Settlement auxiliary analysis method based on bill of quantity structured data

Abstract

The invention discloses a bill of quantity structured data-based settlement auxiliary analysis method, and belongs to the technical field of power industry distribution network business expansion supporting engineering. In order to solve the problem of low data processing efficiency of the bill of quantity structured data, the method comprises the following steps: importing the bill structured data of a business expansion matching project into a settlement auxiliary analysis system, and preprocessing the bill structured data; the list structured data comprises initial data, construction review data, supervision review data and auditing data; key data items in the bill of quantity are automatically identified and matched on the basis of the characteristics of the structured data; performing difference comparison analysis on the list structured data including initial data, construction review data, supervision review data and auditing and approving data by adopting an intelligent optimization algorithm, and enabling a difference comparison analysis result to meet a constraint condition; and generating a project report containing the key indexes, the data analysis result and the suggestions, and visually displaying the project report. The method is used for construction engineering.

Description

Technical Field

[0001] The invention relates to a settlement auxiliary analysis method based on structured data of a bill of quantities, and belongs to the technical field of expansion and matching engineering of distribution network business in the electric power industry. Background Art

[0002] The bill of quantities is a detailed list of the names and corresponding quantities of the sub-items, measures, other items, fees and taxes of a construction project. It consists of a bill of quantities of sub-items, a list of measures, a list of other items, and a list of fees and taxes.

[0003] At present, the commonly used settlement auxiliary analysis tools for structured data of bill of quantities have the following deficiencies:

[0004] (1) Inconsistent review formats: Regarding the settlement of supporting projects for business expansion, each unit has no fixed format for review, resulting in different review formats for different units, and the review unit cannot complete the review and review work quickly by finding a pattern;

[0005] (2) Traditional settlement review method: Currently, most of them are submitted for review in the form of Excel, and then the quantity and cost difference comparison of the bill of quantities is completed through manual screening, sorting and formula comparison. There are problems such as manual errors and omissions of comparison items, which pose audit risks;

[0006] (3) Low efficiency of settlement and review: Currently, most of the construction review and approval work is mainly done by manual verification, which has a low efficiency, affecting the project settlement progress and fund use adjustment;

[0007] (4) Lack of flexibility: Existing tools often lack the necessary flexibility and adaptability when dealing with engineering projects of different types and sizes, and are unable to meet personalized needs. Summary of the invention

[0008] The purpose of the present invention is to solve the problem of low data processing efficiency of structured data of bill of quantities, and to provide a settlement auxiliary analysis method based on structured data of bill of quantities.

[0009] The present invention provides a settlement auxiliary analysis method based on structured data of bill of quantities, which comprises:

[0010] S1. Import the structured data of the list of supporting projects for business expansion into the settlement auxiliary analysis system, and pre-process the structured data of the list;

[0011] The structured data in the list includes initial data, construction review data, supervision review data and audit approval data;

[0012] S2. Automatically identify and match the key data items in the bill of quantities based on the characteristics of structured data;

[0013] S3. Use an intelligent optimization algorithm to conduct a differential comparison analysis on the list structured data including initial data, construction review data, supervision review data, and audit approval data, and make the results of the differential comparison analysis meet the constraint conditions;

[0014] S4. Generate a project report containing key indicators, data analysis results, and suggestions, and conduct a visual display thereof.

[0015] Preferably, the initial data in S1 includes the basic information of the engineering project, the division of the engineering project, the detailed description of the construction project, the quantity and specifications of materials and equipment, and the labor force requirements;

[0016] The construction review data includes the bill of quantities and its related descriptions;

[0017] The supervision review data includes the review information and confirmation information of the bill of quantities;

[0018] The audit approval data includes the quantities, unit prices, and total prices of each item in the bill of quantities.

[0019] Preferably, the preprocessing of the list structured data in S1 specifically includes:

[0020] S1-1. Conduct data cleaning on the list structured data, including duplicate removal, missing value processing, outlier detection and correction of the list structured data;

[0021] S1-2. Conduct data classification and coding on the data after data cleaning, including classifying and coding the data, and establishing a data dictionary for retrieval and analysis.

[0022] Preferably, the specific method for automatically identifying and matching the key data items in the bill of quantities in S2 includes:

[0023] Use a core algorithm module to automatically identify and match the key data items in the bill of quantities;

[0024] The core algorithm module includes an intelligent recognition algorithm and an intelligent matching algorithm.

[0025] Preferably, the automatic identification and matching of the key data items in the bill of quantities by the core algorithm module specifically includes:

[0026] Use an intelligent recognition algorithm to automatically identify the key data items in the bill of quantities;

[0027] An intelligent matching algorithm is adopted to identify and match similar lists from the preliminary list, construction submission list, supervision submission list, and settlement submission list.

[0028] Preferably, the key data items described in S2 include project code, project name, project characteristics, measurement unit, and quantity of work.

[0029] Preferably, the specific method for using the intelligent optimization algorithm to conduct differential comparison and analysis on the structured data of the list, including initial data, construction submission data, supervision submission data, and audit approval data, described in S3 is as follows:

[0030] The multi-dimensional data analysis method is used to conduct differential comparison and analysis on the data, specifically including basic settlement analysis, time series analysis, and cost-benefit analysis;

[0031] The intelligent identification, matching, and optimization algorithms are used to implement the automated process of differential comparison and analysis, automatically identifying key item data, matching historical data, and optimizing resource allocation.

[0032] Preferably, the constraint conditions described in S3 include project scope constraint, technical constraint, resource constraint, time constraint, cost constraint, quality constraint, and regulatory constraint.

[0033] Preferably, the specific content of generating a project report containing key indicators, data analysis results, and suggestions described in S4 is as follows:

[0034] According to user requirements and preset templates, a project report is automatically generated, and it supports exporting the report in various file formats.

[0035] Preferably, the specific content of visually displaying the project report described in S4 is as follows:

[0036] The interactive interface is used to visually display the project report;

[0037] The interactive interface can realize user-defined query conditions, data filtering, and adjustment of chart styles.

[0038] Advantages of the present invention: The settlement auxiliary analysis method based on the structured data of the bill of quantities described in the present invention is applied to the distribution network expansion and supporting project in the power industry, realizing the automatic comparison and settlement auxiliary analysis in the construction settlement submission, supervision settlement submission, and audit approval links based on the structured data of the bill of quantities. It can greatly improve the data processing efficiency, effectively enhance the data visualization ability, and can also realize automated settlement analysis, support multi-dimensional data analysis at the same time, and can effectively improve the decision-making support ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1It is the flowchart of a settlement auxiliary analysis method based on structured data of bill of quantities according to the present invention;

[0040] Figure 2 It is the principle block diagram of a settlement auxiliary analysis method based on structured data of bill of quantities according to the present invention;

[0041] Figure 3 It is the flowchart for preprocessing the structured data of the list;

[0042] Figure 4 It is the principle block diagram of the core algorithm module;

[0043] Figure 5 It is the principle block diagram for visual display;

[0044] Figure 6 It is the principle block diagram for generating a project report. Specific embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments may be combined with each other.

[0047] Next, the present invention will be further described in conjunction with the accompanying drawings and specific embodiments, but it is not a limitation of the present invention.

[0048] Embodiment 1:

[0049] Next, in conjunction with Figures 1-6 This embodiment will be described. A settlement auxiliary analysis method based on structured data of bill of quantities according to this embodiment includes:

[0050] S1. Import the structured data of the list of the service expansion supporting project into the settlement auxiliary analysis system, and preprocess the structured data of the list;

[0051] The structured data of the list includes initial data, construction review data, supervision review data, and audit approval data;

[0052] S2. Automatically identify and match the key data items in the bill of quantities based on the characteristics of the structured data;

[0053] S3. Use intelligent optimization algorithms to perform differential comparison and analysis on the structured data of the list, including initial data, construction submission data, supervision submission data, and audit approval data, and ensure that the results of the differential comparison and analysis meet the constraint conditions;

[0054] S4. Generate a project report containing key indicators, data analysis results, and suggestions, and conduct visual display on it.

[0055] Furthermore, the initial data in S1 includes the basic information of the engineering project, the division of the engineering project, the detailed description of the construction project, the quantity and specifications of materials and equipment, and the labor force requirements;

[0056] The construction submission data includes the bill of quantities and its related descriptions;

[0057] The supervision submission data includes the review information and confirmation information of the bill of quantities;

[0058] The audit approval data includes the quantities, unit prices, and total prices of each item in the bill of quantities.

[0059] Still further, the specific preprocessing of the structured data of the list in S1 specifically includes:

[0060] S1-1. Perform data cleaning on the structured data of the list, including removing duplicates, handling missing values, detecting and correcting outliers in the structured data of the list;

[0061] S1-2. Classify and code the data after data cleaning, including classifying and coding the data, and establishing a data dictionary for retrieval and analysis.

[0062] Still further, the specific method for automatically identifying and matching the key data items in the bill of quantities in S2 includes:

[0063] Use the core algorithm module to automatically identify and match the key data items in the bill of quantities;

[0064] The core algorithm module includes an intelligent recognition algorithm and an intelligent matching algorithm.

[0065] Still further, the automatic identification and matching of the key data items in the bill of quantities by the core algorithm module specifically includes:

[0066] Use the intelligent recognition algorithm to automatically identify the key data items in the bill of quantities;

[0067] Use the intelligent matching algorithm to identify and match the same type of lists in the preliminary design list, construction submission list, supervision submission list, and settlement submission list.

[0068] Furthermore, the key data items described in S2 include project code, project name, project characteristics, measurement unit, and quantity of work.

[0069] Furthermore, the specific method for using the intelligent optimization algorithm to perform differential comparison and analysis on the list structured data including initial data, construction submission data, supervision submission data, and audit approval data described in S3 includes:

[0070] Using multi-dimensional data analysis methods to perform differential comparison and analysis on the data, specifically including basic settlement analysis, time series analysis, and cost-benefit analysis;

[0071] Using intelligent recognition, matching, and optimization algorithms to implement the automated process of differential comparison and analysis, automatically identifying key item data, matching historical data, and optimizing resource allocation.

[0072] Furthermore, the constraint conditions described in S3 include project scope constraint, technical constraint, resource constraint, time constraint, cost constraint, quality constraint, and regulatory constraint.

[0073] Furthermore, the specific content of generating a project report including key indicators, data analysis results, and suggestions described in S4 specifically includes:

[0074] Automatically generating a project report according to user requirements and preset templates, and supporting the export of the report in various file formats.

[0075] Furthermore, the specific content of visually displaying the project report described in S4 specifically includes:

[0076] Using an interactive interface to visually display the project report;

[0077] The interactive interface can realize user-defined query conditions, filter data, and adjust chart styles.

[0078] In the present invention, for the import and preprocessing of list structured data, the user first needs to import the preliminary design data, construction submission data, supervision submission data, and audit approval data of the service expansion supporting project into the system. The preliminary design data usually includes key contents such as the basic information of the engineering project, the division of the engineering project, the detailed description of the construction project, the quantity and specifications of materials and equipment, and the labor force requirements. The construction submission data mainly includes the bill of quantities and its related descriptions and forms. These data are important components of the contract documents. The supervision submission data mainly includes the review and confirmation information of the bill of quantities. The supervision personnel will carefully review the bill of quantities, check whether the items in the list are complete and accurate, whether the calculation of the quantity of work is correct, and whether it complies with relevant standards and regulations. The audit approval data includes the quantity of work, unit price, total price, etc. of each item in the bill of quantities, which are the data that must be obtained and analyzed by the auditor when performing the audit work;

[0079] Intelligent recognition and matching. Combining the characteristics of structured data, which include clear format and organization, easy retrieval and analysis, high consistency and accuracy, scalability, etc., automatically identify key data items in the bill of quantities. The key data items include project code, project name, project characteristics, measurement unit, and quantity of work, etc.;

[0080] Intelligent optimization and analysis. On the premise of meeting project scope constraints, technical constraints, resource constraints, time constraints, cost constraints, quality constraints, and regulatory constraints, the system will accurately analyze and locate the comparison differences between the preliminary design data, construction submission data, supervision submission data, and audit approval data through intelligent optimization algorithms;

[0081] Visualization display. The tool system will display the analysis results to users through a friendly interactive interface;

[0082] Report generation. The tool system will automatically generate a project report containing key indicators, data analysis results, suggestions, etc. This settlement auxiliary analysis tool based on structured data of the bill of quantities can greatly improve data processing efficiency, effectively enhance data visualization capabilities, and can also achieve automated settlement analysis, support multi-dimensional data analysis at the same time, and can effectively improve decision-making support capabilities.

[0083] The import and preprocessing of the structured list data include the following steps:

[0084] Directly import data into the tool database through a data interface or import data into the tool database by manual input;

[0085] Preprocess the imported data through a data preprocessing module.

[0086] The intelligent recognition and matching include the following steps:

[0087] The core algorithm module includes an intelligent recognition algorithm and an intelligent matching algorithm;

[0088] Identify key data items from the preprocessed data through the core algorithm module.

[0089] The intelligent optimization and analysis include the following steps:

[0090] Multi-dimensional data analysis. It can perform basic settlement data analysis on data, as well as time series analysis, cost-benefit analysis, etc.;

[0091] Automated settlement analysis. Using intelligent recognition, matching, and optimization algorithms, it realizes the automated process of settlement analysis, automatically identifies key data items, matches historical data, optimizes resource allocation, etc.

[0092] The visual display includes the following steps:

[0093] Through the visual display module, complex data is presented in the form of an intuitive interactive interface, helping users better understand the meaning and trends behind the data, enhancing the readability and usability of the data.

[0094] The report generation includes the following steps:

[0095] Through the report generation module, a project report containing key indicators, data analysis results, suggestions, etc. is automatically generated, helping users better understand and grasp the project progress and financial status, providing strong support for project management and decision-making, and improving the scientificity and accuracy of decision-making.

[0096] The data preprocessing module includes the following steps:

[0097] Data cleaning: Operations such as duplicate removal, missing value handling, outlier detection and correction are performed on the original bill of quantities data to ensure the accuracy and integrity of the data;

[0098] Data classification and coding: According to the characteristics of the bill of quantities, the data is classified and coded, and a data dictionary is established to facilitate subsequent retrieval and analysis.

[0099] The core algorithm module includes the following steps:

[0100] Intelligent recognition algorithm: Through the structured data of the bill of quantities, key data items in the bill of quantities are automatically recognized;

[0101] Intelligent matching algorithm: By algorithmically matching the preliminary design list, construction application list, supervision application list, and settlement application list, similar lists are identified and matched.

[0102] The visual display module includes the following steps:

[0103] Interactive interface: Provide an interactive interface that allows users to customize query conditions, filter data, adjust chart styles, etc., improving the user experience.

[0104] The report generation module includes the following steps:

[0105] Automatically generate a report: According to user requirements and preset templates, automatically generate a project report containing key indicators, data analysis results, suggestions, etc.;

[0106] Report export: Support the report export function in multiple file formats, such as PDF, Word, Excel, etc., facilitating users to use and share in different scenarios.

[0107] Compared with the prior art, the advantages of the present invention are:

[0108] Significant improvement in data processing efficiency: Through advanced data preprocessing techniques, the invention can quickly and accurately clean, standardize, and classify and code the bill of quantities data, greatly reducing the time and errors of manual operations and improving the efficiency and accuracy of data processing.

[0109] Enhanced data visualization ability: The invention provides powerful data visualization functions, presenting complex data in the form of an intuitive interactive interface, helping users better understand the meaning and trends behind the data, and enhancing the readability and usability of the data.

[0110] Automation of settlement analysis achieved: Using intelligent recognition, matching, and optimization algorithms, the invention realizes the automated process of settlement analysis, automatically identifying key data items, matching historical data, optimizing resource allocation, etc., greatly improving the accuracy and efficiency of settlement analysis.

[0111] Support for multi-dimensional data analysis: The invention not only supports basic settlement data analysis but also has the ability of multi-dimensional data analysis, such as time series analysis, cost-benefit analysis, etc., providing users with a more comprehensive and in-depth perspective for project evaluation.

[0112] Improved decision-making support ability: By providing accurate and comprehensive data support and analysis results, the invention can help users better understand and grasp the project progress and financial situation, provide strong support for project management and decision-making, and improve the scientificity and accuracy of decision-making.

[0113] Although the present invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed, as long as they do not depart from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the different dependent claims and the features described herein can be combined in a manner different from that described in the original claims. It should also be understood that the features described in connection with a single embodiment can be used in other described embodiments.

Claims

1. A settlement auxiliary analysis method based on structured data of bill of quantities, characterized in that: It includes: S1. Import the structured data of the list of supporting projects for business expansion into the settlement auxiliary analysis system, and pre-process the structured data of the list; The structured data in the list includes initial data, construction review data, supervision review data and audit approval data; S2. Based on the characteristics of structured data, key data items in the bill of quantities are automatically identified and matched; S3. Use intelligent optimization algorithms to conduct difference comparison analysis on the list structured data including initial data, construction application data, supervision application data and audit approval data, and make the difference comparison analysis results meet the constraint conditions; S4. Generate a project report containing key indicators, data analysis results and recommendations, and present them visually.

2. A settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The initial data in S1 includes basic information of the project, division of the project, detailed description of the construction project, quantity and specifications of materials and equipment, and labor demand; The construction review data includes the bill of quantities and related instructions; The supervision review data includes the review information and confirmation information of the bill of quantities; The audit and approval data include the quantity, unit price and total price of each item in the bill of quantities.

3. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The preprocessing of the list structured data in S1 specifically includes: S1-1. Perform data cleaning on the list structured data, including deduplication, missing value processing, outlier detection and correction; S1-2. Classify and encode the cleaned data, including classifying and encoding the data and establishing a data dictionary for retrieval and analysis.

4. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The specific method for automatically identifying and matching key data items in the bill of quantities described in S2 includes: Use the core algorithm module to automatically identify and match key data items in the bill of quantities; The core algorithm module includes an intelligent recognition algorithm and an intelligent matching algorithm.

5. A settlement auxiliary analysis method based on bill of quantities structured data according to claim 4, characterized in that: The core algorithm module automatically identifies and matches key data items in the bill of quantities, specifically including: Use intelligent recognition algorithms to automatically identify key data items in the bill of quantities; An intelligent matching algorithm is used to identify and match similar lists such as the initial design list, construction submission list, supervision submission list and settlement submission list.

6. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The key data items described in S2 include project code, project name, project characteristics, measurement units and project quantities.

7. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The specific method of using intelligent optimization algorithm to conduct difference comparison analysis on the list structured data including initial data, construction application data, supervision application data and audit approval data described in S3 includes: Use multi-dimensional data analysis methods to conduct comparative analysis of data, including basic settlement analysis, time series analysis and cost-benefit analysis; Intelligent recognition, matching and optimization algorithms are used to realize the automated process of difference comparison and analysis, automatically identify key data, match historical data and optimize resource allocation.

8. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The constraints described in S3 include project scope constraints, technical constraints, resource constraints, time constraints, cost constraints, quality constraints and regulatory constraints.

9. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: S4 describes the generation of a project report containing key indicators, data analysis results, and recommendations, including: Automatically generate project reports based on user needs and preset templates, and support exporting reports in multiple file formats.

10. The settlement auxiliary analysis method based on bill of quantities structured data according to claim 1, characterized in that: The visual display of the project report described in S4 specifically includes: Use interactive interface to visualize project reports; The interactive interface enables users to customize query conditions, filter data and adjust chart styles.

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