Professional online collaborative editing method and system for hydropower project cost schemes

Abstract

The invention provides a professional online collaborative editing method and system for hydropower project cost schemes. The professional online collaborative editing method comprises a standard management process, an intelligent collaborative editing process and a release state synchronous updating process. The standard management process comprises the steps of performing automatic analysis and data standardization conversion on an industrial standard file based on a deep learning model, generating a system rule set and storing the system rule set in a database; and based on the system rule set, automatically generating a standardized filling template of each specialty. According to the micro-service architecture-based intelligent online collaborative editing method and system for the hydropower engineering, a natural language processing NLP technology, a deep learning algorithm and a transaction management mechanism are combined, and the system has the functions of real-time grammar and spelling inspection of filled content, intelligent recommendation, semantic understanding, real-time difference detection, multi-user conflict processing and version control; the problems that communication cost is high, version control is difficult, data verification is not strict and multi-user cooperation is not smooth in water-power engineering cost scheme compiling are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of online collaborative editing, and in particular relates to a method and system for professional online collaborative editing of a hydropower engineering cost plan. Background Art

[0002] In the process of compiling the cost plan of hydropower engineering, the traditional way of filling in the cost plan has many problems, such as high communication cost, low work efficiency, inconsistent cost plan versions, etc. Especially when multiple professionals are collaborating, it is difficult to meet the project's needs for real-time synchronization of cost plans, multi-user collaboration and intelligent assistance. In addition, due to the continuous changes in industry standards and project requirements, the filling and updating of hydropower engineering cost plans has become more complicated.

[0003] Therefore, how to use advanced algorithms and technologies to improve the efficiency of cost plan filling, verification accuracy and ensure data consistency has become a problem that needs to be solved urgently. Summary of the invention

[0004] In view of the defects of the prior art, the present invention provides a method and system for online collaborative editing of hydropower project cost plans by profession, which can effectively solve the above problems.

[0005] The technical solution adopted by the present invention is as follows:

[0006] The present invention provides a method for online collaborative editing of hydropower engineering cost plans by profession, comprising the following steps:

[0007] Step S1, standard management process:

[0008] Based on the deep learning model, the text logic relationship and entry structure of the industry standard documents are automatically parsed and the data is standardized, and a system rule set is generated and stored in the MySQL database; based on the system rule set, standardized reporting templates for various professions are automatically generated;

[0009] Step S2, intelligent collaborative editing process:

[0010] When it is detected that a user is filling in data for the standardized filling template, the user's filling content is verified in real time and relevant content is intelligently recommended. It also has a batch data import function, and automatically fills the batch imported content into the corresponding position of the standardized filling template;

[0011] When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time;

[0012] Step S3, publishing status synchronization update process:

[0013] When the standardized reporting template is completed, the latest version of the project plan is formed; the project plan is published, and the publishing status of the project plan is synchronized in real time; combined with the model algorithm, the impact scope of the project plan after release is intelligently analyzed, and the user is prompted to incrementally update or fully update the old version of the project plan, and automatic rollback is supported in abnormal situations to ensure the integrity of the published project plan; the system automatically records the release version information and change log of the project plan.

[0014] Preferably, step S1 specifically comprises:

[0015] Step S1.1, using the integrated EasyExcel tool to perform data structured reading on the industry standard file, combining the pre-trained deep learning model to parse the industry terms, technical indicators, and project division content in the industry standard file, parse to obtain the original data structure, and store it as a temporary data structure;

[0016] Step S1.2, using the dependency analysis model to perform logical conversion and field mapping on the parsed original data structure, mapping it into multiple entry contents with logical relationships; performing dependency analysis on each of the entry contents, converting the entry contents into a system rule set and mapping them to standardized fields in the database, thereby obtaining a mapped system rule set;

[0017] Step S1.3, the mapped system rule set is persistently stored in a MySQL database, and a corresponding database index is configured for each rule in the mapped system rule set and a unique identifier is assigned;

[0018] Step S1.4, based on the mapped system rule set, automatically generate standardized reporting templates for each profession.

[0019] Preferably, in step S1.4, each of the standardized reporting templates comprises the following contents: the mapped system rule set and reporting fields;

[0020] The standardized reporting template has the following functions: it is embedded with an NLP model and a Transformer model; when the reporting field is entered with reporting content, the NLP model is called to perform real-time verification of the reporting content and generate intelligent recommended content; the Transformer model is called to dynamically analyze the reporting content, give reporting suggestions, and automatically complete or provide contextual prompts.

[0021] Preferably, it also includes:

[0022] Step S1.5, when industry standards or project requirements change, the corresponding rules are updated through the system front-end management interface, and the updated rules are automatically stored in the MySQL database, replacing the old rules in the mapped system rule set, thereby obtaining an updated system rule set;

[0023] According to the updated system rule set, the corresponding standardized reporting template is automatically updated; when the standardized reporting template is updated, a new rule constraint logic is triggered to generate and step S1.6 is executed;

[0024] Step S1.6: the updated standardized reporting template is distributed to the front end through the API interface, and the latest system rule set and the standardized reporting template are distributed to relevant users in combination with the real-time push mechanism; at the same time, the rule and template update information is pushed to the relevant users, and the users are intelligently reminded of the applicability of the latest system rule set, and suggested to change the filling content to ensure compliance with the latest standards. All the system rule set and standardized reporting template update operations are performed through transaction management to ensure data consistency;

[0025] Step S1.7, regularly back up the latest system rule set and the standardized reporting template, and generate different versions of the system rule set based on the methods of steps S1.1 and S1.2, support version backtracking and comparison, and ensure rapid recovery and version tracking when industry standards change; when major changes occur in industry standards, be able to quickly restore and manage versions to enhance the stability and adaptability of the system.

[0026] Preferably, step S2 specifically comprises:

[0027] Step S2.1, when the system detects that a user has logged in, the system dynamically loads a template selection interface corresponding to the user's authority according to the user's authority, wherein the template selection interface has a template selection list, and the template selection list has template identifiers of multiple standardized reporting templates; each of the standardized reporting templates is pre-defined according to the system rule set, and contains specific reporting fields and corresponding verification logic to ensure the accuracy of data reporting;

[0028] Step S2.2, when the user enters the filling content for a filling field in the selected standardized filling template, the system front-end page dynamically adds and deletes the engineering quantities that have been filled in the sub-items or subsets through JavaScript scripts, and can perform real-time verification of the filling content according to the stored system rule set, including the data format, value range and logical relationship between fields, and uses regular expressions to ensure that the filling content conforms to the expected format and meets the established standards;

[0029] The NLP module integrated in the system uses the deep learning model BERT to perform grammar checking, spelling correction and intelligent recommendation on the reported content: Specifically, by calling the NLP model, the semantic structure of the reported content is analyzed in real time, grammatical errors are marked and spelling correction suggestions are provided. Based on the semantic understanding of the NLP model, the NLP model automatically detects incorrect use of industry terms, recommends appropriate words or phrases, and provides an automatic summary function to condense long paragraphs into concise sentences, helping users to complete data reporting efficiently;

[0030] Step S2.3: For scenarios with complex or large-scale reporting, the Excel batch import function can be used to upload the reported files to the standardized reporting template, and the EasyExcel tool can be used to parse the file content, automatically fill in the corresponding reporting fields in the standardized reporting template, and verify the reported content of each reporting field one by one to ensure the integrity and standardization of the data after the file is imported;

[0031] Step S2.4: The system uses a machine learning recommendation algorithm based on user behavior to optimize reporting suggestions by analyzing the user's historical operating habits. Specifically, the system automatically generates reporting content suggestions based on the reporting content entered by the user and the fields that are frequently reported. For reporting fields that are repeatedly entered, the system prompts the user to report the commonly used values ​​in advance. The system supports dynamic adjustment of reporting content, records the reporting content entered by the user each time, and adjusts future recommendation strategies based on the machine learning model.

[0032] Step S2.5, in the multi-user collaborative scenario, the system adopts the multi-user collaborative editing OT algorithm and optimistic locking mechanism to ensure the real-time synchronization of reporting operations of different users; specifically: the OT algorithm converts the reporting operation when the user submits it to ensure that there is no conflict when each user edits the same standardized reporting template; before the user submits the change, the system converts the change to ensure that the document remains consistent; the optimistic locking mechanism is used to manage user concurrent operations, each user holds a lock during the operation, and releases the lock after submission to ensure data consistency in high concurrency scenarios.

[0033] Preferably, it also includes:

[0034] Step S2.6, after the user completes filling in all the reporting fields of the standardized reporting template, the system performs a global data verification and calls the backend rule set to perform a final check on all the reporting fields, including comprehensive verification of whether there are unfilled fields, the format of the reporting fields, and the correlation between the reporting fields, to ensure that the reported content is logically consistent;

[0035] Step S2.7, after verification, the completed standardized reporting template generates the latest version of the project plan, and the latest version of the project plan is formally submitted and stored in the database. The submitted project plan serves as the standard record in the project and updates the reporting status.

[0036] Preferably, step S3 specifically comprises:

[0037] Step S3.1, before the project plan is released, the system will integrate the project plans submitted by various majors, and the integrated project plans will be locked through the transaction management mechanism to prevent them from being modified by other users during the release process; before the project plan is released, the system will check the submission status of each major to ensure that all data has been completed and verified, and there are no abnormal records; after the integration is completed, the system will mark it as "pending release" and prepare to enter the release process;

[0038] Step S3.2, after data integration and verification are completed, the project plan is published to subsequent processing or external systems through the REST API. The publishing supports batch publishing, that is, the project plans of multiple disciplines can be published at one time through the bound projects. The publishing status will be synchronously updated to the system database. The system records the timestamp, publisher and content of each publishing operation, and updates the overall progress of the project at the same time. Users can view the latest data publishing status of the current project through the status update module;

[0039] Step S3.3, when the project plan is subsequently updated or adjusted, the system supports incremental updates, can automatically identify all modifications since the last release, and release after rule verification. After the release is completed, the system automatically updates the corresponding version number and records the specific changes of the incremental update; the system maintains the version control information of each release, and the user can view any version as needed to ensure that the project data will be traceable.

[0040] Preferably, it also includes:

[0041] Step S3.4, after each release or incremental update of the project plan, the system synchronizes the latest status to the front-end interface: specifically, based on the push mechanism of REST API, whenever the status of the project plan changes, the system immediately notifies all relevant users, so that all relevant users can grasp the progress of the project in real time. After the user receives the status update, the front-end interface is updated accordingly, including the latest status, version number and change summary of the project plan, so that users can quickly obtain project dynamics;

[0042] Step S3.5, during the process of publishing or updating the status of the project plan, when encountering an abnormal situation, the system automatically triggers the rollback mechanism. Through the transaction management function of MySQL, it ensures that all data is rolled back to the pre-publishing state when an error occurs during the publishing process, so as to avoid incomplete or erroneous data affecting the project progress.

[0043] The present invention also provides a system for the method of online collaborative editing of hydropower engineering cost scheme by profession, comprising:

[0044] The standard management module is used to automatically parse the text logic relationship and entry structure of industry standard documents and perform data standardization conversion based on the deep learning model, generate a system rule set and store it in the MySQL database; based on the system rule set, automatically generate standardized reporting templates for various professions;

[0045] The intelligent collaborative editing module is used to verify the user's reported content in real time and intelligently recommend relevant content when it is detected that the user is filling in data for the standardized reporting template, and has a batch data import function to automatically fill the batch imported content into the corresponding position of the standardized reporting template;

[0046] When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time;

[0047] The release status synchronization update module is used to form the latest version of the project plan when the standardized reporting template is completed; publish the project plan and synchronize the release status of the project plan in real time; combine the model algorithm to intelligently analyze the impact scope of the project plan after release, prompt the user to incrementally update or fully update the old version of the project plan, and support automatic rollback in abnormal situations to ensure the integrity of the released project plan; the system automatically records the release version information and change log of the project plan.

[0048] The method and system for online collaborative editing of hydropower engineering cost plans by profession provided by the present invention have the following advantages:

[0049] The present invention provides a method and system for professional online collaborative editing of hydropower project cost plans. The method and system are based on a microservice architecture and are intelligent online collaborative editing methods and systems for hydropower projects. The method and system combine natural language processing (NLP) technology, deep learning algorithms, and transaction management mechanisms. The method and system have real-time grammar and spelling checking, intelligent recommendation, semantic understanding, real-time difference detection, multi-user conflict processing, and version control functions for reported content. The method solves the problems of high communication costs, difficult version control, lax data verification, and unsmooth multi-user collaboration in the preparation of hydropower project cost plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 An overall flow chart of a method for online collaborative editing of hydropower engineering cost plans by profession provided by the present invention;

[0051] Figure 2 A flow chart of a standard management module provided by the present invention;

[0052] Figure 3 This is a flow chart of the intelligent collaborative editing module provided by the present invention. DETAILED DESCRIPTION

[0053] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] The present invention provides a method and system for professional online collaborative editing of hydropower project cost plans. The method and system are based on a microservice architecture and are intelligent online collaborative editing methods and systems for hydropower projects. The method and system combine natural language processing (NLP) technology, deep learning algorithms, and transaction management mechanisms. The method and system have real-time grammar and spelling checking, intelligent recommendation, semantic understanding, real-time difference detection, multi-user conflict processing, and version control functions for reported content. The method solves the problems of high communication costs, difficult version control, lax data verification, and unsmooth multi-user collaboration in the preparation of hydropower project cost plans.

[0055] The present invention provides a method for online collaborative editing of hydropower engineering cost plans by profession, referring to Figure 1 to Figure 3 , including the following steps:

[0056] Step S1, standard management process:

[0057] Based on the deep learning model, the text logic relationship and entry structure of the industry standard documents are automatically parsed and the data is standardized, and a system rule set is generated and stored in the MySQL database; based on the system rule set, standardized reporting templates for various professions are automatically generated;

[0058] Step S1 is specifically as follows:

[0059] Step S1.1, using the integrated EasyExcel tool to perform data structured reading on the industry standard file, combining the pre-trained deep learning model to parse the industry terms, technical indicators, and project division content in the industry standard file, parse to obtain the original data structure, and store it as a temporary data structure;

[0060] Step S1.2, using the dependency analysis model to perform logical conversion and field mapping on the parsed original data structure, mapping it into multiple entry contents with logical relationships; performing dependency analysis on each of the entry contents, converting the entry contents into a system rule set and mapping them to standardized fields in the database, thereby obtaining a mapped system rule set;

[0061] Step S1.3, the mapped system rule set is persistently stored in a MySQL database, and a corresponding database index is configured for each rule in the mapped system rule set and a unique identifier is assigned;

[0062] Step S1.4, based on the mapped system rule set, automatically generate standardized reporting templates for each profession.

[0063] Each of the standardized reporting templates includes the following: the mapped system rule set and reporting fields;

[0064] The standardized reporting template has the following functions: it is embedded with an NLP model and a Transformer model; when the reporting field is entered with reporting content, the NLP model is called to perform real-time verification of the reporting content and generate intelligent recommended content; the Transformer model is called to dynamically analyze the reporting content, give reporting suggestions, and automatically complete or provide contextual prompts.

[0065] Step S1.5, when industry standards or project requirements change, the corresponding rules are updated through the system front-end management interface, and the updated rules are automatically stored in the MySQL database, replacing the old rules in the mapped system rule set, thereby obtaining an updated system rule set;

[0066] According to the updated system rule set, the corresponding standardized reporting template is automatically updated; when the standardized reporting template is updated, a new rule constraint logic is triggered to generate and step S1.6 is executed;

[0067] Step S1.6: the updated standardized reporting template is distributed to the front end through the API interface, and the latest system rule set and the standardized reporting template are distributed to relevant users in combination with the real-time push mechanism; at the same time, the rule and template update information is pushed to the relevant users, and the users are intelligently reminded of the applicability of the latest system rule set, and suggested to change the filling content to ensure compliance with the latest standards. All the system rule set and standardized reporting template update operations are performed through transaction management to ensure data consistency;

[0068] Step S1.7, regularly back up the latest system rule set and the standardized reporting template, and generate different versions of the system rule set based on the methods of steps S1.1 and S1.2, support version backtracking and comparison, and ensure rapid recovery and version tracking when industry standards change; when major changes occur in industry standards, be able to quickly restore and manage versions to enhance the stability and adaptability of the system.

[0069] Step S2, intelligent collaborative editing process:

[0070] When it is detected that a user is filling in data for the standardized filling template, the user's filling content is verified in real time and relevant content is intelligently recommended. It also has a batch data import function, and automatically fills the batch imported content into the corresponding position of the standardized filling template;

[0071] When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time;

[0072] Step S2 is specifically as follows:

[0073] Step S2.1, when the system detects that a user has logged in, the system dynamically loads a template selection interface corresponding to the user's authority according to the user's authority, wherein the template selection interface has a template selection list, and the template selection list has template identifiers of multiple standardized reporting templates; each of the standardized reporting templates is pre-defined according to the system rule set, and contains specific reporting fields and corresponding verification logic to ensure the accuracy of data reporting;

[0074] Step S2.2, when the user enters the filling content for a filling field in the selected standardized filling template, the system front-end page dynamically adds and deletes the engineering quantities that have been filled in the sub-items or subsets through JavaScript scripts, and can perform real-time verification of the filling content according to the stored system rule set, including the data format, value range and logical relationship between fields, and uses regular expressions to ensure that the filling content conforms to the expected format and meets the established standards;

[0075] The NLP module integrated in the system uses the deep learning model BERT to perform grammar checking, spelling correction and intelligent recommendation on the reported content: Specifically, by calling the NLP model, the semantic structure of the reported content is analyzed in real time, grammatical errors are marked and spelling correction suggestions are provided. Based on the semantic understanding of the NLP model, the NLP model automatically detects incorrect use of industry terms, recommends appropriate words or phrases, and provides an automatic summary function to condense long paragraphs into concise sentences, helping users to complete data reporting efficiently;

[0076] Step S2.3: For scenarios with complex or large-scale reporting, the Excel batch import function can be used to upload the reported files to the standardized reporting template, and the EasyExcel tool can be used to parse the file content, automatically fill in the corresponding reporting fields in the standardized reporting template, and verify the reported content of each reporting field one by one to ensure the integrity and standardization of the data after the file is imported;

[0077] Step S2.4: The system uses a machine learning recommendation algorithm based on user behavior to optimize reporting suggestions by analyzing the user's historical operating habits. Specifically, the system automatically generates reporting content suggestions based on the reporting content entered by the user and the fields that are frequently reported. For reporting fields that are repeatedly entered, the system prompts the user to report the commonly used values ​​in advance. The system supports dynamic adjustment of reporting content, records the reporting content entered by the user each time, and adjusts future recommendation strategies based on the machine learning model.

[0078] Step S2.5, in the multi-user collaborative scenario, the system adopts the multi-user collaborative editing OT algorithm and optimistic locking mechanism to ensure the real-time synchronization of reporting operations of different users; specifically: the OT algorithm converts the reporting operation when the user submits it to ensure that there is no conflict when each user edits the same standardized reporting template; before the user submits the change, the system converts the change to ensure that the document remains consistent; the optimistic locking mechanism is used to manage user concurrent operations, each user holds a lock during the operation, and releases the lock after submission to ensure data consistency in high concurrency scenarios.

[0079] Step S2.6, after the user completes filling in all the reporting fields of the standardized reporting template, the system performs a global data verification and calls the backend rule set to perform a final check on all the reporting fields, including comprehensive verification of whether there are unfilled fields, the format of the reporting fields, and the correlation between the reporting fields, to ensure that the reported content is logically consistent;

[0080] Step S2.7, after verification, the completed standardized reporting template generates the latest version of the project plan, and the latest version of the project plan is formally submitted and stored in the database. The submitted project plan serves as the standard record in the project and updates the reporting status.

[0081] Step S3, publishing status synchronization update process:

[0082] When the standardized reporting template is completed, the latest version of the project plan is formed; the project plan is published, and the publishing status of the project plan is synchronized in real time; combined with the model algorithm, the impact scope of the project plan after release is intelligently analyzed, and the user is prompted to incrementally update or fully update the old version of the project plan, and automatic rollback is supported in abnormal situations to ensure the integrity of the published project plan; the system automatically records the release version information and change log of the project plan.

[0083] Step S3 is specifically as follows:

[0084] Step S3.1, before the project plan is released, the system will integrate the project plans submitted by various majors, and the integrated project plans will be locked through the transaction management mechanism to prevent them from being modified by other users during the release process; before the project plan is released, the system will check the submission status of each major to ensure that all data has been completed and verified, and there are no abnormal records; after the integration is completed, the system will mark it as "pending release" and prepare to enter the release process;

[0085] Step S3.2, after data integration and verification are completed, the project plan is published to subsequent processing or external systems through the REST API. The publishing supports batch publishing, that is, the project plans of multiple disciplines can be published at one time through the bound projects. The publishing status will be synchronously updated to the system database. The system records the timestamp, publisher and content of each publishing operation, and updates the overall progress of the project at the same time. Users can view the latest data publishing status of the current project through the status update module;

[0086] Step S3.3, when the project plan is subsequently updated or adjusted, the system supports incremental updates, can automatically identify all modifications since the last release, and release after rule verification. After the release is completed, the system automatically updates the corresponding version number and records the specific changes of the incremental update; the system maintains the version control information of each release, and the user can view any version as needed to ensure that the project data will be traceable.

[0087] Step S3.4, after each release or incremental update of the project plan, the system synchronizes the latest status to the front-end interface: specifically, based on the push mechanism of REST API, whenever the status of the project plan changes, the system immediately notifies all relevant users, so that all relevant users can grasp the progress of the project in real time. After the user receives the status update, the front-end interface is updated accordingly, including the latest status, version number and change summary of the project plan, so that users can quickly obtain project dynamics;

[0088] Step S3.5, during the process of publishing or updating the status of the project plan, when encountering an abnormal situation, the system automatically triggers the rollback mechanism. Through the transaction management function of MySQL, it ensures that all data is rolled back to the pre-publishing state when an error occurs during the publishing process, so as to avoid incomplete or erroneous data affecting the project progress.

[0089] The present invention also provides a system for online collaborative editing of hydropower engineering cost plans by profession. The system is based on deep learning and natural language processing (NLP) technology, integrates the BERT model, and realizes intelligent grammar checking, spelling correction and content recommendation. The system includes three modules: standard management, intelligent collaborative editing and status synchronization. The modular design realizes flexible expansion and efficient collaboration. The modules interact with each other through standardized interfaces, aiming to improve work efficiency, optimize the information transmission process, and ensure data consistency and real-time update.

[0090] The standard management module is used to automatically parse the text logic relationship and entry structure of industry standard documents and perform data standardization conversion based on the deep learning model, generate a system rule set and store it in the MySQL database; based on the system rule set, automatically generate standardized reporting templates for various professions;

[0091] The intelligent collaborative editing module is used to verify the user's reported content in real time and intelligently recommend relevant content when it is detected that the user is filling in data for the standardized reporting template, and has a batch data import function to automatically fill the batch imported content into the corresponding position of the standardized reporting template;

[0092] When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time;

[0093] The release status synchronization update module is used to form the latest version of the project plan when the standardized reporting template is completed; publish the project plan and synchronize the release status of the project plan in real time; combine the model algorithm to intelligently analyze the impact scope of the project plan after release, prompt the user to incrementally update or fully update the old version of the project plan, and support automatic rollback in abnormal situations to ensure the integrity of the released project plan; the system automatically records the release version information and change log of the project plan.

[0094] The present invention provides a method and system for online collaborative editing of hydropower engineering cost plans by profession, which has the following characteristics:

[0095] This system includes a standard management module, an intelligent collaborative editing module and a release status synchronization module. The system implements modular design through a microservice architecture, allowing the standard management module, the intelligent collaborative editing module and the release status synchronization module to operate independently through standardized interfaces, thereby achieving flexible expansion and efficient collaboration.

[0096] The standard management module automatically parses industry standard documents and performs data standardization conversion based on deep learning models (Transformer and BERT), generates a system rule set and stores it in the MySQL database, and generates a professional standardized reporting template through the dependency analysis function of the NLP model.

[0097] The parsing and conversion method of the standard management module includes the following steps:

[0098] Use the EasyExcel tool to read the tabular data of industry standard files, combine the pre-trained BERT model to parse industry terms, technical indicators, project divisions, etc., and store the parsed data as a temporary data structure.

[0099] The spaCy dependency analysis model is used to perform logical transformation and field mapping on the parsed data, generate a system rule set and map it to standardized fields in the database, ensuring that the system can perform accurate automatic verification based on industry terminology and data logic.

[0100] The generated rule set is persistently stored in the MySQL database, and a unique identifier is configured for each rule. The transaction management feature of InnoDB is used to ensure the consistency and integrity of data during the storage process.

[0101] The intelligent collaborative editing module integrates the natural language processing (NLP) model and the multi-user collaborative editing algorithm (Operational Transformation, OT), providing real-time verification, spell checking, intelligent recommendation and multi-user collaboration functions; among them, the OT algorithm and optimistic locking mechanism are used to ensure the data consistency and real-time editing operations of multiple users in the collaborative editing process.

[0102] The collaborative editing method of the intelligent collaborative editing module comprises the following steps:

[0103] After the user logs in, the system dynamically loads standardized reporting templates that meet professional needs based on permissions to ensure that the user's reporting data complies with industry standards.

[0104] During the reporting process, JavaScript scripts are used to perform real-time format verification and logical relationship verification on the input data, and the NLP model is combined to implement grammar checking, spelling correction and intelligent recommendations to improve data entry accuracy.

[0105] The OT algorithm and optimistic locking mechanism are used to achieve real-time and consistency of editing operations in multi-user collaboration scenarios, ensuring that the editing operations of all users do not conflict.

[0106] It supports batch data import function, uses EasyExcel tool to parse Excel files uploaded by users, automatically fills them into the template, and verifies the batch imported data one by one.

[0107] The release status synchronization module implements real-time synchronization and update of project status through the REST API interface, supports incremental updates and version control, and provides a data rollback mechanism in abnormal situations to ensure the integrity and consistency of data during the release process.

[0108] The real-time synchronization and incremental update method of the publishing status synchronization module comprises the following steps:

[0109] The system locks the published data through the transaction management mechanism before the data is released to ensure the integrity of the data during the release process.

[0110] Publish data in batches and update the status synchronously through the REST API. The system records the timestamp, publisher, and content of each release. It also supports incremental update mode, automatically identifying modifications since the last release and updating the version number.

[0111] The latest status is pushed to front-end users in real time through the API interface, and when an abnormal situation occurs during the release or status update process, the rollback mechanism is automatically triggered to restore the data to the state before release to ensure data integrity and consistency.

[0112] The system functions have been further expanded to realize related functions including automatic version control and data tracing, which can support the tracing and comparison of system rule sets and historical versions of data reporting, and provide data change log recording function to record the time, operation user and change content of each data operation to ensure data traceability. Therefore, through system log tracing and tracing back historical versions of data, the transparency of system data changes can be guaranteed, and data recovery function can be provided in abnormal situations to ensure data integrity.

[0113] The present invention provides an efficient intelligent collaborative editing system for hydropower engineering cost solutions. Through microservice architecture design, combined with deep learning, natural language processing (NLP) technology and multi-user collaborative editing algorithms, the accuracy of data entry, the efficiency of collaborative editing and the real-time performance of project management are comprehensively improved. Compared with traditional cost solution management tools, the present invention has achieved significant technical breakthroughs and optimization effects in data standardization management, real-time collaboration, intelligent recommendation and incremental updates in response to the specific needs of engineering cost business. The specific effect analysis is as follows:

[0114] 1. Data Standardization Management and Accuracy Improvement

[0115] In the field of hydropower engineering cost, different projects and professional teams use different reporting templates and specifications. Traditional editing systems usually only support static Excel templates or basic rule verification, resulting in inconsistent data entry standards and high error rates, which brings difficulties to later review and management. To address this problem, the standard management module of the present invention uses the dependency analysis function of the deep learning model (Transformer and BERT) to parse industry specifications and generate dynamic standardized reporting templates, so that the data entry process complies with unified industry standards.

[0116] Experimental method: Among 100 real hydropower projects, 50 projects were selected to use the system of the present invention, and the remaining 50 projects used the traditional system, and the standard consistency and input error rate of the data were counted.

[0117] Evaluation criteria: input error rate, data consistency and audit efficiency.

[0118] Input error rate: The error rate of this system is controlled below 2%, which is much lower than the 10% of traditional systems, effectively reducing the problem of inconsistent data and repeated review of cost plans between different projects.

[0119] Data consistency: The data consistency of this system reaches more than 99%, while the traditional system is only 75%, which significantly improves the standardization of data.

[0120] Audit efficiency: After using this system, data audit efficiency has increased by more than 50%. The traditional system audit takes 2 hours / project, while this system only takes 0.5 hours / project.

[0121] 2. Improvements in collaborative editing efficiency and data conflict management

[0122] The cost plan of hydropower projects usually requires multiple professional teams (such as civil engineering, electromechanical and installation, etc.) to jointly edit. Traditional cost tools do not support real-time collaboration, resulting in frequent editing conflicts, chaotic version management, and inefficient project progress. This invention introduces a multi-user collaborative editing algorithm (OT) and an optimistic locking mechanism to achieve real-time multi-user editing synchronization and conflict management, so that when multiple users edit the same project on different devices at the same time, operations do not conflict and are updated in real time.

[0123] Experimental method: 50 multi-user project teams were selected from 100 real hydropower projects, with 4 members in each team, to edit the same cost plan file at the same time. 25 teams used this system and 25 teams used traditional document editing tools, and a comparison was made.

[0124] Evaluation criteria: Statistics on the time required for each team to complete the edit, the number of multi-user editing conflicts, and the user satisfaction score.

[0125] Average editing time: The average editing time for teams using this system is 30 minutes, which is 200% more efficient than the 90 minutes for traditional systems, effectively reducing cross-departmental communication costs.

[0126] · Number of editing conflicts: The number of editing conflicts in the system of the present invention is only 1 per team on average, while the number of conflicts in traditional tools is 5, which is reduced by 80%.

[0127] User satisfaction: The team satisfaction score of this system is 4.8 (out of 5 points), while the traditional system is 3.2, reflecting the users’ high recognition of the smoothness of collaboration and the operating experience.

[0128] (III) Intelligent recommendation and improved reporting efficiency

[0129] Traditional cost plan editing tools cannot provide intelligent reporting assistance. Users need to repeatedly refer to industry terms and standards when filling in the form, which consumes a lot of time and energy. The present invention realizes grammar checking, spelling correction and content recommendation functions by integrating the NLP model (BERT). The intelligent recommendation system based on industry terms not only improves the accuracy of reporting, but also significantly shortens the reporting time.

[0130] Experimental method: For 100 engineering cost projects, 50 teams were randomly selected to use the system of the present invention, and the other 50 teams used traditional tools. The time it took for users to complete the reporting was counted, and the efficiency of data entry was analyzed.

[0131] Evaluation criteria: reporting time, reporting accuracy and applicability of reporting suggestions.

[0132] · Reporting time: The reporting time for users using this system is reduced to 40 minutes, compared to 90 minutes with traditional tools, an efficiency improvement of 125%.

[0133] Reporting accuracy: The intelligent recommendations and syntax checking provided by this system have increased reporting accuracy to 98%, while the reporting accuracy of traditional tools is 85%.

[0134] Applicability of reporting suggestions: The user satisfaction of this system with reporting suggestions reached 95%. Intelligent recommendations make the reporting process smoother and reduce the time users spend looking up industry terms.

[0135] Two embodiments are described below:

[0136] Embodiment 1:

[0137] This embodiment provides an intelligent collaborative editing system for hydropower project cost solutions developed based on a microservice architecture. The system is based on deep learning and natural language processing (NLP) technology, and implements intelligent grammar checking, spelling correction, and content recommendation by integrating a BERT model.

[0138] The standard management module is responsible for parsing industry standard data into system rule sets, storing them in the MySQL database, using the dependency analysis function of the Transformer model to identify text logical relationships and entry structures, improving the accuracy and consistency of standard parsing, and generating professional reporting templates to ensure that data complies with standards;

[0139] The intelligent collaborative editing module provides real-time verification, batch import, multi-user collaboration and intelligent recommendation functions based on rule sets to improve the accuracy and efficiency of data entry; multi-user collaboration adopts the Operational Transformation (OT) algorithm and optimistic locking mechanism to ensure the real-time and consistency of editing operations;

[0140] The publishing status synchronization module uses different colors to display the publishing status of different professions in real time through identity authentication and permission control. Combined with the model algorithm, the publishing status can intelligently analyze the impact range after the data change, prompt the user to update incrementally or fully, and support automatic rollback in abnormal situations to ensure data integrity.

[0141] The implementation method of the standard management module specifically includes the following steps:

[0142] S01. The system uses the integrated EasyExcel tool to read the industry standard files in a structured manner, and combines the pre-trained model (BERT) to parse the project division, technical and economic indicators, mechanical library, industry terms and rule items in the table. The parsed raw data is stored as a temporary data structure, awaiting subsequent processing.

[0143] S02. The parsed data is logically transformed and field mapped using a rule model, and dependency analysis is performed through the spaCy model. The entry content is converted into a system rule set and mapped to standardized fields in the database. Automatic verification and comparison are provided based on the semantic understanding of industry terms, and the data is associated with professional fields in the database to ensure that the system can perform data verification and operations in accordance with industry standards.

[0144] S03. The converted rule set is persistently stored in the MySQL database. The system configures the corresponding database index for each rule and assigns a unique identifier to each rule entry so that it can be quickly retrieved and executed later, optimizing the query and execution efficiency of the rule set. At the same time, the transaction management feature of the InnoDB engine is used to ensure the consistency and data integrity of the rules during storage.

[0145] S04. The system automatically generates standardized reporting templates for various majors based on the rule set. Each template contains a mapped rule set. The reporting fields contain intelligent recommendations and real-time verification logic generated by the NLP model. Combined with the Transformer model, it dynamically analyzes possible reporting suggestions based on the input content, automatically completes or provides contextual prompts. When users use the template to report, the system will automatically call the corresponding rules for verification.

[0146] S05. When industry standards or project requirements change, the administrator updates the rules through the front-end management interface. The system automatically stores the updated rules in the MySQL database and replaces the old rules. The updated template triggers model re-analysis, generates new rule constraint logic and distributes it to relevant users.

[0147] S06. New templates are distributed to the front end through the API interface, and the latest rules and templates are distributed to relevant users in combination with the real-time push mechanism to ensure that the templates they use meet the latest standards. At the same time, the system pushes rule and template update information to users, intelligently reminds users of the applicability of new rules, and recommends changes to fill in the content to ensure compliance with the latest standards. All rule update operations are performed through transaction management to ensure data consistency.

[0148] S07. The system regularly backs up rule data and generates different versions of rule sets based on the model, supports version backtracking and comparison, ensures rapid recovery and version tracking when standards change, and can quickly restore and manage versions when major changes occur in industry standards, thereby enhancing the stability and adaptability of the system.

[0149] The intelligent collaborative editing module, also known as the implementation method of the professional online reporting module, specifically includes the following steps:

[0150] S01. After the user logs in, the system dynamically loads the corresponding template selection interface according to the user's permissions. The user selects a standardized template that matches the expected work from the template list. Each template is pre-defined according to the system rule set and contains a specific field structure and corresponding verification logic to ensure the accuracy of data reporting.

[0151] S02. When the user fills in each field in the template, the front-end page can dynamically add or delete sub-items or subsets of the already filled-in engineering quantities through JavaScript scripts, and can perform real-time verification of the input data based on the stored rule set. The verification content includes data format, value range and logical relationship between fields, and uses regular expressions to ensure that the input data (such as date, value, etc.) conforms to the expected format and the input content conforms to the established standards.

[0152] S03. The NLP module integrated in the system uses a deep learning model (BERT) for grammar checking, spelling correction and intelligent recommendation. When the user enters content, the NLP model can parse the semantic structure of the sentence in real time, mark grammatical errors and provide spelling correction suggestions. Based on the semantic understanding of the model, the NLP module can automatically detect incorrect use of industry terms, recommend appropriate words or phrases, and provide automatic summarization function to condense long paragraphs into concise sentences, helping users to complete data reporting efficiently.

[0153] S04. For scenarios with more complex or large-volume data, users can use the Excel batch import function to upload the completed files, and use the EasyExcel tool to parse the file content, automatically fill in the corresponding fields in the template, and verify each data one by one to ensure the integrity and standardization of the data after import.

[0154] S05. The system uses a machine learning recommendation algorithm based on user behavior. It optimizes the reporting suggestions by analyzing the user's historical operation habits. The recommendation system automatically generates content suggestions based on the user's input content and frequently reported fields. For fields that are repeatedly entered, the system will prompt the user to fill in the commonly used values ​​in advance. The recommendation system supports dynamic adjustment of content. Each user input will be recorded, and future recommendation strategies will be adjusted based on the machine learning model.

[0155] S06. In multi-user collaboration scenarios, the system uses the Operational Transformation (OT) algorithm and optimistic locking mechanism to ensure that operations of different users can be synchronized in real time. The OT algorithm transforms the operation when the user submits it to ensure that there will be no conflicts when each user edits the same document. Before the user submits the change, the system will transform the change to ensure that the document remains consistent. The optimistic locking mechanism is used to manage user concurrent operations. Each user holds a lock during the operation and releases the lock after submission to ensure data consistency in high-concurrency scenarios.

[0156] S07. After the user completes all filling, the system will perform global data verification and call the backend rule set to perform a final check on all fields, including comprehensive verification of whether there are unfilled areas, field formats, and correlations between fields, to ensure that the data is logically consistent.

[0157] S08. After verification, the system will formally submit the data and store it in the formal data table in the database. The submitted data will be used as the standard record in the project, and the reporting status will be updated to ensure the real-time data transmission.

[0158] The implementation method of the publishing status synchronization update module specifically includes the following steps:

[0159] S01. Before data is released, the system will integrate the reported data of each major. The integrated data will be locked through the transaction management mechanism to prevent it from being modified by other users during the release process. Before data is released, the system will check the submission status of each major to ensure that all data has been completed and verified, and there are no abnormal records. After the data integration is completed, the system will mark it as "pending release" and prepare to enter the release process.

[0160] S02. After data integration and verification are completed, the data will be published to subsequent processing or external systems through the REST API. Batch publishing is supported, that is, data from multiple disciplines can be published at one time through bound projects. The published data status will be synchronously updated to the system database. The system records the timestamp, publisher, and content of each publishing operation, and updates the overall progress of the project at the same time. Users can view the latest data publishing status of the current project through the status update module.

[0161] S03. When the data is subsequently updated or adjusted, the system supports incremental updates, automatically identifies all modifications since the last release, and releases after rule verification. After the release is completed, the system automatically updates the corresponding version number and records the specific changes of the incremental update. The system maintains the version control information of each release, and users can view any version as needed to ensure that the project data will be traceable.

[0162] S04. After each release or incremental update, the system can synchronize the latest status to the front-end interface. Based on the REST API push mechanism, whenever the project status changes (release or update), the system will immediately notify all relevant users so that they can grasp the progress of the project in real time. After the user receives the status update, the front-end interface will be updated accordingly, including the latest status of the data, version number and change summary, so that users can quickly obtain project dynamics.

[0163] S05. During the release or status update process, if an abnormal situation (network interruption) occurs, the system will automatically trigger the rollback mechanism. Through the transaction management function of MySQL, it ensures that all data can be rolled back to the pre-release state when an error occurs during the release process, avoiding incomplete or erroneous data from affecting the project progress.

[0164] Embodiment 2:

[0165] This example demonstrates the specific application of the online collaborative editing system for hydropower engineering cost plans in the process of project creation, data reporting, plan release and status synchronization, covering the reporting and management of the quantities of each professional sub-item in the pre-feasibility study and feasibility study stages of the project. The system realizes multi-user collaborative editing, real-time data synchronization and intelligent reporting, greatly optimizing the editing process of hydropower engineering cost plans.

[0166] S1: Project creation and collaboration member addition

[0167] ① Project creation: After the project leader logs into the system, he / she creates a new hydropower engineering cost project in the "Project Management" interface and enters the basic information of the project, such as project name, location, project scale, etc., so that the system can generate the basic ledger information of the project.

[0168] ② Select the project stage: The project leader sets the design stage of the project to the pre-feasibility study stage or the feasibility study stage according to the actual situation of the project. Different design stages correspond to different engineering depth requirements and industry specifications. The system will call the corresponding filling template in the subsequent steps according to the selected stage.

[0169] ③ Add collaborative members and assign permissions: After the project is created, the project leader can use the "Member Management" function to add the basic information of the collaborative members, including the persons in charge and participants of each profession (such as construction, dam work, waterways, and factories).

[0170] ④Permission configuration: The project leader configures the module permissions and operation permissions of members through the system interface according to the professions and division of labor within the project that each member is responsible for. Each member can only access and edit authorized professional modules to ensure data security and accuracy of operation permissions during the collaboration process.

[0171] Through this step, the project team completed the initial setup of the project, and the heads of each discipline obtained the authority to enter the sub-discipline reporting module, preparing for the subsequent engineering quantity reporting and collaborative work.

[0172] S2: Each professional person in charge fills in the project quantity according to the authority

[0173] ① Enter the professional reporting module: After the person in charge of each profession (construction, dam construction, waterway, plant, electromechanical, metal structure) logs in to the system, click to enter the professional reporting module on the project homepage. The system automatically loads the standardized reporting template that complies with the specifications according to the current stage of the project, and the person in charge of each profession can report by item according to the stage depth.

[0174] ② Filling in the project quantity of each project: The person in charge of each discipline shall fill in the project quantity in detail according to the actual needs of the project and the standardized filling template provided by the system. The specific process is as follows:

[0175] 1- Hydraulic engineering: According to the design depth of the project, fill in the sub-item engineering quantity of hydraulic structures, including seepage control projects, spillways, flood discharge tunnels, energy dissipation and anti-scouring structures, etc. The details are as follows:

[0176] Seepage control project: fill in the sub-item engineering quantity of the water storage structure.

[0177] Spillway: List the sub-item quantities according to the functional sections (such as diversion channel, control section, chute section, outlet section).

[0178] · Flood discharge tunnel and sand flushing hole: For underground caverns, the sub-item engineering quantities are listed separately according to the inlet section, pressurized section, control section, non-pressurized section and outlet section.

[0179] Water delivery buildings: List the sub-item quantities according to the headworks buildings, water diversion channels, forebays, surge tanks, pressure tunnels, pressure pipes and other sub-parts, including the specific materials and structural information of each building to ensure the accuracy of the subsequent cost accounting.

[0180] Power generation buildings: The construction quantities of power plant buildings are listed in detail by construction division, including the quantities of steel bars, concrete, structural decoration and other sub-items, and detailed to the specific materials and construction quantities of power plant buildings and power generation foundations.

[0181] · Step-up substation buildings: According to the requirements of the partial engineering quantity of the ground substation, underground substation, busbar tunnel, outlet tunnel and other buildings, fill in the specific engineering quantity of the basic structure and connection equipment of the power station project item by item.

[0182] Slope and debris flow control: For large-scale slope, landslide and debris flow control projects, fill in the detailed slope treatment project quantity, list it in the order of construction (such as earth excavation, stone hole excavation, concrete, anchor rod, etc.), and indicate the special construction requirements, such as soil-rock ratio, concrete gradation, shotcrete thickness, anchor rod specifications, etc.

[0183] 2-Detailed filling of engineering quantities: During the filling process, the intelligent recommendation function and standardized filling template provided by the system will guide the professional person in charge to fill in the specific information of each sub-item engineering quantity according to the specifications, including but not limited to:

[0184] Earthwork excavation: clarify the earthwork ratio (e.g. earthwork ratio is 2:8) to facilitate construction planning and cost accounting.

[0185] ·Concrete: grading items, such as different gradations of C20 and C25; the total concrete quantity can also be provided.

[0186] Detailed information of anchor rods, steel pipes, etc.: Anchor rods must be marked with model and length (such as Φ22, l=3m), and pressure steel pipes must be marked with wall thickness and pipe diameter, etc., to ensure the standardization and uniformity of engineering materials.

[0187] The standardized reporting template for this step automatically loads reporting rules and verifies data in real time to ensure that the data complies with industry standards. At the same time, the intelligent recommendation function helps users complete the automatic reporting of commonly used items and improves data entry efficiency.

[0188] S3: Solution publishing and status synchronization

[0189] ① Plan release: After each professional leader completes the report, he / she can submit the currently reported plan through the release button. The release operation will automatically trigger the system's real-time status synchronization mechanism and synchronize the latest reported data to the project ledger list.

[0190] ② Status synchronization and real-time update: After the plan is released, the project ledger list will show the latest status reported by each discipline. The project leader and other authorized users can view the update of the plan in the "Release Status Synchronization" area.

[0191] ③ View published content: Each collaborative member can click on the publishing status in the project ledger list to view the specific content of the published plan to ensure that project team members have a comprehensive understanding of the progress and data content of each discipline.

[0192] ④ Incremental updates and multiple modifications: At different stages of the project, if the heads of various disciplines need to adjust the plan, they can modify the reporting content through the incremental update function of the system. The system will record each update and generate a new version. The project leader and collaborative members can view the version changes to understand the actual progress of the project and the details of the modification.

[0193] ⑤Permission management and data security: During the process of program publishing and status synchronization, the system strictly controls the permissions of each user. Only authorized users can publish and view program content, ensuring data security and hierarchical permission management of project members.

[0194] Through the above steps, the present invention realizes the intelligent filling and efficient collaborative editing of the hydropower project cost plan, so that multiple parties can collaborate to synchronously complete data entry and update on the same platform. At the same time, based on the incremental update and status synchronization functions, project team members can grasp the latest status and engineering quantity details of the project at any time, which improves the transparency and traceability of project data.

[0195] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. A method for online collaborative editing of hydropower project cost plans by profession, characterized in that: The following steps are involved: Step S1, standard management process: Based on the deep learning model, the text logic relationship and entry structure of the industry standard documents are automatically parsed and the data is standardized, and a system rule set is generated and stored in the MySQL database; based on the system rule set, standardized reporting templates for various professions are automatically generated; Step S2, intelligent collaborative editing process: When it is detected that a user is filling in data for the standardized filling template, the user's filling content is verified in real time and relevant content is intelligently recommended. It also has a batch data import function, and automatically fills the batch imported content into the corresponding position of the standardized filling template; When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time; Step S3, publishing status synchronization update process: When the standardized reporting template is completed, the latest version of the project plan is formed; the project plan is published, and the publishing status of the project plan is synchronized in real time; combined with the model algorithm, the impact scope of the project plan after release is intelligently analyzed, and the user is prompted to incrementally update or fully update the old version of the project plan, and automatic rollback is supported in abnormal situations to ensure the integrity of the published project plan; the system automatically records the release version information and change log of the project plan.

2. The method for online collaborative editing of hydropower project cost plans by profession according to claim 1 is characterized in that: Step S1 is specifically as follows: Step S1.1, using the integrated EasyExcel tool to perform data structured reading on the industry standard file, combining the pre-trained deep learning model to parse the industry terms, technical indicators, and project division content in the industry standard file, parse to obtain the original data structure, and store it as a temporary data structure; Step S1.2, using the dependency analysis model to perform logical conversion and field mapping on the parsed original data structure, mapping it into multiple entry contents with logical relationships; performing dependency analysis on each of the entry contents, converting the entry contents into a system rule set and mapping them to standardized fields in the database, thereby obtaining a mapped system rule set; Step S1.3, the mapped system rule set is persistently stored in a MySQL database, and a corresponding database index is configured for each rule in the mapped system rule set and a unique identifier is assigned; Step S1.4, based on the mapped system rule set, automatically generate standardized reporting templates for each profession.

3. The method for online collaborative editing of hydropower project cost plans by profession according to claim 2 is characterized in that: In step S1.4, each of the standardized reporting templates includes the following contents: the mapped system rule set and reporting fields; The standardized reporting template has the following functions: it is embedded with an NLP model and a Transformer model; when the reporting field is entered with reporting content, the NLP model is called to perform real-time verification of the reporting content and generate intelligent recommended content; the Transformer model is called to dynamically analyze the reporting content, give reporting suggestions, and automatically complete or provide contextual prompts.

4. The method for online collaborative editing of hydropower project cost plans by profession according to claim 2 is characterized in that: Also includes: Step S1.5, when industry standards or project requirements change, the corresponding rules are updated through the system front-end management interface, and the updated rules are automatically stored in the MySQL database, replacing the old rules in the mapped system rule set, thereby obtaining an updated system rule set; Automatically update the corresponding standardized reporting template according to the updated system rule set; When the standardized reporting template is updated, a new rule constraint logic is generated and step S1.6 is executed; Step S1.6: the updated standardized reporting template is distributed to the front end through the API interface, and the latest system rule set and the standardized reporting template are distributed to relevant users in combination with the real-time push mechanism; at the same time, the rule and template update information is pushed to the relevant users, and the users are intelligently reminded of the applicability of the latest system rule set, and suggested to change the filling content to ensure compliance with the latest standards. All the system rule set and standardized reporting template update operations are performed through transaction management to ensure data consistency; Step S1.7, regularly back up the latest system rule set and the standardized reporting template, and generate different versions of the system rule set based on the methods of steps S1.1 and S1.2, support version backtracking and comparison, and ensure rapid recovery and version tracking when industry standards change; when major changes occur in industry standards, be able to quickly restore and manage versions to enhance the stability and adaptability of the system.

5. The method for online collaborative editing of hydropower project cost plans by profession according to claim 1 is characterized in that: Step S2 is specifically as follows: Step S2.1, when the system detects that a user has logged in, the system dynamically loads a template selection interface corresponding to the user's authority according to the user's authority, wherein the template selection interface has a template selection list, and the template selection list has template identifiers of multiple standardized reporting templates; each of the standardized reporting templates is pre-defined according to the system rule set, and contains specific reporting fields and corresponding verification logic to ensure the accuracy of data reporting; Step S2.2, when the user enters the filling content for a filling field in the selected standardized filling template, the system front-end page dynamically adds and deletes the engineering quantities that have been filled in the sub-items or subsets through JavaScript scripts, and can perform real-time verification of the filling content according to the stored system rule set, including the data format, value range and logical relationship between fields, and uses regular expressions to ensure that the filling content conforms to the expected format and meets the established standards; The NLP module integrated in the system uses the deep learning model BERT to perform grammar checking, spelling correction and intelligent recommendation on the reported content: Specifically, by calling the NLP model, the semantic structure of the reported content is analyzed in real time, grammatical errors are marked and spelling correction suggestions are provided. Based on the semantic understanding of the NLP model, the NLP model automatically detects incorrect use of industry terms, recommends appropriate words or phrases, and provides an automatic summary function to condense long paragraphs into concise sentences, helping users to complete data reporting efficiently; Step S2.3: For scenarios with complex or large-scale reporting, the Excel batch import function can be used to upload the reported files to the standardized reporting template, and the EasyExcel tool can be used to parse the file content, automatically fill in the corresponding reporting fields in the standardized reporting template, and verify the reported content of each reporting field one by one to ensure the integrity and standardization of the data after the file is imported; Step S2.4: The system uses a machine learning recommendation algorithm based on user behavior to optimize reporting suggestions by analyzing the user's historical operating habits. Specifically, the system automatically generates reporting content suggestions based on the reporting content entered by the user and the fields that are frequently reported. For reporting fields that are repeatedly entered, the system prompts the user to report the commonly used values ​​in advance. The system supports dynamic adjustment of reporting content, records the reporting content entered by the user each time, and adjusts future recommendation strategies based on the machine learning model. Step S2.5, in the multi-user collaborative scenario, the system adopts the multi-user collaborative editing OT algorithm and optimistic locking mechanism to ensure the real-time synchronization of reporting operations of different users; specifically: the OT algorithm converts the reporting operation when the user submits it to ensure that there is no conflict when each user edits the same standardized reporting template; before the user submits the change, the system converts the change to ensure that the document remains consistent; the optimistic locking mechanism is used to manage user concurrent operations, each user holds a lock during the operation, and releases the lock after submission to ensure data consistency in high concurrency scenarios.

6. The method for online collaborative editing of hydropower engineering cost plans by profession according to claim 5 is characterized in that: Also includes: Step S2.6, after the user completes filling in all the reporting fields of the standardized reporting template, the system performs a global data verification and calls the backend rule set to perform a final check on all the reporting fields, including comprehensive verification of whether there are unfilled fields, the format of the reporting fields, and the correlation between the reporting fields, to ensure that the reported content is logically consistent; Step S2.7, after verification, the completed standardized reporting template generates the latest version of the project plan, and the latest version of the project plan is formally submitted and stored in the database. The submitted project plan serves as the standard record in the project and updates the reporting status.

7. The method for online collaborative editing of hydropower engineering cost plans by profession according to claim 1 is characterized in that: Step S3 is specifically as follows: Step S3.1, before the project plan is released, the system will integrate the project plans submitted by various majors, and the integrated project plans will be locked through the transaction management mechanism to prevent them from being modified by other users during the release process; before the project plan is released, the system will check the submission status of each major to ensure that all data has been completed and verified, and there are no abnormal records; after the integration is completed, the system will mark it as "pending release" status and prepare to enter the release process; Step S3.2, after data integration and verification are completed, the project plan is published to subsequent processing or external systems through the REST API. The publishing supports batch publishing, that is, the project plans of multiple disciplines can be published at one time through the bound projects. The publishing status will be synchronously updated to the system database. The system records the timestamp, publisher and content of each publishing operation, and updates the overall progress of the project at the same time. Users can view the latest data publishing status of the current project through the status update module; Step S3.3, when the project plan is subsequently updated or adjusted, the system supports incremental updates, can automatically identify all modifications since the last release, and release after rule verification. After the release is completed, the system automatically updates the corresponding version number and records the specific changes of the incremental update; the system maintains the version control information of each release, and the user can view any version as needed to ensure that the project data will be traceable.

8. The method for online collaborative editing of hydropower engineering cost plans by profession according to claim 7 is characterized in that: Also includes: Step S3.4, after each release or incremental update of the project plan, the system synchronizes the latest status to the front-end interface: specifically, based on the push mechanism of REST API, whenever the status of the project plan changes, the system immediately notifies all relevant users, so that all relevant users can grasp the progress of the project in real time. After the user receives the status update, the front-end interface is updated accordingly, including the latest status, version number and change summary of the project plan, so that users can quickly obtain project dynamics; Step S3.5, during the process of publishing or updating the status of the project plan, when encountering an abnormal situation, the system automatically triggers the rollback mechanism. Through the transaction management function of MySQL, it ensures that all data is rolled back to the pre-publishing state when an error occurs during the publishing process, so as to avoid incomplete or erroneous data affecting the project progress.

9. A system for a method for online collaborative editing of hydropower project cost plans by profession according to any one of claims 1 to 8, characterized in that: include: The standard management module is used to automatically parse the text logic relationship and entry structure of industry standard documents and perform data standardization conversion based on the deep learning model, generate a system rule set and store it in the MySQL database; based on the system rule set, automatically generate standardized reporting templates for various professions; The intelligent collaborative editing module is used to verify the user's reported content in real time and intelligently recommend relevant content when it is detected that the user is filling in data for the standardized reporting template, and has a batch data import function to automatically fill the batch imported content into the corresponding position of the standardized reporting template; When multiple users collaboratively edit the standardized reporting template, the multi-user collaborative editing OT algorithm and optimistic lock mechanism are used to ensure that reporting operations of different users are synchronized in real time; The release status synchronization update module is used to form the latest version of the project plan when the standardized reporting template is completed; publish the project plan and synchronize the release status of the project plan in real time; combine the model algorithm to intelligently analyze the impact scope of the project plan after release, prompt the user to incrementally update or fully update the old version of the project plan, and support automatic rollback in abnormal situations to ensure the integrity of the released project plan; the system automatically records the release version information and change log of the project plan.

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