A method and related device for collecting water and electricity and water conservancy project budget based on coding mapping

Abstract

The application provides a water and electricity and water conservancy project budget collection method based on coding mapping and related devices, and belongs to the technical field of project budget collection. In the tree structure corresponding to the bill of quantities and the project budget list, a budget collection path automatic identification algorithm is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-objects and the budget collection target nodes; for each contract, the progress settlement report of each settlement is calculated, and the settlement amount of each settlement of the project bill of quantities sub-objects is counted; based on the many-to-one coding mapping relationship and the progress settlement report of each settlement, the settlement amount of each settlement of the project bill of quantities sub-objects of each contract is automatically collected to the minimum target unit corresponding to the budget tree of the hierarchical structure, and the budget collection report of each settlement of the minimum target unit is obtained. The application solves the problem of low efficiency of water and electricity and water conservancy project budget collection.

Description

Technical Field

[0001] This invention belongs to the field of engineering cost estimation technology, specifically relating to a method and related apparatus for cost estimation of hydropower and water conservancy projects based on coding mapping. Background Technology

[0002] In recent years, with the integration of the engineering and IT (Information Technology) industries, the level of digital management technology for hydropower and water conservancy project investment has gradually improved. However, most systems have only achieved the informatization of some business processes in investment management, mainly focusing on the input or simple calculation of measurement, settlement, and payment data, online process management, and automatic generation of statistical reports. The work of collecting preliminary estimate data is highly dependent on manual operation, which is not only time-consuming and labor-intensive, but also has a high error rate and makes it difficult to guarantee data quality. The traditional manual preliminary estimate collection mode has become a bottleneck restricting efficiency and accuracy, and it is difficult to meet the needs of refined management.

[0003] Therefore, there is an urgent need to propose a new method for investment estimation and over-estimate early warning using information technology and coding technology, so as to achieve efficient integration and calculation of budget data and provide technical support for the analysis and decision-making of budget aggregation. Summary of the Invention

[0004] The purpose of this invention is to provide a method and related apparatus for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping, in order to solve the problem of low efficiency in the collection of preliminary estimates of hydropower and water conservancy projects in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for compiling preliminary estimates for hydropower and water conservancy projects based on encoding mapping, comprising the following steps: Obtain several contracts, wherein the contracts include a bill of quantities, and the bill of quantities includes several bill of quantities sub-items; Obtain a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules for the target budget stage. In the hierarchical budget tree, the smallest target unit for the collection of budget amounts in the target budget stage is designated as the budget collection target node, and the hierarchy of the budget collection target node remains consistent. The bill of quantities and the project budget are coded according to rules to obtain the rule coding results; The rule coding results are parsed to obtain the tree structure corresponding to the bill of quantities and the project budget list; Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection path is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes. For each contract, calculate the progress settlement report for each period and compile the settlement amount for each period of the project bill of quantities sub-item; Based on the many-to-one coding mapping relationship and the progress settlement reports of each period, the settlement amount of each period of the project bill of quantities sub-item of each contract is automatically collected to the smallest target unit corresponding to the budget tree of the hierarchical structure, so as to obtain the budget collection report of each period of the smallest target unit.

[0006] A further improvement of this invention is that the encoding mapping relationship supports manual review and adjustment.

[0007] A further improvement of this invention lies in that, within the tree structure corresponding to the bill of quantities and the project budget estimate, an automatic identification algorithm for budget estimate aggregation paths is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget estimate aggregation target nodes, specifically as follows: Obtain the contract name, perform engineering semantic matching between the contract name and the standard name of the parent category node of the target node in the budget collection tree, determine the range of the parent category node to which the contract belongs, and form a hierarchical constraint of the collection search space. Within the determined range of the superior classification node to which the contract belongs, for each item in the bill of quantities, under the hierarchical constraints of the aggregation search space, all budget aggregation target nodes included in the range are used as the candidate aggregation target set to extract the attribute information of the item in the bill of quantities. Based on the attribute information, the comprehensive aggregation similarity between the bill of quantities sub-items and each candidate budget aggregation target node is calculated. The budget aggregation target node with the highest comprehensive aggregation similarity is determined as the final aggregation target of the bill of quantities sub-item, thus forming a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget aggregation target node.

[0008] A further improvement of the present invention is that the comprehensive aggregation similarity is obtained by weighted summation of the text similarity of the project name and the matching degree of the project features in the bill of quantities sub-items.

[0009] A further improvement of this invention is that the text similarity of the project name is obtained based on the semantic vector model of engineering terms trained on the professional corpus of hydropower and water conservancy engineering; the project feature matching degree is obtained by extracting key features of engineering parts, material types and construction technology from the project description of the sub-items of the bill of quantities and comparing them in a structured manner with the standard features of the target node of the budget collection.

[0010] A further improvement of this invention lies in the fact that the automatic aggregation of the settlement amounts for each period of the project quantity list sub-item of each contract to the smallest target unit corresponding to the hierarchical budget tree is specifically as follows: Determine the contract settlement matrix and transformation matrix; Multiply the contract settlement matrix and the transformation matrix to obtain the preliminary calculation aggregation matrix; Using the budget aggregation matrix, the settlement amounts for each period of the project bill of quantities sub-items in each contract are automatically aggregated to the smallest target unit corresponding to the hierarchical budget tree; The formula for calculating the approximate aggregation matrix is ​​as follows:

[0011] in, For the preliminary aggregation matrix, For the transformation matrix, For contract settlement matrix, k The number of sub-items in the bill of quantities. l The number of settlement cycles. w This is the smallest target unit corresponding to the preliminary calculation tree; Transformation matrix The calculation formula is:

[0012] in, For the bill of quantities, number k The settling relationship between sub-items and the first smallest target unit corresponding to the budget tree. For the bill of quantities, number k The item and the corresponding budget tree w The reducibility relationship of the smallest target unit; Contract Settlement Matrix The calculation formula is:

[0013] in, For item 1 of the bill of quantities, in the... l Settlement amount within a settlement period For the bill of quantities, number k Item No. l Settlement amount within a settlement cycle.

[0014] A further improvement of this invention is that, after obtaining the budget collection report for each period of the minimum target unit, the data in the budget collection report for each period of the minimum target unit is cumulatively calculated to obtain the cumulative calculation result. Based on the cumulative calculation result, it is determined whether the cumulative budget investment has exceeded the budget and an over-budget warning message is issued.

[0015] Secondly, the present invention provides a hydropower and water conservancy project budget collection system based on encoding mapping, comprising: The first data acquisition module is used to acquire several contracts, the contracts including a bill of quantities, and the bill of quantities including several bill of quantities sub-items; The second data acquisition module is used to acquire a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules of the target budget stage. The node specification module is used to specify the smallest target unit for the collection of budgeted amounts in the target budgeting stage as the budget collection target node in the hierarchical budgeting tree, and the hierarchy of the budget collection target node remains consistent. The rule coding module is used to perform rule coding on the bill of quantities and the project budget list to obtain the rule coding results; The parsing module is used to parse the rule encoding results and obtain the tree structure corresponding to the bill of quantities and the project budget list; The coding mapping module is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the estimated budget target nodes within the tree structure corresponding to the bill of quantities and the project estimate list, using an automatic identification algorithm for the estimated budget collection path. The calculation module is used to calculate the progress settlement report for each period for each contract, and to calculate the settlement amount for each period of the project bill of quantities sub-items; The preliminary estimate aggregation module is used to automatically aggregate the settlement amount of each period of the project bill of quantities sub-item of each contract to the smallest target unit corresponding to the preliminary estimate tree of the hierarchical structure, based on the many-to-one coding mapping relationship and the progress settlement report of each period, so as to obtain the preliminary estimate aggregation report of each period of the smallest target unit.

[0016] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping.

[0017] Fourthly, the present invention provides a storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The proposed method for collecting preliminary estimates for hydropower and water conservancy projects based on coding mapping has two main aspects. First, it designates the smallest target unit for collecting the estimated amount at the target stage as the target node in the hierarchical estimated estimate tree. This operation unifies the collection standards, avoids repeated corrections due to misunderstandings, and effectively reduces communication and error correction costs. Second, within the tree structure corresponding to the bill of quantities and the project estimated estimate list, an automatic identification algorithm for the estimated estimate collection path is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the estimated estimate collection target node. Therefore, this invention replaces the traditional manual verification and matching operation mode, effectively reducing manual operations, avoiding the risk of human mismatch, significantly simplifying the settlement process, and significantly improving the overall efficiency and data collection accuracy of project settlement. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to the present invention; Figure 2 This is a schematic diagram of the hydropower and water conservancy project budget collection system based on encoding mapping according to the present invention; Figure 3 This is a flowchart of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping in Embodiment 4 of the present invention; Figure 4 A schematic diagram of the contract bill of quantities in Embodiment 4 of the present invention; Figure 5 This is a schematic diagram illustrating the collection and analysis of contract quantity list data and feasibility study estimate data in Embodiment 4 of the present invention; Figure 6 This is a schematic diagram of the preliminary calculation and statistical collection in Embodiment 4 of the present invention; Figure 7 This is a schematic diagram of the structure of the electronic device of the present invention. Detailed Implementation

[0020] To further understand the content of this invention, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0021] Example 1: The flowchart of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping in this invention is as follows: Figure 1 As shown, the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to the present invention includes the following steps: S1. Obtain several contracts, wherein the contracts include a bill of quantities, and the bill of quantities includes several bill of quantities sub-items; S2. Obtain a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules for the target budget stage. S3. In the hierarchical budget tree, designate the smallest target unit for the budget amount collection in the target budget stage as the budget collection target node, and the hierarchy of the budget collection target node remains consistent. S4. Perform rule coding on the bill of quantities and the project budget list to obtain the rule coding results; S5. Parse the rule coding results to obtain the tree structure corresponding to the bill of quantities and the project budget list; S6. Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection paths is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes; S7. For each contract, calculate the progress settlement report for each period and compile the settlement amount for each period of the project bill of quantities sub-item; S8. Based on the many-to-one coding mapping relationship and the progress settlement reports of each period, the settlement amount of each period of the project bill of quantities sub-item of each contract is automatically collected to the smallest target unit corresponding to the budget tree of the hierarchical structure, and the budget collection report of each period of the smallest target unit is obtained.

[0022] Example 2: A schematic diagram of the hydropower and water conservancy project budget collection system based on encoding mapping of the present invention is shown below. Figure 2 As shown, the hydropower and water conservancy project budget collection system based on encoding mapping of the present invention includes: The first data acquisition module is used to acquire several contracts, the contracts including a bill of quantities, and the bill of quantities including several bill of quantities sub-items; The second data acquisition module is used to acquire a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules of the target budget stage. The node specification module is used to specify the smallest target unit for the collection of budgeted amounts in the target budgeting stage as the budget collection target node in the hierarchical budgeting tree, and the hierarchy of the budget collection target node remains consistent. The rule coding module is used to perform rule coding on the bill of quantities and the project budget list to obtain the rule coding results; The parsing module is used to parse the rule encoding results and obtain the tree structure corresponding to the bill of quantities and the project budget list; The coding mapping module is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the estimated budget target nodes within the tree structure corresponding to the bill of quantities and the project estimate list, using an automatic identification algorithm for the estimated budget collection path. The calculation module is used to calculate the progress settlement report for each period for each contract, and to calculate the settlement amount for each period of the project bill of quantities sub-items; The preliminary estimate aggregation module is used to automatically aggregate the settlement amount of each period of the project bill of quantities sub-item of each contract to the smallest target unit corresponding to the preliminary estimate tree of the hierarchical structure, based on the many-to-one coding mapping relationship and the progress settlement report of each period, so as to obtain the preliminary estimate aggregation report of each period of the smallest target unit.

[0023] Example 3: The present invention provides a method for compiling preliminary estimates for hydropower and water conservancy projects based on encoding mapping, comprising the following steps: S1. Obtain several contracts, wherein the contracts include a bill of quantities, and the bill of quantities includes several bill of quantities sub-items.

[0024] The bill of quantities includes the contract bill of quantities, the change order and claims bill of quantities, the price difference adjustment bill of quantities, and other bills of quantities. S2. Obtain a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules for the target budget stage.

[0025] The project budget list includes lists for different stages such as feasibility study budget, bidding and design budget, and management budget.

[0026] S3. In the hierarchical budget tree, specify the smallest target unit for the budget amount collection in the target budget stage as the budget collection target node, and keep the hierarchy of the budget collection target node consistent.

[0027] S4. Perform rule coding on the bill of quantities and the project budget list to obtain the rule coding results.

[0028] S5. Parse the rule coding results to obtain the tree structure corresponding to the bill of quantities and the project budget list.

[0029] S6. Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection paths is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes.

[0030] The encoding mapping relationship in this step can be manually reviewed and adjusted.

[0031] In this step, within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection paths is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes. Specifically: Obtain the contract name, perform engineering semantic matching between the contract name and the standard name of the parent category node of the target node in the budget collection tree, determine the range of the parent category node to which the contract belongs, and form a hierarchical constraint of the collection search space. Within the scope of the superior classification node to which the contract belongs, for each item in the bill of quantities, under the hierarchical constraints of the aggregation search space, all budget aggregation target nodes included in the scope are used as the candidate aggregation target set to extract the attribute information of the item in the bill of quantities. Based on attribute information, the comprehensive aggregation similarity between the bill of quantities sub-items and each candidate budget aggregation target node is calculated. The budget aggregation target node with the highest comprehensive aggregation similarity is determined as the final aggregation target of the bill of quantities sub-item, forming a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget aggregation target node.

[0032] In this step, the overall similarity is obtained by weighted summation of the text similarity of the project name in the bill of quantities and the matching degree of the project features.

[0033] In this step, the text similarity of the project name is obtained based on a semantic vector model of engineering terms trained on a corpus of hydropower and water conservancy engineering. The project feature matching degree is obtained by extracting key features of engineering location, material type and construction technology from the project description of the sub-items in the bill of quantities, and performing a structured comparison with the standard features of the target node of the budget collection.

[0034] S7. For each contract, calculate the progress settlement report for each period and compile the settlement amount for each period of the project bill of quantities sub-items.

[0035] S8. Based on the many-to-one coding mapping relationship and the progress settlement reports of each period, the settlement amount of each period of the project bill of quantities sub-item of each contract is automatically collected to the smallest target unit corresponding to the budget tree of the hierarchical structure, and the budget collection report of each period of the smallest target unit is obtained.

[0036] This step automatically aggregates the settlement amounts for each period of the bill of quantities sub-item for each contract to the smallest target unit corresponding to the hierarchical budget tree, specifically: Determine the contract settlement matrix and transformation matrix; Multiply the contract settlement matrix and the transformation matrix to obtain the preliminary calculation aggregation matrix; Using the budget aggregation matrix, the settlement amounts for each period of the project bill of quantities sub-items in each contract are automatically aggregated to the smallest target unit corresponding to the budget tree in the hierarchical structure.

[0037] The formula for calculating the approximate aggregation matrix is:

[0038] in, For the preliminary aggregation matrix, For the transformation matrix, For contract settlement matrix, k The number of sub-items in the bill of quantities. l The number of settlement cycles. w This is the smallest target unit corresponding to the preliminary calculation tree.

[0039] Transformation matrix The calculation formula is:

[0040] in, It is a Boolean matrix (0-1 matrix). For the bill of quantities, number k The settling relationship between the sub-item and the first smallest target unit corresponding to the budget tree (value is 0 or 1). For the bill of quantities, number k The item and the corresponding budget tree w The reducibility relation of the smallest target unit (with a value of 0 or 1).

[0041] Contract Settlement Matrix The calculation formula is:

[0042] in, For item 1 of the bill of quantities, in the... l Settlement amount within a settlement period For the bill of quantities, number k Item No. l Settlement amount within a settlement cycle.

[0043] After obtaining the budget collection reports for each period of the minimum target unit in this step, the data in the budget collection reports for each period of the minimum target unit are cumulatively calculated to obtain the cumulative calculation results. Based on the cumulative calculation results, it is determined whether the cumulative budget investment has exceeded the budget and an over-budget warning is issued.

[0044] Example 4: The method of the present invention will be described in detail below. The flowchart of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping is as follows: Figure 3 As shown, the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to the present invention includes the following steps: Step 1: After coding the bill of quantities and project budget list according to the rules, import them in batches into the hydropower and water conservancy project construction management system (hereinafter referred to as the system) through an EXCEL template to form a tree structure corresponding to the bill of quantities and project budget list.

[0045] Specifically, such as Figure 4 As shown, for the contract bill of quantities EXCEL template after the contract is signed, the basic fields "Original Code, Project Name, Unit, Quantity, Unit Price, Total Price" are retained. The hierarchical coding rule is as follows: list items are sorted by Arabic numerals, and list items are divided into levels by ".". After compilation, the system is imported to generate the corresponding tree structure of the bill of quantities and the project budget list. The coding and import of change order lists, price difference adjustment lists, and other lists are consistent with the principle of the contract list.

[0046] For feasibility study estimates, the basic fields of "number, feasibility study estimate code, project or cost name, investment, and percentage of total investment" are retained. The feasibility study estimate is also coded hierarchically according to the same coding rules as the contract bill of quantities. After compilation, it is imported into the system to generate the corresponding tree structure of the bill of quantities and project estimate list. The coding and import of bidding design estimates and management estimates follow the same principles as feasibility study estimates.

[0047] Step 2: Taking feasibility study estimates as an example, an automatic identification algorithm for estimate collection paths is used to establish a many-to-one coding mapping relationship between bill of quantities sub-items (hereinafter referred to as sub-items) and estimate collection target nodes.

[0048] The following is a detailed explanation of this step: A. Setting the target nodes for preliminary budget aggregation According to the "Regulations for the Compilation of Design Estimates for Hydropower Projects" (NB / T 11408-2023), the smallest target unit for collecting the estimate amount in the feasibility study stage is set at the expanded unit project level. Among them: The key project includes five expanded unit project nodes: KY-1.1 construction auxiliary works, KY-1.2 building works, KY-1.3 environmental protection and soil and water conservation works, KY-1.4 electromechanical equipment and installation works, and KY-1.5 metal structure equipment and installation works.

[0049] The compensation for land acquisition and resettlement includes two expanded unit project nodes: KY-2.1 compensation for the reservoir inundation impact area and KY-2.2 compensation for the construction area of ​​the hub project.

[0050] The independent cost component includes four expanded unit project nodes: KY-3.1 Project construction management fee, KY-3.2 Production preparation fee, KY-3.3 Scientific research, survey and design fee, and KY-3.4 Other taxes and fees.

[0051] The aforementioned 11 expanded unit project nodes are all target nodes for budget aggregation, and all bill of quantities items must ultimately be aggregated to one of these 11 nodes. The system pre-configures a feature terminology library for each node.

[0052] B. First-level aggregation: Contract-level coarse aggregation The goal of the first level of aggregation is to determine the scope of the three main components to which the contract as a whole belongs, thus forming hierarchical constraints on the aggregation search space.

[0053] Taking the contract "XX Hydropower Station Dam Civil Engineering and Metal Structure Installation Project Contract" as an example, the system obtains the contract name, extracts keywords such as "dam," "civil engineering," "metal structure," and "installation project" through word segmentation, and matches them with the feature word library of the three main components: Matching "key project": Matches "dam", "civil engineering", "metal structure", and "installation engineering", with a relevance score of 0.95; Matched with "Compensation for Land Acquisition and Resettlement for Construction": Score 0.05; Matching "Independent Costs": Score 0.05.

[0054] The system defines the scope of the contract's superior classification node as "hub project". The subsequent aggregation search space is constrained to the five nodes (KY-1.1 to KY-1.5) under the hub project, completely eliminating interference from the immigration and independence costs.

[0055] When the relevance of all sectors is below a preset threshold, a manual confirmation process is triggered.

[0056] C. Second-level aggregation: Sub-item-level refined aggregation The goal of the second-level aggregation is to automatically aggregate each item in the bill of quantities to a unique preliminary estimate aggregation target node within the scope defined by the first-level aggregation.

[0057] The second level of aggregation specifically includes: a. Settlement space constraints: The five nodes (KY-1.1 to KY-1.5) under the "hub project" are used as the candidate set of settling targets.

[0058] b. Unit pre-filtering: When the unit of a sub-item is significantly different from the typical unit of a candidate node, the node is downgraded or removed.

[0059] c. Comprehensive Similarity Calculation: This is obtained by weighted summation of the text similarity of project names in the bill of quantities sub-items and the matching degree of project features. Specifically, the text similarity of project names is calculated based on a semantic vector model of engineering terms trained on a corpus of hydropower and water conservancy engineering; the matching degree of project features is obtained through structured comparison of key features extracted from engineering locations, material types, and construction techniques; and the weights are dynamically adjusted according to the descriptive features of the bill of quantities sub-items. Industry knowledge correction is also introduced: based on the engineering nature (main project or temporary auxiliary project) implied in the contract names in the first-level aggregation, the matching scores of construction auxiliary projects (KY-1.1) in candidate nodes are differentiated to avoid cross-nature mis-aggregation caused by relying solely on the matching of bill of quantities sub-item names.

[0060] d. Determining the aggregation result: The node with the highest overall aggregation similarity is determined as the final aggregation target.

[0061] D. Confidence assessment and human intervention When the confidence level is higher than the high threshold (e.g., 0.85), it is automatically adopted; when it is lower than the low threshold (e.g., 0.60), the top three candidate nodes are recommended for the user to choose from; when it is in between, it is marked as "pending review".

[0062] E. Incremental Learning and Optimization of Settlement Models The system records manually confirmed or corrected mapping relationships as labeled samples and periodically performs incremental training on the semantic vector model and weight parameters.

[0063] The following is a specific example of aggregation: by Figure 5 Taking the bill of quantities and preliminary estimate data shown as an example, the first-level aggregation of this contract has determined the search space to be the 5 nodes (KY-1.1 to KY-1.5) under the key project, and the aggregation of each sub-item is as follows: Example 1: Earthwork open excavation and rock excavation items – aggregated into KY-1.2 Construction Engineering No. 1.1.1 "Open excavation of earthwork" (unit: m³), ​​No. 1.1.2 "Open excavation of rockwork" (unit: m³).

[0064] Candidate nodes are KY-1.1 to KY-1.5. Unit pre-filtering reduces the weight of KY-1.5 (typical units t, m²). In terms of text similarity, "earthwork excavation" is similar to "earthwork excavation" (serving temporary facilities) in KY-1.1 construction auxiliary engineering, and also similar to "earthwork excavation" (serving the main building) in KY-1.2 building engineering, as the two have the same name.

[0065] At this point, industry knowledge correction comes into play: based on the contract name "Dam Civil Engineering and Metal Structure Installation Project" in the first-level aggregation set—which is a main project contract, not a temporary auxiliary project contract—the system adjusts the matching score of KY-1.1 (construction auxiliary project) by reducing its weight.

[0066] Overall similarity score: KY-1.2 score 0.94, KY-1.1 score 0.40, KY-1.5 score 0.15. The system automatically categorized it as KY-1.2 Construction Engineering.

[0067] Example 2: Shotcrete and Reinforcing Steel Items – Collected under KY-1.2 Building Engineering Item No. 1.2.1 "Plain Shotcrete C25" (unit: m³), ​​1.2.2 "Shotcrete C25 with Wire Mesh" (unit: m³), ​​1.2.3 "Wire Mesh Reinforcing Steel" (unit: t).

[0068] Similarly, shotcrete and reinforcing mesh may also appear in KY-1.1 construction auxiliary engineering (serving temporary slope support), but industry knowledge correction reduces the weight of KY-1.1 based on the nature of the main project in the contract. Meanwhile, the unit t for "reinforcing mesh" in feature matching is consistent with the unit t for metal structures in KY-1.5, but the features "reinforcing bars" and "steel" differ. Combining this with text similarity, the system determines that it belongs to the category of building construction.

[0069] Overall similarity score: KY-1.2 score 0.93, KY-1.1 score 0.42, KY-1.5 score 0.35. The system automatically categorized it as KY-1.2 Construction Engineering.

[0070] Example 3: Q345R steel fabrication and installation item – aggregated under KY-1.5 Metal Structure Equipment and Installation Engineering Numbered 10.1 to 10.6, a total of 6 sub-items, named "Q345R steel fabrication and installation, wall thickness 22-34mm" (unit: t). After unit pre-filtering, the feature matching material "Q345R steel" and process "fabrication and installation" both fall under the category of metal structures; the comprehensive score KY-1.5 is 0.97, and KY-1.2 is 0.20. The system automatically aggregates all 6 sub-items into KY-1.5, forming a "many-to-one" mapping.

[0071] Example 5: Hydraulic machinery and equipment and pipeline pre-embedded items – collected under KY-1.4 Mechanical and electrical equipment and installation engineering Items 12.1.1.1 to 12.1.1.3, comprising three sub-items, are named "Hydraulic Machinery Equipment and Pipeline Pre-embedding." The text similarity is highly correlated with KY-1.4 "Mechanical and Electrical Equipment and Installation Engineering"; the overall score is 0.93 for KY-1.4, 0.25 for KY-1.2, and 0.20 for KY-1.5. The system automatically aggregates all nine sub-items under KY-1.4 "Mechanical and Electrical Equipment and Installation Engineering," forming a "many-to-one" mapping.

[0072] Example 6: Sub-items that cannot be automatically grouped Suppose that for a sub-item, "Temporary Drainage Pipe Installation" (unit: meters), the highest overall similarity among candidate nodes is only 0.52, which is below the low threshold of 0.60. The system marks this sub-item as "Cannot be automatically aggregated," and a selection interface pops up. Based on the first-level aggregation results, the system recommends the top three candidate nodes (KY-1.1, KY-1.2, KY-1.4) under the Hub Project section for the user to manually select. After the user confirms it as KY-1.1 construction auxiliary project, the system records this mapping relationship as a positive sample and adds it to the database for subsequent incremental training.

[0073] Step 3: For each contract, the system automatically generates progress settlement reports for each period. Specifically, the calculations are performed for four project categories: construction, technical services, equipment and materials, and virtual projects.

[0074] For construction contracts, the system initiates a change order normally within a given calendar month. The measured items must be selected from the bill of quantities. Once approved by the supervisor and owner, the change order process is complete. At the end of the month, the system initiates a measurement summary process, selecting the change orders to be included in the month's summary. Based on the bill of quantities structure, the system automatically generates a measurement summary table by classifying and summarizing the measurement items from different change orders. Subsequently, the system initiates a progress settlement process, linking the corresponding measurement summary table. Based on the same bill of quantities structure, it automatically calculates and generates a detailed progress settlement report using a method of horizontal quantity-price multiplication and vertical accumulation. Deductions and rebates, as well as migrant worker wages, are entered into the audit form to calculate the net payment amount for the month. The specific algorithm is as follows:

[0075]

[0076] in, Net settlement amount; For project settlement price; For prepayment; For deductions; To refund the money; n represents the quantity of work order items in each work order form; n is the number of work order items for a specific work order item. m represents the unit price of each item in the bill of quantities; m represents the quantity of each item in the bill of quantities involved in the settlement this month. This is the cumulative amount of the settlement price for which taxes need to be calculated; This refers to the tax rate.

[0077] For contracts related to technical services and equipment / materials, there is no process for calculating the quantity of work in the bill of quantities. The settlement amount for the current period can be manually entered and then calculated. Non-contractual virtual expenditure data such as corporate management fees and interest should be entered periodically, and each item in the bill of quantities can be set as a single item.

[0078] Step 4: Based on the coding mapping relationship in Step 2 and the progress settlement report in Step 3, an automatic budget aggregation algorithm is used to automatically aggregate the settlement amounts of each period for the bill of quantities sub-items of each contract to the smallest target unit, forming a budget aggregation report for each period of the smallest target unit, thus realizing the budget aggregation of hydropower and water conservancy projects. Figure 6 As shown.

[0079] Specifically, the automatic aggregation algorithm is as follows: multiply the bill of quantities settlement matrix by the transformation matrix to obtain the preliminary estimate aggregation matrix, and use the preliminary estimate aggregation matrix to realize the preliminary estimate aggregation of hydropower and water conservancy projects.

[0080] Taking the feasibility study budget collection as an example, this step is introduced. The settlement reports for each period of the contract are shown in Table 1.

[0081] Table 1. Settlement Completion Status of Bill of Quantities at Each Stage

[0082] Corresponding contract settlement matrix :

[0083] If a certain item in the bill of quantities corresponds to a certain smallest target unit in the preliminary estimate, the value is 1 if there is a relevance relationship, and 0 if there is no relationship. The relevance conversion table is shown in Table 2.

[0084] Table 2. Preliminary Estimate Conversion Table

[0085] Corresponding transformation matrix :

[0086] Based on the contract settlement information in Table 1 and the data collection information in Table 2, the system automatically collects the data. The data collection completion status is shown in Table 3.

[0087] Table 3. Completion Status of Budget Collection

[0088] Corresponding approximate aggregation matrix :

[0089] The above demonstrates the process of collecting settlement data into feasibility study estimates. The same principle can be used to collect settlement data into budget structures such as bidding design estimates and management estimates. The only difference is that the project name, level, and amount of the smallest target unit are different.

[0090] Step 5: Based on the summarization results of Step 4, the system automatically accumulates the estimated investment data for the two periods, determines whether the estimated investment exceeds the budget, and automatically issues an over-budget warning message, as shown in Table 4.

[0091] Table 4. Over-premium warning status table

[0092] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0093] Example 5: Please see Figure 7 As shown, the present invention also provides an electronic device 100 for a method of collecting preliminary estimates for hydropower and water conservancy projects based on encoding mapping; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0094] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the hydropower and water conservancy project budget collection method based on encoding mapping described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0095] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0096] The memory 101 in the electronic device 100 stores multiple instructions to implement a method for compiling preliminary estimates of hydropower and water conservancy projects based on encoding mapping, and the processor 102 can execute the multiple instructions to achieve the following: Obtain several contracts, wherein the contracts include a bill of quantities, and the bill of quantities includes several bill of quantities sub-items; Obtain a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules for the target budget stage. In the hierarchical budget tree, the smallest target unit for the collection of budget amounts in the target budget stage is designated as the budget collection target node, and the hierarchy of the budget collection target node remains consistent. The bill of quantities and the project budget are coded according to rules to obtain the rule coding results; The rule coding results are parsed to obtain the tree structure corresponding to the bill of quantities and the project budget list; Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection path is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes. For each contract, calculate the progress settlement report for each period and compile the settlement amount for each period of the project bill of quantities sub-item; Based on the many-to-one coding mapping relationship and the progress settlement reports of each period, the settlement amount of each period of the project bill of quantities sub-item of each contract is automatically collected to the smallest target unit corresponding to the budget tree of the hierarchical structure, so as to obtain the budget collection report of each period of the smallest target unit.

[0097] Example 6: If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0098] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping, characterized in that, Includes the following steps: Obtain several contracts, wherein the contracts include a bill of quantities, and the bill of quantities includes several bill of quantities sub-items; Obtain a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules for the target budget stage. In the hierarchical budget tree, the smallest target unit for the collection of budget amounts in the target budget stage is designated as the budget collection target node, and the hierarchy of the budget collection target node remains consistent. The bill of quantities and the project budget are coded according to rules to obtain the rule coding results; The rule coding results are parsed to obtain the tree structure corresponding to the bill of quantities and the project budget list; Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection path is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes. For each contract, calculate the progress settlement report for each period and compile the settlement amount for each period of the project bill of quantities sub-item; Based on the many-to-one coding mapping relationship and the progress settlement reports of each period, the settlement amount of each period of the project bill of quantities sub-item of each contract is automatically collected to the smallest target unit corresponding to the budget tree of the hierarchical structure, so as to obtain the budget collection report of each period of the smallest target unit.

2. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 1, characterized in that, The encoding mapping relationship supports manual review and adjustment.

3. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 1, characterized in that, Within the tree structure corresponding to the bill of quantities and the project budget list, an automatic identification algorithm for budget collection paths is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget collection target nodes. Specifically: Obtain the contract name, perform engineering semantic matching between the contract name and the standard name of the parent category node of the target node in the budget collection tree, determine the range of the parent category node to which the contract belongs, and form a hierarchical constraint of the collection search space. Within the determined range of the superior classification node to which the contract belongs, for each item in the bill of quantities, under the hierarchical constraints of the aggregation search space, all budget aggregation target nodes included in the range are used as the candidate aggregation target set to extract the attribute information of the item in the bill of quantities. Based on the attribute information, the comprehensive aggregation similarity between the bill of quantities sub-items and each candidate budget aggregation target node is calculated. The budget aggregation target node with the highest comprehensive aggregation similarity is determined as the final aggregation target of the bill of quantities sub-item, thus forming a many-to-one coding mapping relationship between the bill of quantities sub-items and the budget aggregation target node.

4. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 3, characterized in that, The overall similarity is obtained by weighted summation of the text similarity of project names and the matching degree of project features in the bill of quantities sub-items.

5. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 4, characterized in that, The text similarity of the project name is obtained based on the semantic vector model of engineering terms trained on the professional corpus of hydropower and water conservancy engineering; the project feature matching degree is obtained by extracting key features of engineering parts, material types and construction technology from the project description of the sub-items of the bill of quantities and comparing them in a structured manner with the standard features of the target node of the budget collection.

6. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 1, characterized in that, The process of automatically aggregating the settlement amounts for each period of the project bill of quantities sub-items in each contract to the smallest target unit corresponding to the hierarchical budget tree is as follows: Determine the contract settlement matrix and transformation matrix; Multiply the contract settlement matrix and the transformation matrix to obtain the preliminary calculation aggregation matrix; Using the budget aggregation matrix, the settlement amounts for each period of the project bill of quantities sub-items in each contract are automatically aggregated to the smallest target unit corresponding to the hierarchical budget tree; The formula for calculating the approximate aggregation matrix is ​​as follows: in, For the approximate aggregation matrix, For the transformation matrix, For contract settlement matrix, k The number of sub-items in the bill of quantities. l The number of settlement cycles. w This is the smallest target unit corresponding to the preliminary calculation tree; Transformation matrix The calculation formula is: in, For the bill of quantities, number k The reducible relationship between sub-items and the first smallest target unit corresponding to the budget tree. For the bill of quantities, number k The item and the corresponding budget tree w The reducibility relationship of the smallest target unit; Contract settlement matrix The calculation formula is: in, For item 1 of the bill of quantities, in the... l Settlement amount within a settlement period For the bill of quantities, number k Item No. l Settlement amount within a settlement cycle.

7. The method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping according to claim 1, characterized in that, After obtaining the budget summary reports for each period of the minimum target unit, the data in the budget summary reports for each period of the minimum target unit are cumulatively calculated to obtain the cumulative calculation results. Based on the cumulative calculation results, it is determined whether the cumulative budget investment has exceeded the budget and an over-budget warning is issued.

8. A system for collecting preliminary estimates for hydropower and water conservancy projects based on encoding mapping, characterized in that, include: The first data acquisition module is used to acquire several contracts, the contracts including a bill of quantities, and the bill of quantities including several bill of quantities sub-items; The second data acquisition module is used to acquire a project budget list, which is represented by a hierarchical budget tree. The hierarchical budget tree is compiled according to the compilation rules of the target budget stage. The node specification module is used to specify the smallest target unit for the collection of budgeted amounts in the target budgeting stage as the budget collection target node in the hierarchical budgeting tree, and the hierarchy of the budget collection target node remains consistent. The rule coding module is used to perform rule coding on the bill of quantities and the project budget list to obtain the rule coding results; The parsing module is used to parse the rule encoding results and obtain the tree structure corresponding to the bill of quantities and the project budget list; The coding mapping module is used to establish a many-to-one coding mapping relationship between the bill of quantities sub-items and the estimated budget target nodes within the tree structure corresponding to the bill of quantities and the project estimate list, using an automatic identification algorithm for the estimated budget collection path. The calculation module is used to calculate the progress settlement report for each period for each contract, and to calculate the settlement amount for each period of the project bill of quantities sub-items; The preliminary estimate aggregation module is used to automatically aggregate the settlement amount of each period of the project bill of quantities sub-item of each contract to the smallest target unit corresponding to the preliminary estimate tree of the hierarchical structure, based on the many-to-one coding mapping relationship and the progress settlement report of each period, so as to obtain the preliminary estimate aggregation report of each period of the smallest target unit.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for collecting preliminary estimates of hydropower and water conservancy projects based on encoding mapping as described in any one of claims 1 to 7.

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