during the scanning process, identify historical project data that closely matches the new projects, and use the historical project data to calculate and store the comprehensive unit price of the new projects.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention extracts the features of new engineering projects and performs similar feature retrieval in the project identification database. Based on project code, project name, project features, unit of measurement, comprehensive unit price, project region, contract type, and project source dynamic configuration list template, it achieves rapid adaptation of new engineering projects, avoiding the lag of traditional manual review. It generates a reasonable range of comprehensive unit price for new engineering projects through historical data, providing a quantitative basis for decision-making and reducing pricing disputes caused by ambiguous descriptions of new engineering project features. 2. This invention can effectively identify abnormal quotations by automatically comparing them with reasonable ranges. It can detect omissions in the bill of quantities and deviations in feature descriptions in advance, avoiding settlement disputes caused by pricing errors. By correcting abnormal quotations that deviate from reasonable ranges, it can reduce the risk of project delays or claims caused by pricing errors. By automatically generating a comprehensive unit price analysis table through correction records, it clarifies the cost composition and adjustment basis. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method for detecting the rationality of the comprehensive unit price in the bill of quantities according to the present invention; Figure 2 This is a block diagram of the bill of quantities unit price rationality detection system of the present invention; Figure 3 This invention provides a process for determining the comprehensive unit price of a new engineering project. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To address the problem that existing technologies struggle to determine the reasonableness of unit prices for new engineering projects due to the lack of corresponding price standards, thus hindering the determination of unit prices for these projects, please refer to [link to relevant documentation]. Figures 1-3 This embodiment provides the following technical solution: The method for testing the reasonableness of the comprehensive unit price in the bill of quantities includes the following steps: Collect relevant data for the engineering project, perform data cleaning, and extract key factor features after cleaning; The price range for relevant items in the project is calculated using the pricing documents to obtain the comprehensive unit price corresponding to the item name; Build a project identification library and store the calculated project-related data according to templates such as project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source; After the project identification library is built, the projects in the project identification library are scanned, and projects with pricing abnormalities are quickly identified. When a project with pricing abnormalities is identified, the project pricing is corrected and improved. When a new project is encountered during the scanning process, its features are extracted and compared with historical related project data to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the project is stored in the project identification library.

[0020] Collect relevant data for the engineering project, perform data cleaning, and extract key feature characteristics after cleaning, including: Collect relevant data for the project, including bill of quantities, pricing documents, quota information, and information on personnel, materials, and machinery.

[0021] Preprocessing of project-related data includes: cleaning project-related data, preprocessing missing and outlier values ​​in project-related data, removing irrelevant noise, improving the data quality of multi-source business data, and standardizing measurement units. After the cleaning is completed, key factor features are extracted, including project name, project characteristics, unit of measurement, region, contract type, and project source.

[0022] After calculation, the relevant project data will be stored according to templates for project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source. Specifically, this includes: The project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source are fixed into a template to ensure that the level and scope of the list items are the same no matter who does the project. Employees can only fill in the blanks and cannot change the structure to prevent different scopes for the same project. Fill in the template with the calculated comprehensive unit price corresponding to the project name and the extracted key factor features; The completed templates are stored, and key fields are locked and projects are uniformly coded so that employees can only fill in the blanks in the templates and cannot modify them, thus avoiding different interpretations for the same project. Project characteristics include: the project materials corresponding to the project name and the project process.

[0023] After the project identification library is built, the projects in the library are scanned, and projects with pricing anomalies are quickly identified. When a project with pricing anomalies is identified, its pricing is corrected and improved, specifically including: After the project identification library is built, the reasonable range of historical comprehensive unit prices is calculated, and then the projects in the project identification library are scanned. The comprehensive unit price of the project in the project identification database is compared with the reasonable range to determine whether the comprehensive unit price of the project exceeds the reasonable range. When the comprehensive unit price of a project exceeds the reasonable range, the comprehensive unit price of the project shall be revised and improved.

[0024] By establishing an automatic screening mechanism for abnormal pricing in the project identification database, omissions in the bill of quantities and deviations in feature descriptions can be detected in advance, avoiding settlement disputes caused by pricing errors. By correcting abnormal quotations that deviate from the reasonable range, the risk of project delays or claims caused by pricing errors can be reduced. By automatically generating a comprehensive unit price analysis table through correction records, the cost composition and adjustment basis can be clearly defined.

[0025] The calculation of the reasonable range for historical composite unit prices specifically includes: Extract the historical comprehensive unit price of similar lists and verify the historical comprehensive unit price using the normal distribution method; It also determines whether there is any abnormal data in the historical comprehensive unit price. If there is abnormal data, it removes the abnormal data until there is no abnormal data. After the exclusion is completed, the reasonable range of historical comprehensive unit prices is calculated, and the comprehensive unit prices of projects that exceed the reasonable range are marked as abnormal.

[0026] Projects with unit prices exceeding the reasonable range will be marked as abnormal, specifically including: Abnormal unit prices exceeding the highest threshold of the reasonable range are marked in red, and those below the lowest threshold of the reasonable range are marked in green. Output a list of abnormal items with composite unit prices, including the abnormal list code, item characteristics, unit of measurement, composite unit price, confidence interval for comparison, and deviation rate.

[0027] When a new project is encountered during the scanning process, its features are extracted and compared with historical data of related projects to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the results are stored in the project identification database. Specifically, this includes: When a new project is encountered during the scanning process, relevant features of the new project are extracted, and the relevant features are used to search in the project identification database. When relevant features are retrieved from the project identification database, the random forest algorithm is used for statistical classification analysis. The engineering projects related to the new engineering project are classified according to price, project name, project materials corresponding to the project name, and project process; Identify historical engineering project data that closely matches the new engineering project, use the historical engineering project data to predict the cost of the new engineering project, and generate the actual cost of the new engineering project. A deviation analysis was performed on the unit price of the new project, and the index weights were adjusted according to the analysis results to obtain the comprehensive unit price of the new project. Match the unit price of the new project to the corresponding project code, project name, project characteristics, unit of measurement, region, contract type and project source, and store it in the project identification database.

[0028] By extracting the characteristics of new engineering projects and searching for similar features in the project identification database, and based on project codes, project names, project characteristics, units of measurement, comprehensive unit prices, project regions, contract types, and project source dynamic configuration list templates, the system enables rapid adaptation of new engineering projects, avoiding the lag of traditional manual review. This is particularly suitable for emerging engineering fields with complex technologies or frequent design changes. Cluster analysis technology is used to identify key influencing factors, such as material price fluctuations and differences in construction techniques. Historical data is used to generate a reasonable range for the comprehensive unit price of new engineering projects, providing a quantitative basis for decision-making. Through standardized testing processes, pricing disputes caused by ambiguous descriptions of new engineering project characteristics can be reduced. The function of automatically comparing quotations with reasonable ranges can effectively identify abnormal quotations, assisting both the contracting parties in reaching a risk-sharing agreement during the bidding stage.

[0029] The bill of quantities unit price rationality testing system, applied in the bill of quantities unit price rationality testing methods, includes: The unit price calculation module is used to collect relevant data of engineering projects, preprocess the relevant data, extract key factor features after cleaning, and use the pricing file to calculate the price range of relevant items of the project to obtain the comprehensive unit price corresponding to the project name. The database construction module is used to build a project identification library. It fills the template with the comprehensive unit price corresponding to the calculated project name and the extracted key factor features, stores the filled template, locks the key fields, and uniformly encodes the projects. The comprehensive unit price identification module is used to calculate the reasonable range of historical comprehensive unit prices. After the calculation is completed, it scans the projects in the project identification database, compares the comprehensive unit price of the projects in the project identification database with the reasonable range, and determines whether the comprehensive unit price of the project exceeds the reasonable range. The new project identification module is used to extract relevant features from new projects during the scanning process, identify historical project data that closely matches the new projects, and use the historical project data to calculate and store the comprehensive unit price of the new projects.

[0030] The methods for building a project identification library include: Obtain historical project datasets and extract features to obtain project features; Project characteristics are stratified and classified based on industry type to generate a project characteristic classification standard table; the classification standard table defines project characteristic coding rules, mapping each project characteristic to a unique characteristic code; Extract data corresponding to project characteristics, region, and contract type from the historical project contribution event database as the first data; Calculate the contribution value of the first data and the average unit price of the region corresponding to the combination of project characteristics, region, and contract type; Obtain the expert evaluation values ​​of the industry expert evaluation node set for the combination of project characteristics, region, and contract type; The basic value of the project characteristics-region-contract type combination is calculated based on the contribution value and expert evaluation value of the combination. Real-time regional economic correction coefficients are obtained from the national regional economic index platform. The final value of the project characteristics-region-contract type combination is calculated based on the basic value of the combination and the real-time regional economic correction coefficient. Obtain the average unit price for the region; Calculate the reference unit price of the project characteristics-region-contract type combination based on the final value of the combination and the average unit price of the region; A correlation table is constructed using project feature code, region code, contract type code, basic value, correction coefficient, final value, reference unit price, and update timestamp as core fields to obtain a correlation database of project features, region, and contract value. The system pre-defines six major conflict scenarios: code-name conflict, feature-unit price conflict, contract type-unit of measurement conflict, data source-parameter conflict, cross-time parameter conflict, and region-unit price logic conflict. Construct a three-axis data system; the three-axis data system includes a project code-time-parameter time axis constructed according to the entry timestamp, a project feature-region-parameter region axis constructed according to the project region code, and a field axis constructed according to the field-related field of the project data field; Calculate the degree of difference in the combination of project characteristics, region, and contract type; Introduce a time decay coefficient and a regional weight; The conflict value of the project characteristics-region-contract type combination is calculated based on the difference degree, time decay coefficient and regional weight of the project characteristics-region-contract type combination. Conflict levels are determined based on conflict values; The project data conflict intelligent judgment library is obtained by using the combination coding of project characteristics, region, and contract type, conflict type, three-axis coordinates, difference degree, conflict value, and conflict level as a control group. A project identification database is constructed based on a project characteristics-region-contract value association database and a project data conflict intelligent judgment database.

[0031] In this embodiment, the feature encoding serves as the identification basis for the combination of project features, region, and contract type in subsequent steps.

[0032] In this embodiment, the project feature code is derived from the classification standard table, the regional code adopts the national standard administrative division code, and the contract type code is generated according to the preset rules of contract type.

[0033] In this embodiment, the contribution value = min((actual revenue of a single project / average revenue of similar projects in the same region) × 100, 200), the regional average unit price = the arithmetic mean of the unit prices of the bill of quantities of similar projects in the same region, and when the average revenue of similar projects in the same region ≤ 0 or the number of historical projects < 5, the contribution value = 0 and the regional average unit price = 0.

[0034] In this embodiment, the industry expert evaluation node set includes 5-8 senior experts from each industry, including owners, contractors, and cost consultants, who are used to evaluate the project characteristics, region, and contract type combination on a scale of 1-10.

[0035] In this embodiment, the three-axis data system architecture is a three-dimensional data organization framework composed of three mutually perpendicular coordinate axes: Time axis: a project code-time-parameter dimension constructed based on the entry timestamp, recording the time attribute of the data; Regional axis: a project feature-region-parameter dimension constructed based on the project region code, recording the regional attribute of the data; Field axis: a field-related field dimension constructed based on the project data fields, recording the content attribute of the data. The specific composition of the three-axis coordinates: The three-axis coordinates are the precise location identifier of a specific data point in the three-axis data system, composed of coordinate values ​​in three dimensions: Time axis coordinates: determined by both the timestamp and the project code, example: 20230815-PROJ-2023-001 (representing data entered on August 15, 2023, with project code PROJ-2023-001); Correspondence: the specific location on the time axis, reflecting the timeliness and historical traceability of the data; Regional axis coordinates: determined by both the region code and the project feature code; example... : 110000-STR-001 (represents the steel structure (STR-001) feature data of Beijing (110000)); Correspondence: the specific location on the regional axis, reflecting the regional characteristics and regional differences of the data; Field axis coordinates: determined by the data field code and the associated field code; Example: UNIT-PRICE-01|QUANTITY-01 (represents the association between the unit price field and the quantity field); Correspondence: the specific location on the field axis, reflecting the field characteristics and association of the data; Practical application example: when an abnormal unit price of a steel structure project is detected: Time axis coordinates: 20230820-PROJ-2023-045; Regional axis coordinates: 110000-STR-001; Field axis coordinates: UNIT-PRICE-01|CONTRACT-TYPE-01; These three axes coordinates accurately locate the conflict between the unit price field and the contract type field in the steel structure project of Beijing entered on August 20, 2023.

[0036] In this embodiment, the normalized contribution value = min(contribution value, 100) and the basic value = normalized contribution value × 60% + evaluation value × 40%.

[0037] In this embodiment, the final value = basic value × regional economic adjustment coefficient, the reference unit price = regional average unit price × (final value / 100), and when the regional average unit price = 0, the reference unit price = 0.

[0038] In this embodiment, the difference includes the difference of numerical fields and the difference of character fields; the difference of numerical fields = |historical project unit price - reference unit price| / reference unit price, and the difference of character fields = 0 (completely consistent) or 1 (completely inconsistent). When the reference unit price ≤ 0, the difference is 1, and when the calculation result > 1, the difference is 1.

[0039] In this embodiment, the time decay coefficient = ( The difference between the current time and the updated timestamp (in years).

[0040] In this embodiment, the conflict value = difference degree × time decay coefficient × regional weight.

[0041] In this embodiment, the identification mechanism of the project identification library is as follows: Feature matching stage: When the project to be detected is input, the system first extracts its project features, regional information, and contract type, and generates corresponding codes according to the feature classification standard table to form a project feature-region-contract type combination identifier; Value matching stage: Search for matching combinations in the project feature-region-contract value association library and obtain its reference unit price. This reference unit price is a comprehensive result based on historical data, expert evaluation, and regional economic correction, representing the reasonable unit price level of the feature-region-contract type combination; Conflict detection stage: Calculate the difference between the unit price of the project to be detected and the reference unit price, and calculate the conflict value by combining the time decay coefficient and regional weight; Conflict value calculation The system considers data timeliness (time decay) and regional importance (regional weight) to make conflict determination more scientific and reasonable. In the conflict grading stage, conflicts are divided into three levels: low, medium, and high, based on their conflict values. High-conflict projects are marked as requiring close attention, medium-conflict projects require further review, and low-conflict projects are considered reasonable. In the intelligent judgment stage, the detection results are stored in the project data conflict intelligent judgment library and compared with six preset conflict scenarios to determine the specific conflict type and provide a detailed analysis of the reasons for unreasonableness. In the closed-loop optimization stage, the identification results feed back into the project feature-region-contract value association library. With the continuous addition of new data, the system can continuously optimize the calculation model of the reference unit price, improving the accuracy of identification.

[0042] The working principle and beneficial effects of the above technical solution are as follows: It calculates contribution values ​​and regional average unit prices using historical data, combining this with expert evaluation to form a basic value, avoiding reliance solely on subjective judgment and providing objective data support for unit price rationality assessment; it pre-defines six major conflict scenarios, quantifies the degree of irrationality through difference calculation, and introduces time decay coefficients and regional weights, ensuring that conflict values ​​accurately reflect the actual degree of conflict in the combination of project characteristics, region, and contract type, classifying conflicts into clear levels for targeted subsequent handling; it connects to the national regional economic index platform to obtain real-time correction coefficients, enabling reference unit prices to dynamically adapt to regional economic fluctuations and ensuring the comparability of unit prices in the bill of quantities across different regions and periods; the three-axis data system (time axis, regional axis, and field axis) enables multi-dimensional correlation analysis of project data, allowing conflict detection to consider not only unit price values ​​but also regional characteristics, time factors, and data consistency; by automatically identifying unreasonable quotations that significantly deviate from the reference unit price, it effectively prevents inflated or undervalued unit prices in the bill of quantities, reducing disputes and risks during contract performance and providing basic data support for subsequent big data analysis and decision-making regarding project costs.

[0043] Before storing the relevant data of the project after the calculation is completed, the method further includes: calculating the comprehensive unit price rationality assessment value of the relevant data of the project, and storing the relevant data of the project when the assessment value is greater than or equal to a preset assessment threshold. The comprehensive unit price reasonableness assessment value of the calculation project-related data includes: The environmental impact coefficient of a project is determined based on project type data from relevant engineering project data. Based on the project's pre-set basic rationality score and environmental impact coefficient, the first evaluation value of the project is determined. Obtain the absolute deviation values ​​of core elements and non-core elements of the relevant data of the engineering project and the preset benchmark data of the engineering project. The amplification factor of the absolute deviation value of the core element is determined based on the sum of the absolute deviation values ​​of the non-core elements and a preset constant. The second evaluation value of the project is determined based on the absolute deviation value and amplification factor of the core elements of the project-related data. The influence coefficient of each non-core element in the acquisition of relevant data for engineering projects and the influence coefficient of non-core elements on rationality; The third evaluation value of the project is determined based on the influence coefficient and impact factor of each non-core element. Based on the first, second, and third evaluation values ​​of the project, determine the comprehensive unit price rationality assessment value of the relevant data of the project.

[0044]

[0045] in, Indicates the first The comprehensive unit price rationality assessment value of relevant data for each engineering project; This indicates the pre-set basic reasonableness score; Indicates the first Environmental impact coefficient of each engineering project; Indicates the first Deviation values ​​of core elements in the data related to each engineering project; Indicates the first The first of the relevant data for each engineering project Deviation values ​​for non-core elements; This represents the baseline value for the total deviation of non-core elements; Indicates the first The total number of elements in the data related to each engineering project; Indicates the first The influence coefficient of each non-core element; Indicates the first The influence coefficient of non-core elements on rationality.

[0046] In this embodiment, Indicates the first evaluation value; This indicates the second evaluation value; This indicates the third evaluation value.

[0047] In this embodiment, This is an environmental impact moderating factor, ranging from (0,1], representing the degree to which environmental complexity weakens the basic rationality; for example, high-pollution projects. =0.8, ordinary project =1.0.

[0048] In this embodiment, core elements refer to the core components of the unit price (such as labor costs and material costs), while non-core elements refer to auxiliary items (such as management fees and taxes).

[0049] In this embodiment, C is defined as a preset benchmark value for the total deviation of non-core elements. The value is derived from historical project data and represents a reasonable threshold for the total deviation of non-core elements. For example, based on historical data, C=50 indicates that when the total deviation of non-core elements is ≤50, the impact of core deviation is relatively small; C satisfies C>0 and passes industry standard calibration. Amplification factor = Its value range is [1,3] to avoid extreme values.

[0050] In this embodiment, the influence coefficient, i.e., the value range [0,1], is determined by: statistical analysis of historical data, calculating the average proportion of this factor in the total cost of a large number of historical engineering projects; for example: by analyzing 1000 similar projects, it is found that the management fee accounts for an average of 4% of the total cost, then... =0.04×10 (normalized)=0.4; Based on the cost structure model: directly determine the basic weight of each element according to the industry standard cost structure; for example: in construction projects, labor costs usually account for 30-35%, material costs account for 50-55%, and management fees account for 3-5%, then the influence coefficient of management fees is... =0.04 (midpoint value). Management fee: typically accounts for 3-5% in construction projects. ≈0.4 (relatively high, due to its large proportion) Insurance premium: typically only accounts for 0.5-1.5%, ≈0.15 (low, due to its small proportion) Taxes and fees: fixed percentage but large amount. ≈0.3 (Medium).

[0051] In this embodiment, the influence coefficient and historical deviation impact analysis analyze the correlation between the deviation of this element in historical data and the final evaluation of the project. For example, if statistics show that a 1% deviation in taxes and fees leads to 70% of projects being judged as unreasonable, then... =0.7; Sensitivity analysis: Through simulation calculation, other factors are fixed, and only this factor is changed to observe the degree of impact on the final evaluation value; for example: for every 1% increase in taxes and fees, the comprehensive evaluation value decreases by an average of 1.2 points. =1.2 / Maximum Possible Deduction = 0.8; For example: Taxes and Fees: Highly sensitive to policy changes; even a 1% deviation could lead to an unreasonable project. ≈0.9 (very high); Management fee: usually has flexibility, a deviation of 2-3% is generally acceptable. ≈0.5 (Medium); Insurance premium: fluctuations are small and the impact is limited. ≈0.3 (lower). The difference between the impact coefficient and the influence coefficient: The impact coefficient represents the inherent importance of a factor in the cost structure, that is, how important the factor itself is; the influence coefficient represents the sensitivity of a factor's deviation to reasonableness, that is, how dangerous the fluctuation of this factor is.

[0052] The working principle and beneficial effects of the above technical solution are as follows: Before storing relevant data of engineering projects, a comprehensive unit price rationality assessment value is calculated and compared with a preset assessment threshold. Data is only stored when the assessment value is greater than or equal to the preset assessment threshold. This effectively filters out engineering project data with unreasonable comprehensive unit prices, ensuring the quality of stored data and avoiding subsequent analysis and decision-making based on low-quality data. Through the assessment of the rationality of the comprehensive unit price, the stored data has a certain degree of consistency and reliability in terms of unit price rationality, providing a solid data foundation for subsequent data mining, cost analysis, project comparison, and other work.

[0053] In summary, the method and system for detecting the reasonableness of the comprehensive unit price in the bill of quantities of this invention extracts the characteristics of new engineering projects and performs similar feature retrieval in a project identification database. Based on project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source, it dynamically configures the bill of quantities template to achieve rapid adaptation to new engineering projects, avoiding the lag of traditional manual review. It is particularly suitable for emerging engineering fields with complex technologies or frequent design changes. Cluster analysis technology is used to identify key influencing factors, such as material price fluctuations and differences in construction techniques, and new engineering projects are generated using historical data. The comprehensive unit price reasonableness range provides a quantitative basis for decision-making. Through standardized testing processes, it can reduce pricing disputes caused by ambiguous descriptions of new project characteristics. The function of automatically comparing quotations with reasonableness ranges can effectively identify abnormal quotations. By establishing an automatic screening mechanism for abnormal pricing through a project identification database, it can detect omissions in the bill of quantities and deviations in characteristic descriptions in advance, avoiding settlement disputes caused by pricing errors. By correcting abnormal quotations that deviate from the reasonableness range, it can reduce the risk of project delays or claims caused by pricing errors. By automatically generating comprehensive unit price analysis tables through correction records, it clarifies the cost composition and adjustment basis.

[0054] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0055] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for testing the reasonableness of the comprehensive unit price in a bill of quantities, characterized in that, Includes the following steps: Collect relevant data for the engineering project, perform data cleaning, and extract key factor features after cleaning; The price range for relevant items in the project is calculated using the pricing documents to obtain the comprehensive unit price corresponding to the item name; Build a project identification library and store the calculated project-related data according to templates such as project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source; After the project identification library is built, the projects in the project identification library are scanned, and projects with pricing abnormalities are quickly identified. When a project with pricing abnormalities is identified, the project pricing is corrected and improved. When a new project is encountered during the scanning process, its features are extracted and compared with historical related project data to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the project is stored in the project identification library.

2. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, The process involves collecting relevant data from the engineering project, cleaning the data, and extracting key feature elements, specifically including: Collect relevant data for the project, including bill of quantities, pricing documents, quota information, and personnel, material, and equipment information; Preprocessing of project-related data includes: cleaning project-related data, preprocessing missing and outlier values ​​in project-related data, removing irrelevant noise, improving the data quality of multi-source business data, and standardizing measurement units. After the cleaning is completed, key factor features are extracted, including project name, project characteristics, unit of measurement, region, contract type, and project source.

3. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, After the calculation is completed, the relevant data of the engineering project will be stored according to the templates of project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source, specifically including: The project code, project name, project characteristics, unit of measurement, comprehensive unit price, project region, contract type, and project source are fixed into a template. The project characteristics include the project materials and project processes corresponding to the project name. Fill in the template with the calculated comprehensive unit price corresponding to the project name and the extracted key factor features; Save the completed template, lock the key fields, and use standardized coding for the project.

4. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, After the project identification library is built, the projects in the library are scanned, and projects with pricing anomalies are quickly identified. When a project with pricing anomalies is identified, its pricing is corrected and improved, specifically including: After the project identification library is built, the reasonable range of historical comprehensive unit prices is calculated, and then the projects in the project identification library are scanned. The comprehensive unit price of the project in the project identification database is compared with the reasonable range to determine whether the comprehensive unit price of the project exceeds the reasonable range. When the comprehensive unit price of a project exceeds the reasonable range, the comprehensive unit price of the project shall be revised and improved.

5. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 4, characterized in that, The reasonable range for calculating the historical comprehensive unit price specifically includes: Extract the historical comprehensive unit price of similar lists and verify the historical comprehensive unit price using the normal distribution method; It also determines whether there is any abnormal data in the historical comprehensive unit price. If there is abnormal data, it removes the abnormal data until there is no abnormal data. After the exclusion is completed, the reasonable range of historical comprehensive unit prices is calculated, and the comprehensive unit prices of projects that exceed the reasonable range are marked as abnormal.

6. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 5, characterized in that, Projects with unit prices exceeding the reasonable range will be marked as abnormal, specifically including: Abnormal unit prices exceeding the highest threshold of the reasonable range are marked in red, and those below the lowest threshold of the reasonable range are marked in green. Output a list of abnormal items with composite unit prices, including the abnormal list code, item characteristics, unit of measurement, composite unit price, confidence interval for comparison, and deviation rate.

7. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, When a new project is encountered during the scanning process, its features are extracted and compared with historical related project data to identify similar historical projects. Cost prediction is then performed using these similar historical projects. Based on the predicted cost of the new project, the actual cost is calculated, the comprehensive unit price of the new project is determined, and the project is stored in the project identification database. Specifically, this includes: When a new project is encountered during the scanning process, relevant features of the new project are extracted, and the relevant features are used to search in the project identification database. When relevant features are retrieved from the project identification database, the random forest algorithm is used for statistical classification analysis. The engineering projects related to the new engineering project are classified according to price, project name, project materials corresponding to the project name, and project process; Identify historical engineering project data that closely matches the new engineering project, use the historical engineering project data to predict the cost of the new engineering project, and generate the actual cost of the new engineering project. A deviation analysis was performed on the unit price of the new project, and the index weights were adjusted according to the analysis results to obtain the comprehensive unit price of the new project. Match the unit price of the new project to the corresponding project code, project name, project characteristics, unit of measurement, region, contract type and project source, and store it in the project identification database.

8. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, The methods for building a project identification library include: Obtain historical project datasets and extract features to obtain project features; Project characteristics are stratified and classified based on industry type to generate a project characteristic classification standard table; the classification standard table defines project characteristic coding rules, mapping each project characteristic to a unique characteristic code; Extract data corresponding to project characteristics, region, and contract type from the historical project contribution event database as the first data; Calculate the contribution value of the first data and the average unit price of the region corresponding to the combination of project characteristics, region, and contract type; Obtain the expert evaluation values ​​of the industry expert evaluation node set for the combination of project characteristics, region, and contract type; The basic value of the project characteristics-region-contract type combination is calculated based on the contribution value and expert evaluation value of the combination. Real-time regional economic correction coefficients are obtained from the national regional economic index platform. The final value of the project characteristics-region-contract type combination is calculated based on the basic value of the combination and the real-time regional economic correction coefficient. Obtain the average unit price for the region; Calculate the reference unit price of the project characteristics-region-contract type combination based on the final value of the combination and the average unit price of the region; A correlation table is constructed using project feature code, region code, contract type code, basic value, correction coefficient, final value, reference unit price, and update timestamp as core fields to obtain a correlation database of project features, region, and contract value. The system pre-defines six major conflict scenarios: code-name conflict, feature-unit price conflict, contract type-unit of measurement conflict, data source-parameter conflict, cross-time parameter conflict, and region-unit price logic conflict. Construct a three-axis data system; the three-axis data system includes a project code-time-parameter time axis constructed according to the entry timestamp, a project feature-region-parameter region axis constructed according to the project region code, and a field axis constructed according to the field-related field of the project data field; Calculate the degree of difference in the combination of project characteristics, region, and contract type; Introduce a time decay coefficient and a regional weight; The conflict value of the project characteristics-region-contract type combination is calculated based on the difference degree, time decay coefficient and regional weight of the project characteristics-region-contract type combination. Conflict levels are determined based on conflict values; The project data conflict intelligent judgment library is obtained by using the combination coding of project characteristics, region, and contract type, conflict type, three-axis coordinates, difference degree, conflict value, and conflict level as a control group. A project identification database is constructed based on a project characteristics-region-contract value association database and a project data conflict intelligent judgment database.

9. The method for detecting the reasonableness of the comprehensive unit price in the bill of quantities according to claim 1, characterized in that, Before storing the relevant data of the project after the calculation is completed, the method further includes: calculating the comprehensive unit price rationality assessment value of the relevant data of the project, and storing the relevant data of the project when the assessment value is greater than or equal to a preset assessment threshold. The comprehensive unit price reasonableness assessment value of the calculation project-related data includes: The environmental impact coefficient of a project is determined based on project type data from relevant engineering project data. Based on the project's pre-set basic rationality score and environmental impact coefficient, the first evaluation value of the project is determined. Obtain the absolute deviation values ​​of core elements and non-core elements of the relevant data of the engineering project and the preset benchmark data of the engineering project. The amplification factor of the absolute deviation value of the core element is determined based on the sum of the absolute deviation values ​​of the non-core elements and a preset constant. The second evaluation value of the project is determined based on the absolute deviation value and amplification factor of the core elements of the project-related data. The influence coefficient of each non-core element in the acquisition of relevant data for engineering projects and the influence coefficient of non-core elements on rationality; The third evaluation value of the project is determined based on the influence coefficient and impact factor of each non-core element. Based on the first, second, and third evaluation values ​​of the project, determine the comprehensive unit price rationality assessment value of the relevant data of the project.

10. A system for detecting the reasonableness of a comprehensive unit price in a bill of quantities, applied in the method for detecting the reasonableness of a comprehensive unit price in a bill of quantities as described in claim 9, characterized in that, include: The unit price calculation module is used to collect relevant data of engineering projects, preprocess the relevant data, extract key factor features after cleaning, and use the pricing file to calculate the price range of relevant items of the project to obtain the comprehensive unit price corresponding to the project name. The database construction module is used to build a project identification library. It fills the template with the comprehensive unit price corresponding to the calculated project name and the extracted key factor features, stores the filled template, locks the key fields, and uniformly encodes the projects. The comprehensive unit price identification module is used to calculate the reasonable range of historical comprehensive unit prices. After the calculation is completed, it scans the projects in the project identification database, compares the comprehensive unit price of the projects in the project identification database with the reasonable range, and determines whether the comprehensive unit price of the project exceeds the reasonable range. The new project identification module is used to extract relevant features from new projects during the scanning process, identify historical project data that closely matches the new projects, and use the historical project data to calculate and store the comprehensive unit price of the new projects.

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