Engineering output value determination method and device, electronic equipment and readable storage medium

Abstract

This disclosure relates to the field of engineering data management technology, and provides a method, apparatus, electronic device, and readable storage medium for determining engineering output value. The method includes: classifying and processing sub-item engineering data based on process status data to obtain target sub-item engineering data; associating the target sub-item engineering data with bill of quantities data to obtain an association table; matching engineering progress data and bill of quantities data based on the association table to obtain target bill of quantities data; and performing value accounting processing on the target bill of quantities data and engineering progress data to obtain the target engineering output value. This improves the systematicness and accuracy of data processing, strengthens the correlation between engineering progress and value accounting, enhances the timeliness and reliability of engineering output value determination, strengthens the degree of data collaboration between systems, and improves the efficiency and accuracy of engineering output value determination.

Description

Technical Field

[0001] This disclosure relates to the field of engineering data management technology, and in particular to a method, apparatus, electronic device and readable storage medium for determining engineering output value. Background Technology

[0002] In real estate development project management, conventional output value declaration and payment rely on manual on-site collection of progress data, manual comparison and calculation with contract lists, and multiple rounds of manual review. However, this method is not only inefficient and prone to errors, but also creates data silos because progress, cost, and payment data are stored in isolated systems, resulting in difficulties in information collaboration, poor real-time performance, and difficulty in achieving real-time data connectivity and accurate correlation.

[0003] It is evident that existing technologies suffer from problems such as low efficiency, poor accuracy, difficulty in coordination, and high error rate in determining engineering output value due to insufficient data collaboration between systems, low automation in output value calculation, and complex review processes. Summary of the Invention

[0004] In view of this, the present disclosure provides a method, apparatus, electronic device and readable storage medium for determining engineering output value, in order to solve the problems of low efficiency, poor accuracy, difficulty in coordination and high error rate in determining engineering output value due to insufficient data collaboration between systems, low degree of automation in output value calculation and complex review process in the prior art.

[0005] A first aspect of this disclosure provides a method for determining engineering output value, comprising: classifying and processing sub-item engineering data based on process status data to obtain target sub-item engineering data; associating the target sub-item engineering data with engineering bill of quantities data to obtain an association table; matching engineering progress data and engineering bill of quantities data based on the association table to obtain target bill of quantities data; and performing value accounting processing on the target bill of quantities data and engineering progress data to obtain the target engineering output value.

[0006] In some embodiments, the target sub-item project data includes sub-item structure data, and the project list data includes list structure data; the target sub-item project data and the project list data are associated to obtain an association table, including: performing dimensional matching processing on the sub-item structure data and the list structure data to obtain structure mapping data; and performing relationship solidification processing on the structure mapping data to obtain an association table.

[0007] In some embodiments, matching project progress data and project list data based on a relationship table to obtain target list data includes: performing proportional parsing on the project progress data to obtain progress proportion data; and performing index filtering on the progress proportion data and project list data based on the relationship table to obtain target list data.

[0008] In some embodiments, classifying and processing the sub-item project data based on process status data to obtain target sub-item project data includes: performing completion status judgment processing on the process status data to obtain completion status data; and performing attribution mapping processing on the completion status data and sub-item project data to obtain target sub-item project data.

[0009] In some embodiments, the project progress data includes project quantity ratio data, and the target list data includes list value data; the target list data and project progress data are subjected to value accounting processing to obtain the target project output value, including: extracting the list value data to obtain the value data to be accounted for; and performing weighted calculation processing on the value data to be accounted for and the project quantity ratio data to obtain the target project output value.

[0010] In some embodiments, before classifying the sub-item project data based on the process status data to obtain the target sub-item project data, the method further includes: performing noise filtering on the initial sensing data to obtain initial process data; and performing status marking on the initial process data to obtain process status data.

[0011] In some embodiments, performing dimensional matching processing on the component structure data and the list structure data to obtain structure mapping data includes: performing hierarchical decomposition processing on the component structure data to obtain component hierarchical data; performing granularity adaptation processing on the list structure data to obtain list granular data; and performing hierarchical mapping processing on the component hierarchical data and the list granular data to obtain structure mapping data.

[0012] A second aspect of this disclosure provides an apparatus for determining engineering output value, comprising: a first processing module for classifying and processing sub-item engineering data based on process status data to obtain target sub-item engineering data; a second processing module for associating the target sub-item engineering data and engineering list data to obtain an association table; a third processing module for matching engineering progress data and engineering list data based on the association table to obtain target list data; and a fourth processing module for performing value accounting processing on the target list data and engineering progress data to obtain the target engineering output value.

[0013] A third aspect of this disclosure provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0014] A fourth aspect of this disclosure provides a readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0015] The beneficial effects of this disclosed embodiment compared with the prior art are as follows: By using process status data as the processing basis, the original sub-item project data is classified and processed to output target sub-item project data; a mapping relationship is established between the target sub-item project data and the bill of quantities data to form an association table; based on this association table, the dynamically collected project progress data is matched with the bill of quantities data to generate target bill of quantities data; and value accounting is performed by combining the target bill of quantities data and the project progress data to obtain the target project output value. In this way, the systematicness and accuracy of data processing are improved, the correlation between project progress and value accounting is strengthened, the timeliness and reliability of project output value determination are improved, the degree of data collaboration between systems is enhanced, and the efficiency and accuracy of project output value determination are improved. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario of an embodiment of this disclosure; Figure 2 This is a flowchart illustrating a method for determining engineering output value provided in an embodiment of this disclosure; Figure 3 This is a flowchart illustrating another method for determining engineering output value provided in this embodiment of the disclosure; Figure 4 This is a schematic diagram of the structure of an engineering output value determination device provided in an embodiment of this disclosure; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, so as to provide a thorough understanding of the embodiments of this disclosure. However, those skilled in the art will understand that this disclosure may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this disclosure with unnecessary detail.

[0019] It should be noted that the user information (including but not limited to terminal device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0020] The following will describe in detail, with reference to the accompanying drawings, a method and apparatus for determining engineering output value according to an embodiment of the present disclosure.

[0021] Figure 1 This is a schematic diagram illustrating an application scenario of an embodiment of this disclosure. The application scenario may include terminal devices 1, 2, and 3, server 4, and network 5.

[0022] Terminal devices 1, 2, and 3 can be hardware or software. When terminal devices 1, 2, and 3 are hardware, they can be various electronic devices with displays and supporting communication with server 4, including but not limited to smartphones, tablets, laptops, and desktop computers. When terminal devices 1, 2, and 3 are software, they can be installed in the aforementioned electronic devices. Terminal devices 1, 2, and 3 can be implemented as multiple software programs or software modules, or as a single software program or software module; this disclosure does not limit this. Furthermore, various applications can be installed on terminal devices 1, 2, and 3, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0023] Server 4 can be a server that provides various services, such as a backend server that receives requests sent by terminal devices with which it has established communication connections. This backend server can receive and analyze the requests sent by the terminal devices and generate processing results. Server 4 can be a single server, a server cluster consisting of several servers, or a cloud computing service center. This disclosure embodiment does not limit this.

[0024] It should be noted that server 4 can be either hardware or software. When server 4 is hardware, it can be various electronic devices that provide various services to terminal devices 1, 2, and 3. When server 4 is software, it can be multiple software programs or software modules that provide various services to terminal devices 1, 2, and 3, or it can be a single software program or software module that provides various services to terminal devices 1, 2, and 3. This disclosure does not limit the scope of the embodiments.

[0025] Network 5 can be a wired network using coaxial cable, twisted pair, and fiber optic connection, or it can be a wireless network that enables interconnection of various communication devices without wiring, such as Bluetooth, Near Field Communication (NFC), and Infrared. This disclosure does not limit the scope of the network.

[0026] Users can establish a communication connection with server 4 via network 5 through terminal devices 1, 2, and 3 to receive or send information. Specifically, server 4 can acquire process status data, sub-item project data, and project list data through terminal devices 1, 2, and 3. Using process status data as the processing basis, it performs classification processing on the original sub-item project data and outputs target sub-item project data. A mapping relationship is established between this target sub-item project data and the project list data to form a correlation table. Based on this correlation table, dynamically collected project progress data is matched with the project list data to generate target project list data. Finally, value accounting is performed by combining the target project list data and the project progress data to obtain the target project output value.

[0027] It should be noted that the specific types, quantities, and combinations of terminal devices 1, 2, and 3, server 4, and network 5 can be adjusted according to the actual needs of the application scenario, and this disclosure embodiment does not impose any restrictions on this.

[0028] Figure 2 This is a flowchart illustrating a method for determining engineering output value provided in an embodiment of this disclosure. Figure 2 The method for determining the output value of an engineering project can be determined by Figure 1 The server executes this. For example... Figure 2 As shown, the method for determining the output value of this project includes: S201, classify and process the sub-item project data based on the process status data to obtain the target sub-item project data.

[0029] Specifically, process status data can be data that characterizes the completion status of one or more construction processes. This process status data can be used to characterize whether a specific process has been completed. It is the starting point and basis for triggering subsequent data processing. Process status data can be generated by data acquisition equipment deployed at the construction site, such as sensors that monitor the operating status of equipment, or by completion confirmation information submitted by construction personnel through smart terminals. The corresponding signals are judged logically, and the corresponding process status data is generated when the preset completion conditions are met.

[0030] Furthermore, standard process information for a specified project, i.e., process status data, can be obtained from the process library of the central database. This includes, but is not limited to, process name, quality requirements, and planned duration, providing a benchmark for determining and / or recording process status.

[0031] In addition, the sub-item project data can be data organized based on the sub-item project division standards of building construction projects. This sub-item project database includes the codes and / or names of sub-items and hierarchical structure information, etc., which are not limited here. The sub-item project data can be used as the target framework for data classification to receive and integrate progress information from different processes. This sub-item project data can be provided through an external engineering management system via a data interface, or it can be static data pre-generated by the system based on the contract list and project structure.

[0032] Furthermore, based on the standards for dividing sub-items into work items, the amounts of each item in the contract list can be decomposed and aggregated under the corresponding sub-item work item nodes, forming structured sub-item work item data that corresponds to the sub-item work item system.

[0033] Furthermore, classification processing can be used to map and integrate discrete, process-based status information into a data structure based on sub-item projects, according to predefined rules. When a process status data is marked as completed, the process can be assigned to its corresponding sub-item project node according to the mapping relationship to obtain the target sub-item project data.

[0034] Furthermore, this mapping relationship can be established during project initialization based on the process attributes in the process library and the sub-item engineering division standards to ensure the accuracy of data association.

[0035] Furthermore, the target sub-item project data can be data generated through classification processing. This target sub-item project data can be used to characterize the sub-item projects that have been completed by existing related processes. The target sub-item project data can be stored in temporary memory or persistent database, and a timestamp and project identifier can be attached to provide a clear and well-defined input for subsequent calls.

[0036] Furthermore, the results of the classification process, including the identification of sub-items, the list of associated completed processes and their completion times, can be stored in a specific database table, and indexes can be used to ensure data retrieval and traceability.

[0037] For example, in a residential building construction project, the standard process set for the project can be retrieved from the process library of the central database, including processes such as "foundation earthwork excavation," "foundation cushion layer pouring," and "basement slab reinforcement binding." At the construction site, when the "foundation cushion layer pouring" process is completed, the operation sensors of the concrete mixing plant stop working and upload their status. Simultaneously, the construction worker can confirm completion via a smart terminal application. Upon receiving the signal, logical judgments can be used to determine if the completion conditions are met, generating process status data indicating that "foundation cushion layer pouring" has been completed. Pre-defined mapping relationships can include classifying the "foundation cushion layer pouring" process under the "concrete foundation" sub-section of the "foundation and foundation engineering" division. Based on this mapping relationship, the stored static sub-item engineering data, including structures such as "foundation and foundation engineering" and "main structure engineering," can be categorized. The completed process status information can be integrated into the corresponding engineering node to obtain target sub-item engineering data. This target sub-item engineering data can represent the completion of existing processes under the "foundation and foundation engineering - concrete foundation" node.

[0038] This application embodiment obtains process status data and sub-item project data from the process library of a central database, and integrates the process status data into the sub-item project data structure based on predefined mapping relationships to obtain the target sub-item project data. This enhances the accuracy of the correlation between process status data and sub-item project data; improves the structuring and integration efficiency of project progress information; enhances the automation and real-time performance of data classification; optimizes the traceability and query efficiency of project management data; strengthens the refinement of construction progress management; improves the efficiency of progress data collection and preliminary processing; ensures the accuracy and consistency of the correlation between progress information and project structure; and enhances the integration and collaboration capabilities of project data.

[0039] S202, perform correlation processing on the target sub-item project data and the bill of quantities data to obtain the correlation table.

[0040] Specifically, the bill of quantities data can be detailed cost data obtained by breaking down the project according to the contract and the structure of the project. This bill of quantities data can be used to constitute the detailed costs of the total project cost and provide a monetary benchmark for output value calculation. This bill of quantities data can be structured data generated by reading the total contract list through the cost management system and mapping and decomposing the bill of quantities items with the data codes of the sub-items of the building construction project based on the sub-item division standards.

[0041] Furthermore, the target sub-item project data includes, but is not limited to, sub-item project codes, project names, and / or corresponding completed work process identifiers; the project list data includes, but is not limited to, list item codes, list item names, corresponding sub-item project codes, contract unit prices, contract quantities, and / or total prices.

[0042] In addition, association processing can be used to establish a correspondence between two different sources of data, thereby achieving the matching of schedule data and cost data. This association processing can use the sub-item project code or name as a key field to perform matching processing between the target sub-item project data and the bill of quantities data, and obtain an association table.

[0043] Furthermore, the matching process may specifically include traversing each entry in the target sub-item project data and extracting its sub-item project code; searching for all list items with the same sub-item project code in the project list data; when a matching item is found, a link relationship can be established between the target sub-item project entry and the corresponding list item entry, thereby ensuring that each sub-item project data representing the progress completion status can find its cost basis in the contract.

[0044] Furthermore, the relationship table can be a result table of the corresponding data. This relationship table can represent the cost item corresponding to each progress unit. This relationship table can write each successfully matched pair of target sub-item project and list item relationship as a record row into a new data table.

[0045] Furthermore, the fields included in this association table may include the target sub-item project code, the target sub-item project name, the corresponding list item code, the list item name, the contract amount, and / or the association establishment time, etc., without limitation here. This association table can be indexed and stored by project number or contract number.

[0046] For example, in a residential development project, based on the completion confirmation information reported by the on-site smart terminal, the completion of the foundation earthwork excavation process can be identified and mapped to the foundation earthwork excavation node under the earthwork engineering of the sub-item project. This can generate target sub-item project data, which includes codes, names, etc. The project general contracting contract list can be pre-divided based on national standard list specifications. The contract amount for the foundation earthwork excavation item in the list can be a specific value. When performing association processing, the code can be used as a key field for matching. The foundation earthwork excavation engineering node representing the progress completion can be associated with the corresponding foundation earthwork excavation list item in the contract, and an association relationship table record can be generated. This record can include the correspondence between the foundation earthwork excavation engineering node and the specific contract list item and its contract amount.

[0047] This application embodiment establishes a precise and automated correspondence between schedule data and cost data by associating target sub-item project data with bill of quantities data and generating an association table. This simplifies the preliminary data processing flow for output value accounting, promotes data collaboration between project schedule management and cost management, and improves the automation level and accuracy of project data association processing. It also improves the efficiency and reliability of multi-source heterogeneous data fusion and enhances the collaboration capability and data consistency between project schedule information and cost information.

[0048] S203, Based on the relationship table, match the project progress data and the project list data to obtain the target list data.

[0049] Specifically, project progress data can be a set of information representing the actual completion status of a project at a specific point in time or within a time period. This project progress data can be used to represent specific numerical values ​​of the project's progress. This project progress data can be obtained by interacting with data interfaces of external systems, requesting and acquiring data based on preset strategies, and can be used to represent the percentage of progress in terms of sub-projects.

[0050] In addition, matching processing can be used to find and establish corresponding relationships between two or more datasets based on predefined association rules. This matching processing can identify the specific sub-items of the current project progress data through the association table, and then locate one or more project list data sub-items that are bound to the sub-item.

[0051] Furthermore, the matching process may specifically include reading project progress data, extracting sub-item project identifiers from the project progress data, querying the sub-item project identifier in the association table, and retrieving all list items associated with the identifier and their amount information from the project list data based on the query results.

[0052] Furthermore, the matching process can traverse all the acquired project progress data entries. For each project progress data entry containing a specific sub-item project identifier and the corresponding percentage of progress, the sub-item project identifier can be used as the key to retrieve the data in the association table. After retrieval, the association table returns the unique number of one or more project list sub-items bound to it. Based on this number, the corresponding detailed information of the list sub-item is extracted from the structured project list data pool, including but not limited to the sub-item name, unit of measurement, unit price and / or total amount.

[0053] The target list data can be a subset of the engineering list data related to the current project progress, which is output through matching processing. This target list data can be used to filter and aggregate all list items corresponding to the actual completion progress within the current reporting period, ensuring the relevance and accuracy of output value calculation. This target list data can be obtained by filtering and screening the full engineering list data.

[0054] Furthermore, the successfully matched and extracted project list item information can be integrated into a new data set, namely the target list data. Each item in the target list data is associated with the source project progress item and retains the original monetary information.

[0055] For example, in the monthly output value declaration of a large residential development project, the output value calculation process can be triggered at the end of each month. The progress data of each sub-item of the project up to the current month can be obtained from the project department's daily report system via an interface. For example, the underground structure project is 100% complete, the main structure's fifth floor slab is 80% complete, and the masonry work is 30% complete, thus forming the project progress data. The project list data, which has been broken down based on the sub-item project standards, can be called. This project list data can include corresponding list items and amounts for the underground structure, each floor of the main structure, and the masonry work. A pre-generated association table can include the correspondence between the underground structure project identifier and sub-items in the project list such as earthwork excavation, foundation pad, and waterproofing layer. The project progress data can be matched with the project list data. For example, the completion of the underground structure project can be matched to multiple project list sub-items such as earthwork excavation and foundation pad through the association table. Detailed information of the project list sub-items can be extracted to obtain the set of all list items for which the output value needs to be calculated this month, i.e., the target list data.

[0056] This application embodiment obtains project progress data representing the percentage of progress of individual project items from an external system through a data interface based on a preset strategy; performs matching processing based on a predefined association table, extracts the project item identifiers from the project progress data, queries the association table for the project item identifier, and retrieves and extracts relevant list item details from the structured list data based on the returned corresponding list item number; iterates through all project progress data entries to complete the matching, and integrates the extracted list item information into the target list data. This enhances the relevance and accuracy of output value calculation; improves the matching efficiency between project progress data and list data; and increases the automation level of data processing and the consistency of results.

[0057] S204 performs value accounting on the target list data and project progress data to obtain the target project output value.

[0058] Specifically, the value accounting process can be a data processing procedure that combines the monetary information in the target list data with the progress percentage in the project progress data, and executes a preset calculation logic to obtain the monetized value result. This value accounting process can include reading the amount corresponding to each item in the target list data, obtaining the percentage of progress in the project progress data that matches the sub-item of the project to which the item belongs, multiplying the amount by the percentage of progress based on a predetermined calculation method to obtain the completed output value of the item at the current progress, iterating through all the target list data, repeating the above multiplication operation for each item, and summing all the calculation results to obtain the cumulative completed output value of the contract or project at the current time node, i.e., the target project output value.

[0059] Furthermore, the predetermined calculation formula can be configured according to the cost type or management rules. For example, for fixed unit price types, the calculation can be performed by multiplying the unit price of the bill of quantities item by the completed work quantity calculated based on the project progress data.

[0060] Furthermore, after the cumulative calculation of the target project output value is completed, the output value result can be associated and bound with the corresponding cost number, calculation timestamp, and progress value of each sub-item of the project on which it is based, and stored in the output value result database table for subsequent application, review and retrieval.

[0061] The target project output value can be calculated by applying the corresponding project progress data to the target list data that is associated with the completion status of the work processes. It can be used to represent the total monetary value of the work completed in the project at a specific point in time.

[0062] For example, in a residential development project, a sub-item of the project could be the concrete pouring of the second-floor beams, slabs, and columns for the main structure. The target bill of quantities data could include the amount of the sub-item corresponding to the concrete pouring of the second-floor beams, slabs, and columns for the main structure. The project progress data could include the current percentage of progress of the concrete pouring of the second-floor beams, slabs, and columns for the main structure. Then, the amount of the obtained sub-item could be multiplied by the corresponding percentage of progress to calculate the current cumulative output value of the sub-item. By iterating through all sub-items in the project with similar statuses, calculating and summing them, the target project output value of the project up to the present could be generated.

[0063] This application embodiment reads the monetary information of each item in the matched target list data and obtains the percentage of progress in the project progress data corresponding to the sub-item of the project to which the item belongs. Based on a preset calculation method, the amount of each item is multiplied by the matched percentage of progress to calculate the completed output value of the item at the current progress. The above calculation is repeated for all items in the target list data, and the calculation results of each item are summed to obtain the cumulative completed output value of the contract or project at the current time node, i.e., the target project output value. This improves the accuracy and timeliness of monetary value accounting; enhances the efficiency of collaborative analysis of project progress and cost data; improves the accuracy and reliability of output value data; improves the automation level and processing efficiency of output value calculation; and enhances the collaborative ability and data consistency between project progress information and cost information.

[0064] According to the technical solution provided in this disclosure, the sub-item project data is categorized based on process status data, and the completed process information is mapped and integrated into the corresponding sub-item project nodes to obtain target sub-item project data. The target sub-item project data is then associated with the bill of quantities data, establishing a matching relationship using the sub-item project code as a key field to generate an association table. Based on this association table, the project progress data is matched with the bill of quantities data. By extracting the sub-item project identifier from the project progress data and querying the corresponding bill of quantities sub-items in the association table, detailed information of the bill of quantities sub-items related to the current progress is filtered and extracted, and integrated into target bill of quantities data. The target bill of quantities data is then processed... Value accounting is performed on the project progress data. By multiplying the amount of each item in the bill of quantities by the corresponding percentage of progress, the completed output value of each item is calculated and summed to obtain the target project output value. This enhances the accuracy of the correlation between process status data and sub-item project data; improves the structuring and integration efficiency of project progress information; enhances the automation and real-time performance of data classification; ensures the accuracy and consistency of the correlation between progress information and project structure; enhances the integration and collaboration capabilities of project data; improves the automation and accuracy of project data correlation processing; improves the efficiency and reliability of multi-source heterogeneous data fusion; enhances the relevance and accuracy of output value calculation; and improves the automation and processing efficiency of output value calculation.

[0065] In some embodiments, the target sub-item project data includes sub-item structure data, and the project list data includes list structure data; the target sub-item project data and the project list data are associated to obtain an association table, including: performing dimensional matching processing on the sub-item structure data and the list structure data to obtain structure mapping data; and performing relationship solidification processing on the structure mapping data to obtain an association table.

[0066] Specifically, the sub-item structure data can be a set of data obtained by hierarchically and structurally decomposing the project according to the construction specifications and project work breakdown structure. It can be used to organize and manage construction tasks, and ensure that construction progress information is recorded and transmitted in a standardized structure. This sub-item structure data can be obtained by calling the process library and classifying the completed processes to the corresponding sub-item project nodes based on the process completion status fed back by the construction site data acquisition equipment.

[0067] The bill of quantities structure data can be structured data formed by breaking down the total price of a project into details and items according to the bill of quantities pricing specification. It can be used to represent the measurement unit, quantity and unit price of each work within the scope, and provide a basis for calculating output value. This bill of quantities structure data can be obtained by parsing and storing the imported bill of quantities to form a structured data table with standard coding and hierarchical relationship.

[0068] In addition, dimensional matching processing can be used to compare and associate structured data from different systems based on one or more preset key dimensions, thereby discovering potential correspondences between sub-item engineering data and bill of quantities items. Specifically, this dimensional matching processing can extract common dimensional features of sub-item structure data and bill of quantities structure data, such as coding rules, name keywords, engineering parts and / or professional categories, etc., without limitation here, and perform similarity calculation or rule matching to generate structured mapping data containing corresponding relationships.

[0069] In addition, relationship solidification can be used to verify, confirm and persist the mapping relationship generated by the initial matching. This can transform temporary and potentially questionable matching results into stable and reliable mapping relationships, forming the core data association that subsequent output value calculations depend on. This relationship solidification process can eliminate incorrect matching pairs, confirm the correct mapping relationship, and generate an association table through business process review or system logic verification. This association table can be persistently stored in the system's database.

[0070] Furthermore, the relationship solidification process can trigger a notification mechanism. When a matching relationship needs to be confirmed, relevant management personnel can be notified for review. Once the mapping relationship is confirmed, it can be locked and remain unchanged throughout the project cycle unless the project changes.

[0071] For example, in the output value declaration of a residential development project, structural data of sub-items, including hierarchical nodes such as main structure engineering, concrete engineering, and beam, slab and column concrete pouring, can be generated according to the construction plan. List structure data, including detailed items such as rectangular column concrete pouring and beam and slab concrete pouring under the concrete engineering chapter, can be stored. By performing dimension matching processing, the sub-item node beam, slab and column concrete pouring can be associated with the list item rectangular column concrete pouring and beam and slab concrete pouring based on concrete engineering and name keywords such as beam, slab and column, generating preliminary structural mapping data. After confirming the mapping relationship, relationship solidification processing can be performed to write the confirmed correspondence into the association relationship table.

[0072] According to the technical solution provided in this disclosure, sub-item structure data is extracted from target sub-item project data, and list structure data is extracted from project list data; the sub-item structure data and list structure data are subjected to dimensional matching processing, and similarity calculation or rule matching is performed by extracting common dimensional features to generate structure mapping data; the structure mapping data is subjected to relationship solidification processing, and the mapping relationship is confirmed through business process review or system logic verification, and the confirmed correspondence is stored to generate an association relationship table. This simplifies the data processing process, enhances the accuracy and standardization of the mapping between sub-item structure and list structure, improves the systematization and controllability of the data matching process, and enhances the data integration and collaboration capabilities between the project management system and the cost management system.

[0073] In some embodiments, matching project progress data and project list data based on a relationship table to obtain target list data includes: performing proportional parsing on the project progress data to obtain progress proportion data; and performing index filtering on the progress proportion data and project list data based on the relationship table to obtain target list data.

[0074] Specifically, proportional analysis can be used to convert the completion status or workload represented in the project progress data into percentage values ​​representing the degree of completion based on predetermined calculation rules. This transforms non-standardized progress representations into quantifiable progress proportions, facilitating subsequent mathematical operations with the bill of quantities to calculate output value.

[0075] Furthermore, the proportional analysis processing can be based on the standard process information defined in the process library. For example, when a process is detected as marked as completed, the corresponding progress percentage can be calculated based on the weight of the process in the entire sub-item project data. Alternatively, for progress based on quantity measurement, the completed quantity can be divided by the total quantity of the sub-item to obtain the progress ratio data.

[0076] In addition, index filtering can be used to find matching records in the relationship table by using the specific sub-items or processes corresponding to the progress ratio data as index keys. This allows the corresponding list items and their amount data to be located and extracted from the bill of quantities data, thereby locking in the cost portion related to the current progress and eliminating interference from irrelevant list items.

[0077] Furthermore, the index filtering process can identify the relevant specific sub-item project codes based on the progress ratio data, query all list item numbers associated with the sub-item code in the association table, and retrieve the corresponding list representation and amount from the project list database in batches based on the list item number, and summarize them to form the target list data.

[0078] For example, during the curtain wall construction phase of a residential development project, sensors installed on-site and smart terminals held by construction workers can collect real-time data on the completion status of processes such as curtain wall keel installation, panel laying, and sealing, forming project progress data. The collected data can be processed through proportional analysis; for instance, based on the process library definition, when the east facade curtain wall panel laying process is marked as completed, the percentage of progress achieved by this process can be calculated by considering its weight within the curtain wall project, thus obtaining progress ratio data. The total price list for the curtain wall project can be pre-divided into sub-items such as keel, panels, auxiliary materials, and labor, and a relationship table can be established between these sub-items and process information. Based on this relationship table, and using the calculated curtain wall project progress ratio as an index, all relevant sub-items in the list, such as galvanized steel keel, glass curtain wall panels, and sealant, along with their corresponding amounts, can be filtered and summarized into target list data.

[0079] According to the technical solution provided in this disclosure, by performing proportional analysis on the project progress data, the completion status or workload represented therein is calculated and converted into a quantifiable progress percentage based on a predefined weight or work volume ratio, thus obtaining progress ratio data. Based on the relationship table, using the specific sub-item or process corresponding to the progress ratio data as the index key, the matching record is searched in the relationship table, thereby locating and batch retrieving and extracting the corresponding list items and their amount information from the project list data, and summarizing them to form target list data. This enhances the accuracy and standardization of the vectorized numerical conversion of progress status, improves the indexing and filtering efficiency from progress to cost data, enhances the accuracy and automation level of target list data generation, and improves the accuracy and processing efficiency of output value determination.

[0080] In some embodiments, classifying and processing the sub-item project data based on process status data to obtain target sub-item project data includes: performing completion status judgment processing on the process status data to obtain completion status data; and performing attribution mapping processing on the completion status data and sub-item project data to obtain target sub-item project data.

[0081] Specifically, the completion status judgment process can be used to identify records in the process status data that are marked as completed or have reached the preset completion standard, thereby filtering out all processes that have been completed. This completion status judgment process can be implemented through a logical judgment process. The input can be unfiltered process status data, and the output can be filtered completion status data that only contains information on completed processes.

[0082] Furthermore, the completion status data can be a subset of data generated through completion status judgment processing, containing only information of processes identified as completed. This completion status data can be obtained by performing status judgment and filtering on process status data and is used for subsequent attribution mapping processing.

[0083] In addition, the attribution mapping process can be used to match and classify completed processes in the completed status data into the corresponding sub-items in the sub-item project data based on a preset correspondence. This attribution mapping process can be based on the predefined correspondence logic between processes and sub-item projects in the process library. The input can be completed status data and sub-item project data, and the target sub-item project data can be obtained.

[0084] Furthermore, during the attribution mapping process, the process can be matched with the subordinate relationships between the processes and sub-items maintained in the process library. When a process is marked as completed, the sub-items to which the process belongs can be queried, and the completion information can be added to the corresponding sub-item record. This mapping relationship can be pre-configured to ensure the accuracy and consistency of the conversion of process progress to sub-item progress.

[0085] For example, during the main structure construction phase of a residential building, the process status data can include rebar tying, formwork erection, and concrete pouring. Once the concrete pouring process is confirmed by on-site personnel, the corresponding status can be updated to "completed." The system can process all process status data to determine completion status, filtering out all process records with a "completed" status to form finished status data. For example, this could include the completion of three-story concrete pouring. The system can maintain the project's sub-item engineering data, where the main structure engineering sub-item can include concrete engineering sub-items. It can also perform attribution mapping processing, based on preset mapping rules, to associate the completion of three-story concrete pouring with the concrete engineering sub-item, obtaining the target sub-item engineering data.

[0086] According to the technical solution provided in this disclosure, by performing completion status judgment processing on the process status data, and through a logical judgment process, identifying and filtering records marked as completed or reaching the preset completion standard, completion status data is obtained. The completion status data is then mapped to the sub-item project data. Based on the preset subordinate correspondence between processes and sub-items in the process library, the completed process information in the completion status data is matched and classified under the corresponding project node in the sub-item project data, thereby obtaining the target sub-item project data. This enhances the accuracy and reliability of process completion status identification; improves the efficiency of completion information collection and engineering structure data integration; and enhances the automation and standardization level of preliminary progress data processing, thereby improving the efficiency and accuracy of progress data processing and classification.

[0087] In some embodiments, the project progress data includes project quantity ratio data, and the target list data includes list value data; the target list data and project progress data are subjected to value accounting processing to obtain the target project output value, including: extracting the list value data to obtain the value data to be accounted for; and performing weighted calculation processing on the value data to be accounted for and the project quantity ratio data to obtain the target project output value.

[0088] Specifically, the quantity ratio data can characterize the ratio between the actual completed quantity of each sub-item or process in an engineering project and the planned total quantity. It can be used as a quantitative indicator to characterize the progress of the project. This quantity ratio data can be obtained through data interfaces with external systems, or it can be calculated by summarizing and analyzing the process completion status data collected by sensors and smart terminals at the construction site. It can also be used to characterize the real-time progress information of the project.

[0089] The list value data can be the unit price or total price data corresponding to each sub-item of the project or material and equipment, which is determined based on the details of the project list. It can be used to form the basic value unit of the total price. The list value data can be formed by decomposing and coding the project list and mapping it with the standard process library. It can be used to characterize the pricing standard of each work within the scope.

[0090] In addition, the extraction process can be used to filter and extract the corresponding value items from the complete list database based on the current scope of the project or process node that needs to be calculated, and obtain the value data to be calculated. The value data to be calculated can be a specific set of value data obtained through the extraction process that can be used to match and calculate with the current progress, and can be used to characterize the value basis of the output value to be confirmed.

[0091] In addition, the weighted calculation process can be used to multiply the value data to be calculated for each sub-item by its corresponding engineering quantity ratio data to calculate the output value of the sub-item based on the current progress. If there are multiple sub-items, the summation operation is performed to obtain the target engineering output value, thereby realizing dynamic and proportional matching between value and actual project progress. This weighted calculation process can follow the core algorithm that the list value multiplied by the engineering quantity ratio equals the sub-item output value and the sum of the sub-item output values ​​equals the target engineering output value.

[0092] For example, in the exterior wall coating project, the current progress of the project can be obtained from an external system through a data interface, such as the completion of wall base treatment or the first coat of paint. This progress can be converted into specific quantity ratio data using a built-in algorithm, such as a completion rate of 65%. The system can maintain the corresponding bill of quantities value data for the exterior wall coating, which can include detailed unit prices for each process, such as base treatment and the number of coats. When output value calculation is triggered, the unit prices corresponding to base treatment and the first coat of paint can be extracted from the bill of quantities value data based on the processes associated with the current progress. A weighted calculation can be performed, multiplying the two extracted unit prices by the ratios converted from their respective completion quantities to calculate the output value of each sub-item. The output values ​​of the sub-items can then be added together to obtain the target project output value of the exterior wall coating project at the current calculation node.

[0093] According to the technical solution provided in this disclosure, by extracting list value data from the target list data, and through extraction processing, based on the current scope of the project or process node to be calculated, corresponding value items are screened and extracted from the complete list to obtain the value data to be calculated; the value data to be calculated is weighted and processed with the quantity ratio data in the project progress data, and the value data to be calculated for each sub-item is multiplied by its quantity ratio data to obtain the output value of the sub-item based on the current progress, and the output value results of multiple sub-items are summed to obtain the target project output value, thereby enhancing the accuracy of value accounting and dynamic matching of project progress; improving the operability and transparency of the output value calculation process; improving the efficiency and automation level of financial data accounting based on quantitative ratios; and improving the automation level and calculation accuracy of output value accounting.

[0094] In some embodiments, before classifying the sub-item project data based on the process status data to obtain the target sub-item project data, the method further includes: performing noise filtering on the initial sensing data to obtain initial process data; and performing status marking on the initial process data to obtain process status data.

[0095] Specifically, the initial sensing data can be raw, unprocessed monitoring data obtained by data acquisition equipment deployed at the construction site. This initial sensing data can come from various data acquisition devices at the construction site, such as sensors used to monitor the operating status of construction equipment, or smart terminal devices used to receive information reported by construction personnel. The aforementioned devices continuously or on demand collect raw signals or records reflecting the status of construction activities.

[0096] In addition, noise filtering can be used to clean and screen the initial sensing data to remove invalid, erroneous or interfering information, thereby improving the purity and reliability of the initial sensing data. For example, noise filtering can be used to filter out abnormal values ​​caused by momentary sensor failures, or to merge duplicate reports of the same process from different terminals, thereby obtaining more regular and reliable initial process data.

[0097] Furthermore, the initial process data can be a set of data that has been processed by noise filtering and can be used to characterize the actual progress of each process at the construction site. This initial process data can be used as the basis for state judgment. This initial process data can be obtained by transforming the initial sensing data after noise filtering.

[0098] In addition, status marking processing can be used to analyze initial process data based on preset rules or algorithms to determine and identify the current status of the corresponding process. This can transform the original progress data into structured information with clear status meaning. This status marking processing can be executed based on predefined process completion standards in the process library. For example, when it is detected that the material usage related to a certain process reaches a preset threshold and the operation time is within the expected range, the process can be determined to be completed.

[0099] For example, in residential development projects, initial sensing data on pouring operation duration, material consumption, and manual completion status can be collected in real time through concrete pouring sensors installed on the construction floors of residential buildings and smart terminals handheld by construction workers. Noise filtering can be performed to remove abnormal values ​​caused by momentary sensor malfunctions, or to merge duplicate reports of the same process from different terminals, thereby obtaining initial process data. Status marking logic can be applied to the noise-filtered initial process data, calling the completion standards of floor concrete pouring processes in the process library, comparing the actual pouring volume and completion time in the initial process data with the standard values. When the data meets the completion conditions, a process completion status marker can be added to the data record; if not, it can be marked as in progress or not started, generating process status data containing clear status information.

[0100] According to the technical solution provided in this disclosure, noise filtering is performed on the initial sensing data from the data acquisition equipment at the construction site. Through cleaning and screening, regular and reliable initial process data is obtained. The initial process data is then processed with status marking. Based on the predefined process completion standards in the process library, analysis and comparison are performed to determine and add a process status identifier to each process data, thereby obtaining process status data. This enhances the purity and usability of the original data acquisition, improves the accuracy and automation level of process status determination, and enhances the overall reliability and efficiency of the construction progress data acquisition and preprocessing process, as well as the reliability and efficiency of the output value determination process.

[0101] In some embodiments, performing dimensional matching processing on the component structure data and the list structure data to obtain structure mapping data includes: performing hierarchical decomposition processing on the component structure data to obtain component hierarchical data; performing granularity adaptation processing on the list structure data to obtain list granular data; and performing hierarchical mapping processing on the component hierarchical data and the list granular data to obtain structure mapping data.

[0102] Specifically, hierarchical decomposition processing can be used to break down structured data into multiple levels with different membership or inclusion relationships based on the inherent hierarchical relationship of the data. This allows for the parsing of clear hierarchical relationship information contained in the structured data. For example, it can decompose the data into sub-project levels, item-by-item levels, etc. This hierarchical decomposition processing can identify and extract the name, code, and subordinate relationship of each level by parsing the predefined parent-child node relationship or hierarchical identifier in the data, and generate a set of sub-project hierarchical data containing a complete hierarchical tree.

[0103] Furthermore, granularity adaptation processing can be used to adjust the level of detail or aggregation of data according to target matching requirements, so as to make it consistent with the granularity of another data system. This can adjust the amount items in the list to a granularity that matches the level of detail of the sub-item level data. For example, a comprehensive unit price list item can be split into sub-items corresponding to multiple sub-projects, or multiple overly detailed list items can be merged into a sub-item level, thereby eliminating differences in data organization dimensions. This granularity adaptation processing can reorganize the original list items based on preset splitting and merging rules or mapping tables, ensuring that each item in the generated list granularity data can find a corresponding or attributable hierarchical node in the sub-item level data.

[0104] Furthermore, hierarchical mapping processing can be used to establish node-to-node or level-to-level correspondences between two datasets with hierarchical structures. This improves the consistency of the data structure through hierarchical decomposition and granularity adaptation, establishing a correspondence between each level of the sub-item project and the corresponding amount item in the list. This hierarchical mapping processing can establish the association by comparing key identifiers in the two datasets or based on a preset mapping rule table, generating a structured mapping data that clearly records the list amount item corresponding to each sub-item node.

[0105] For example, in the interior decoration phase of a residential building project, structural data of sub-items can be generated, including the interior decoration sub-project and its sub-items such as living room floor tiling and bedroom wall plastering; the bill of quantities structure data of the interior decoration contract can be stored, which can include items such as the comprehensive unit price of floor tile tiling and the comprehensive unit price of wall base treatment; the sub-item structure data can be hierarchically decomposed to identify interior decoration as a first-level node, living room floor tiling as a second-level node, and the complete hierarchical path can be extracted; the bill of quantities structure data can be granularly adapted, and the comprehensive unit price of floor tile tiling can be adapted and split into sub-amount data corresponding to specific sub-items such as living room floor tiling and kitchen floor tiling according to project characteristics, forming bill of quantities granular data; hierarchical mapping can be performed to establish a mapping between the living room floor tiling sub-item node and the corresponding sub-amount data of floor tile tiling after splitting, and to establish a mapping between the bedroom wall plastering sub-item node and the corresponding sub-amount data of the comprehensive unit price of wall base treatment after adaptation; and structural mapping data can be generated.

[0106] According to the technical solution provided in this disclosure, by performing hierarchical decomposition processing on the component structure data, and by parsing the inherent parent-child node relationship or hierarchical identifier, the name, code, and subordinate relationship of each level are identified and extracted to obtain component hierarchical data containing a complete hierarchical tree; by performing granular adaptation processing on the list structure data, based on preset splitting or merging rules, the level of detail or aggregation of list items is adjusted to be consistent with the granularity of the component hierarchical data, thus obtaining list granular data; by performing hierarchical mapping processing on the component hierarchical data and list granular data, by comparing key identifiers or according to the mapping rule table, a node-to-node correspondence relationship is established between the two hierarchical datasets, thereby generating structural mapping data, thereby enhancing the alignment accuracy of hierarchy and granularity between different data structures; improving the coordination and success rate of cross-system data matching; improving the clarity and maintainability of structural mapping relationships; and improving the automation and accuracy of the output value determination process.

[0107] All of the above-mentioned optional technical solutions can be combined in any way to form optional embodiments of this disclosure, and will not be described in detail here.

[0108] Figure 3 This is a flowchart illustrating another method for determining engineering output value provided in this embodiment of the disclosure. Figure 3 As shown, the method for determining the output value of this project includes: Business logic steps: Obtain project progress data. By connecting the engineering management system with the enterprise daily report system, various types of contracts applicable to the project (such as general contracting contracts, waterproofing contracts, exterior wall coatings, curtain walls, underfloor heating, public area interior decoration projects, fire protection, railings, fire doors, rainwater and sewage systems, interior decoration projects, etc.) are integrated, and project progress data (process status data) is obtained from the enterprise daily report.

[0109] Obtain the contract list amount. Extract the list amount data (engineering list data) of the corresponding project contract from the contract management module of the cost management system.

[0110] Calculate the cumulative output value. Following the logical relationship of "progress in progress × contract amount = cumulative output value", calculate the cumulative output value (target project output value) by combining the obtained project progress with the obtained contract amount.

[0111] Product implementation logic steps: Process library call. The process management module of the engineering management system calls the process library to obtain standard information for each process in the project, including process name, process requirements, process duration, etc.

[0112] Work process completion confirmation. The completion status of each work process is monitored in real time through the construction site data acquisition equipment (such as sensors, smart terminals, etc.) of the project management system. When a work process is completed, the system automatically marks the work process as "work process completed" (completion status data).

[0113] Work process matching to sub-items. Based on the correspondence between work processes and sub-item projects in the work process library, the system automatically matches "work processes completed" to the corresponding sub-item projects.

[0114] The cost management system's contract list management module breaks down the contract list into sub-items and then associates them with the matching work processes in the project management system, establishing a correspondence between work processes and contract list sub-items.

[0115] Progress Acquisition and Automatic Output Value Calculation. After obtaining the project's visual progress from the company's daily reports, the project management system, combined with the correspondence between work processes and contract list items established in step 4, automatically extracts the amounts of relevant contract list items, calculates the output value result according to the logic of "visual progress × list amount," and feeds the result back to the output value management module of the cost management system.

[0116] The data acquisition module is used to capture project progress status data in real time. This module is equipped with various data acquisition devices, such as sensors installed at the construction site to monitor the operating status of construction equipment and material usage; and smart terminal devices to facilitate real-time reporting of process completion by construction personnel. Simultaneously, it automatically acquires project progress data through an interface with the company's daily reporting system. This multi-dimensional and real-time collection of project progress-related data provides accurate and timely basic data support for subsequent output value calculations.

[0117] The data processing module processes the collected data, including rapid processing of progress data and automatic calculation of output value. For progress data processing, it cleans and integrates the collected raw data, removing invalid data and unifying the format of data from multiple sources. For output value calculation, it incorporates built-in algorithms based on business logic and product implementation logic, automatically and quickly calculating output value results based on input project progress data and contract amount data. Through efficient data processing algorithms, it improves the efficiency and accuracy of data processing, ensuring the timeliness and precision of output value calculation.

[0118] The communication module enables communication with external systems such as the enterprise's main system, as well as with internal modules within the engineering management and cost management systems. When communicating with external systems, it uses standard network communication protocols to upload and download data, such as retrieving project progress data from the enterprise's daily report system and transmitting output payment information to relevant enterprise systems. Within the internal system, it handles data exchange between the engineering management and cost management systems, ensuring real-time data sharing and synchronization between modules. This guarantees the stability and efficiency of data communication between the system and external systems, as well as between internal modules, promoting collaborative work across the entire system.

[0119] Storage Module: Stores project progress data, contract data, and output value calculation related data. It utilizes high-capacity storage media (such as hard drives and solid-state drives) and a comprehensive database management system to categorize and manage the data. For example, project progress data is stored according to time and project dimensions, contract data is categorized by contract type and project name, and output value calculation related data is stored in association with projects and contracts. This provides reliable data storage for the system, facilitates data querying, retrieval, and backtracking, and also provides a data foundation for subsequent data analysis and system optimization.

[0120] According to the technical solutions provided in this disclosure, the time for real-time progress status capture is significantly shortened, and the export of output value declaration-related data is more convenient. After the output value payment process is optimized, the time spent on cost consultation and other tasks is significantly reduced, and the overall business process efficiency is greatly improved, which helps business departments to seamlessly connect various tasks through the system. Output value payment does not require a second review, reducing the review process and the complexity of manual intervention. At the same time, the system automatically calculates output value, reducing the workload of manual statistics and accounting, avoiding errors that may be caused by manual operation, and making the process simpler, more efficient and accurate. The data integration capability realizes efficient correlation and automatic calculation between project progress and contract output value, promotes data collaboration between business departments and with external partners, ensures the timeliness and accuracy of project fund flow, and provides strong support for project management and fund management of real estate development enterprises.

[0121] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0122] Figure 4 This is a schematic diagram of an engineering output value determination device provided in an embodiment of this disclosure. Figure 4 As shown, the device for determining the output value of this project includes: The first processing module 401 is used to classify and process the sub-item project data based on the process status data to obtain the target sub-item project data. The second processing module 402 is used to perform association processing on the target sub-item project data and the project list data to obtain an association table; The third processing module 403 is used to match the project progress data and the project list data based on the relationship table to obtain the target list data; The fourth processing module 404 is used to perform value accounting processing on the target list data and project progress data to obtain the target project output value.

[0123] According to the technical solution provided in this disclosure, the sub-item project data is categorized based on process status data, and the completed process information is mapped and integrated into the corresponding sub-item project nodes to obtain target sub-item project data. The target sub-item project data is then associated with the bill of quantities data, establishing a matching relationship using the sub-item project code as a key field to generate an association table. Based on this association table, the project progress data is matched with the bill of quantities data. By extracting the sub-item project identifier from the project progress data and querying the corresponding bill of quantities sub-items in the association table, detailed information of the bill of quantities sub-items related to the current progress is filtered and extracted, and integrated into target bill of quantities data. The target bill of quantities data is then processed... Value accounting is performed on the project progress data. By multiplying the amount of each item in the bill of quantities by the corresponding percentage of progress, the completed output value of each item is calculated and summed to obtain the target project output value. This enhances the accuracy of the correlation between process status data and sub-item project data; improves the structuring and integration efficiency of project progress information; enhances the automation and real-time performance of data classification; ensures the accuracy and consistency of the correlation between progress information and project structure; enhances the integration and collaboration capabilities of project data; improves the automation and accuracy of project data correlation processing; improves the efficiency and reliability of multi-source heterogeneous data fusion; enhances the relevance and accuracy of output value calculation; and improves the automation and processing efficiency of output value calculation.

[0124] In some embodiments, the second processing module 402 is specifically used to perform dimensional matching processing on the sub-item structure data and the list structure data to obtain structure mapping data; and to perform relationship solidification processing on the structure mapping data to obtain an association table.

[0125] In some embodiments, the third processing module 403 is specifically used to perform proportional parsing processing on the project progress data to obtain progress proportion data; and to perform index filtering processing on the progress proportion data and the project list data based on the association table to obtain target list data.

[0126] In some embodiments, the first processing module 401 is specifically used to perform completion status judgment processing on the process status data to obtain completion status data; and to perform attribution mapping processing on the completion status data and the sub-item project data to obtain target sub-item project data.

[0127] In some embodiments, the fourth processing module 404 is specifically used to extract and process the list value data to obtain the value data to be calculated; and to perform weighted calculation on the value data to be calculated and the engineering quantity ratio data to obtain the target engineering output value.

[0128] In some embodiments, the above-described engineering output determination device is further configured to perform noise filtering processing on the initial sensing data to obtain initial process data; and to perform state marking processing on the initial process data to obtain process state data.

[0129] In some embodiments, performing dimensional matching processing on the component structure data and the list structure data to obtain structure mapping data is specifically used for: performing hierarchical decomposition processing on the component structure data to obtain component hierarchical data; performing granularity adaptation processing on the list structure data to obtain list granular data; and performing hierarchical mapping processing on the component hierarchical data and the list granular data to obtain structure mapping data.

[0130] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure.

[0131] Figure 5 This is a schematic diagram of the electronic device 5 provided in an embodiment of this disclosure. Figure 5 As shown, the electronic device 5 of this embodiment includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 503, it implements the steps in the various method embodiments described above. Alternatively, when the processor 501 executes the computer program 503, it implements the functions of each module / unit in the various device embodiments described above.

[0132] Electronic device 5 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 5 may include, but is not limited to, processor 501 and memory 502. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown, or different components.

[0133] The processor 501 can 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.

[0134] The memory 502 can be an internal storage unit of the electronic device 5, such as a hard disk or RAM of the electronic device 5. The memory 502 can also be an external storage device of the electronic device 5, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 5. The memory 502 can also include both internal and external storage units of the electronic device 5. The memory 502 is used to store computer programs and other programs and data required by the electronic device.

[0135] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0136] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a readable storage medium (e.g., 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 may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0137] The above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit it. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be included within the protection scope of this disclosure.

Claims

1. A method for determining engineering output value, characterized in that, include: Based on the process status data, the sub-item project data is classified and processed to obtain the target sub-item project data; The target sub-item project data and the project list data are associated to obtain an association table; Based on the aforementioned relationship table, the project progress data and the project list data are matched to obtain the target list data; The target list data and the project progress data are subjected to value accounting processing to obtain the target project output value.

2. The method for determining engineering output value according to claim 1, characterized in that, The target sub-item project data includes sub-item structure data, and the project list data includes list structure data; The step of associating the target sub-item project data and the project list data to obtain an association table includes: The sub-item structure data and the list structure data are subjected to dimensional matching processing to obtain structure mapping data; The structure mapping data is subjected to relation solidification processing to obtain the association table.

3. The method for determining engineering output value according to claim 1, characterized in that, The process of matching the project progress data and the project list data based on the relationship table to obtain the target list data includes: The project progress data is subjected to proportional analysis to obtain progress proportion data; Based on the relationship table, the progress ratio data and the project list data are indexed and filtered to obtain the target list data.

4. The method for determining engineering output value according to claim 1, characterized in that, The process of classifying and processing the sub-item project data based on the process status data to obtain the target sub-item project data includes: The process status data is processed to determine the completion status, and the completion status data is obtained. The completion status data and the sub-item project data are subjected to affiliation mapping processing to obtain the target sub-item project data.

5. The method for determining engineering output value according to claim 1, characterized in that, The project progress data includes project quantity ratio data, and the target list data includes list value data. The process of performing value accounting on the target list data and the project progress data to obtain the target project output value includes: The value data of the list is extracted and processed to obtain the value data to be calculated; The target project output value is obtained by weighting the value data to be calculated and the project quantity ratio data.

6. The method for determining engineering output value according to claim 1, characterized in that, Before classifying and processing the sub-item project data based on the process status data to obtain the target sub-item project data, the following steps are also included: The initial sensing data is processed to remove noise, resulting in initial process data; The initial process data is processed by status marking to obtain the process status data.

7. The method for determining engineering output value according to claim 2, characterized in that, The step of performing dimensional matching processing on the sub-item structure data and the list structure data to obtain structure mapping data includes: The sub-item structure data is subjected to hierarchical decomposition to obtain sub-item hierarchical data; The granularity of the list structure data is adapted to obtain list granular data; The structure mapping data is obtained by performing hierarchical mapping processing on the sub-item hierarchical data and the list granular data.

8. A device for determining engineering output value, characterized in that, include: The first processing module is used to classify and process the sub-item project data based on the process status data to obtain the target sub-item project data; The second processing module is used to perform association processing on the target sub-item project data and the project list data to obtain an association table; The third processing module is used to match the project progress data and the project list data based on the relationship table to obtain the target list data; The fourth processing module is used to perform value accounting processing on the target list data and the project progress data to obtain the target project output value.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

Images