Business and group leadership cockpit construction method and device, equipment and medium

Abstract

The application discloses a kind of business and group leader cockpit construction method, device, equipment and medium.The method is collected by edge computing node the real-time operation data of multiple power plants, establishes three-dimensional data matrix according to real-time operation data;Business team post description information and group leader post description information are obtained, and business team post description information and group leader post description information are parsed according to natural language processing, and business team three-dimensional user portrait and group leader three-dimensional user portrait are constructed;According to the historical operation information corresponding to business team and group leader, business visualization interface and group visualization interface are respectively generated;Business team data access authority and group leader data access authority are determined according to business team three-dimensional user portrait and group leader three-dimensional user portrait;The construction of business cockpit group leader cockpit is completed.Solve the problem that traditional energy enterprise cockpit role requirement dynamic matching is difficult, realize cross-level, business data integration and display.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and particularly relates to a construction method and device of a business and group leader cockpit, equipment and medium. BACKGROUND

[0002] At present, in the management of energy enterprises, how to effectively integrate multi-source heterogeneous data and construct a cockpit system suitable for different roles has always been a technical difficulty in the industry. The traditional cockpit construction method is usually based on fixed templates and static index configurations, which is difficult to meet the individualized needs of different role users for data. For example, in the prior art, the construction of the cockpit often relies on manual configuration, lacks intelligent index matching and dynamic updating mechanism, resulting in single function of the cockpit and inability to effectively support cross-level and cross-business decision-making needs. SUMMARY

[0003] The present application provides a construction method, device, equipment and medium of a business and group leader cockpit, aiming to solve the problem that the traditional cockpit construction method is usually based on fixed templates and static index configurations, which is difficult to meet the individualized needs of different role users for data.

[0004] In a first aspect, the present application provides a construction method of a business and group leader cockpit, the method comprising:

[0005] Collecting real-time operation data of a plurality of power plants through an edge computing node, and establishing a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix comprises a device layer, a business layer and a management layer; the data corresponding to the device layer at least includes unit efficiency, fuel consumption and environmental indicators, the data corresponding to the business layer at least includes production KPI and operating cost, and the data corresponding to the management layer at least includes strategic indicators and industry benchmark data;

[0006] Obtaining business team post description information and group leader post description information, and constructing a business team three-dimensional user portrait and a group leader three-dimensional user portrait according to natural language processing analysis of the business team post description information and the group leader post description information; the business team three-dimensional user portrait and the group leader three-dimensional user portrait both include decision-making level, business field and attention dimension;

[0007] Generating a business visualization interface and a group visualization interface according to the historical operation information corresponding to the business team and the group leader, respectively; the visualization interface at least includes a data dashboard, a trend graph and a warning component;

[0008] Determining business team data access rights and group leader data access rights according to the business team three-dimensional user portrait and the group leader three-dimensional user portrait;

[0009] According to the three-dimensional data matrix, the association information, the business visualization interface, the group visualization interface, the business team data acquisition permission and the group leader data acquisition permission, a business cockpit group leader cockpit is constructed.

[0010] In some embodiments, the three-dimensional data matrix is established according to the real-time operation data, including: performing data cleaning and standardization processing on the real-time operation data to generate a device layer basic data pool; based on a preset association rule library, dynamically mapping the device layer data with a business index logical chain to construct a business layer derived index set; through an industry benchmarking algorithm, dynamically weighting the management layer data to generate a management layer index topology network containing a strategic weight coefficient; using a space-time association modeling technology, establishing a two-way data traceability channel between the device layer, the business layer and the management layer to form a three-dimensional data matrix architecture with a dynamic feedback mechanism.

[0011] In some embodiments, the business team three-dimensional user portrait and the group leader three-dimensional user portrait are constructed according to the natural language processing of the business team post description information and the group leader post description information, including: according to a domain knowledge graph, performing entity relationship extraction on the business team post description information and the group leader post description information to identify the core decision-making elements corresponding to the business team post description information and the group leader post description information; using an attention mechanism driven semantic analysis model, respectively obtaining the decision-making preference intensity coefficients corresponding to the business team post description information and the group leader post description information; performing feature extraction on the business team post description information and the group leader post description information to respectively obtain the post level features corresponding to the business team post description information and the group leader post description information; obtaining the historical behavior features corresponding to the historical operation information; and constructing the business team three-dimensional user portrait and the group leader three-dimensional user portrait according to the core decision-making elements, the decision-making preference intensity coefficients, the post level features and the historical behavior features.

[0012] For example, the method further includes: based on a dynamic attenuation algorithm, establishing a user portrait updating mechanism to automatically adjust the portrait dimension weight of the business team three-dimensional user portrait and the group leader three-dimensional user portrait according to the user operation log corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait.

[0013] In some embodiments, the generating the business visualization interface and the group visualization interface according to the historical operation information corresponding to the business team and the group leader respectively comprises: analyzing the historical operation information to obtain component interaction frequency and path jump characteristics for constructing a visualization element heat map; determining an interface template corresponding to the business visualization interface and the group visualization interface according to the visualization element heat map; determining a warning component and a corresponding dynamic threshold mechanism corresponding to the business visualization interface and the group visualization interface according to the business field and the concerned dimension; and generating the business visualization interface and the group visualization interface respectively according to the interface template, the warning component and the corresponding dynamic threshold mechanism.

[0014] In some embodiments, the determining the business team data access authority and the group leader data access authority according to the business team three-dimensional user portrait and the group leader three-dimensional user portrait comprises: respectively obtaining a portrait feature vector corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait; constructing a dynamic authority matrix based on the portrait feature vector; the decision level corresponds to the data longitudinal penetration depth of the dynamic authority matrix, and the business field limits the horizontal data range of the dynamic authority matrix; and determining the business team data access authority and the group leader data access authority according to the dynamic authority matrix corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait.

[0015] In some embodiments, the constructing the business cockpit and the group leader cockpit respectively according to the three-dimensional data matrix, the associated information, the business visualization interface, the group visualization interface, the business team data access authority and the group leader data access authority comprises: establishing a dynamic association relationship corresponding to the device layer, the business layer and the management layer based on the three-dimensional data matrix, the associated information, the business team data access authority and the group leader data access authority according to the graph database technology; obtaining business data corresponding to the business visualization interface and the group visualization interface in the three-dimensional data matrix according to the dynamic association relationship, so as to add the business data to the business visualization interface and the group visualization interface, and complete the construction of the business cockpit and the group leader cockpit.

[0016] In a second aspect, the application provides a business and group leader cockpit construction device, comprising:

[0017] A data acquisition unit is configured to collect real-time operation data of a plurality of power plants through an edge computing node, and establish a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix comprises a device layer, a business layer and a management layer; the data corresponding to the device layer at least includes unit efficiency, fuel consumption and environmental indicators, the data corresponding to the business layer at least includes production KPI and operating cost, and the data corresponding to the management layer at least includes strategic indicators and industry benchmark data;

[0018] An information acquisition unit is configured to acquire business team post description information and group leader post description information, parse the business team post description information and the group leader post description information according to natural language processing, and construct a business team three-dimensional user portrait and a group leader three-dimensional user portrait; the business team three-dimensional user portrait and the group leader three-dimensional user portrait each include a decision level, a business field, and a focus dimension;

[0019] An interface generation unit is configured to generate a business visualization interface and a group visualization interface according to historical operation information corresponding to the business team and the group leader, respectively; the visualization interface at least includes a data dashboard, a trend graph, and a warning component;

[0020] A permission acquisition unit is configured to determine business team data acquisition permissions and group leader data acquisition permissions according to the business team three-dimensional user portrait and the group leader three-dimensional user portrait;

[0021] A construction completion unit is configured to construct a business cockpit and a group leader cockpit according to the three-dimensional data matrix, the associated information, the business visualization interface, the group visualization interface, the business team data acquisition permissions, and the group leader data acquisition permissions.

[0022] In a third aspect, a computer device is provided, including a memory and a processor; the memory is configured to store a computer program; the processor is configured to execute the computer program and implement the method provided in any of the embodiments of the present application when executing the computer program.

[0023] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program; the computer readable instructions are executed by the processor to make one or more processors execute the method provided in any of the embodiments of the present application.

[0024] The present application discloses a business and group leader cockpit construction method, device, equipment and medium. The method first constructs a device-business-management three-dimensional data correlation model by collecting power plant device layer data (unit efficiency, fuel consumption, etc.), business layer data (production KPI, operating cost) and management layer data (strategic indicators, industry benchmark data) in real time through an edge computing node, to realize full-dimensional data fusion from bottom device operation to high-level decision-making.

[0025] Then, the natural language processing technology is used to analyze the post description, extract the three elements of decision level (such as operation layer / tactical layer / strategic layer), business field (such as production / finance / safety) and focus dimension (such as efficiency / cost / risk), and analyze user behavior patterns combined with historical operation logs, to establish a dynamic portrait updating mechanism including time dimension.

[0026] Then, based on the user portrait, the data authority is automatically matched, an interactive interface including a data dashboard (a comprehensive dashboard), a trend graph (time series analysis), and an early warning component (a threshold triggering mechanism) is generated, a component-based design is adopted to support dynamic combination of visual elements, and personalized adaptation of interface layout is realized.

[0027] Finally, a matrix permission control model is established, the data access permission is dynamically associated with the three-dimensional features (decision level x business domain x focus dimension) of the user portrait, an edge-cloud collaborative mechanism is introduced, and pre-processing and desensitization of sensitive data are completed at the edge node.

[0028] In summary, the present scheme creatively combines edge computing, three-dimensional data modeling, and dynamic user portrait, breaking through the static display limitations of traditional cockpit. By establishing a three-dimensional permission model of decision level-business domain-focus dimension, accurate adaptation of data presentation is realized; by using a dual portrait construction mechanism of NLP+behavior analysis, the problem of dynamic matching of role requirements is solved.

[0029] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0031] Figure 1 is a step schematic flow chart of the construction method of the business and group leadership cockpit provided by an embodiment of the present application;

[0032] Figure 2 is a first interface schematic diagram of the business and group leadership cockpit provided by an embodiment of the present application;

[0033] Figure 3 is a second interface schematic diagram of the business and group leadership cockpit provided by an embodiment of the present application;

[0034] Figure 4 is a structure schematic diagram of the construction device of the business and group leadership cockpit provided by an embodiment of the present application;

[0035] Figure 5 is a structure schematic block diagram of the computer device provided by an embodiment of the present application.

[0036] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0038] The flowcharts shown in the drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be further decomposed, combined or partially merged, so the actual execution order can be changed according to the actual situation.

[0039] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", etc. are used to distinguish the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. also do not necessarily mean different.

[0040] It should be understood that the terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0041] It should also be understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0042] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0043] At present, in the management of energy enterprises, how to effectively integrate multi-source heterogeneous data and build a cockpit system suitable for different roles has always been a technical difficulty in the industry. The traditional cockpit construction method is usually based on fixed templates and static index configuration, which is difficult to meet the personalized needs of different role users for data. For example, in the prior art, the construction of the cockpit often relies on manual configuration, lacks intelligent index matching and dynamic updating mechanism, resulting in single function of the cockpit and inability to effectively support cross-level and cross-business decision-making needs.

[0044] Therefore, there is an urgent need for a method to solve at least one of the above problems.

[0045] To solve the above problems, please refer to Figure 1 , Figure 1 is a schematic flowchart of a method for constructing a business and group leadership cockpit provided by an embodiment of the present application. The execution device of the method is the device, which includes a computer device.

[0046] To solve the above problems, please refer to Figure 1 . Specifically, as shown in Figure 1 , the provided method includes steps S101 to S105. The computer device can be a handheld terminal, a notebook computer, a wearable device, or a robot, etc. The steps S101 to S105 and the corresponding embodiments for implementing them are used.

[0047] The steps are described in detail as follows:

[0048] Step S101. Collect real-time operation data of multiple power plants through edge computing nodes, and establish a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix includes a device layer, a business layer, and a management layer; the data corresponding to the device layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPI and operating cost, and the data corresponding to the management layer at least includes strategic indicators and industry benchmark data.

[0049] Specifically, real-time operation data from multiple power plants is collected by using edge computing nodes. Based on the collected data, a three-dimensional data matrix is constructed, which covers three dimensions of device layer, business layer, and management layer.

[0050] As the device layer data collection includes key performance indicators such as unit efficiency, fuel consumption, and environmental indicators. The business layer data collection includes business-related data such as production KPI (key performance indicator) and operating cost. The management layer data collection includes data at the management level such as strategic indicators and industry benchmark data. Through edge computing technology, real-time data collection and preliminary processing are realized, data transmission delay is reduced, and data processing efficiency is improved. The real-time and accuracy of data are realized, providing a reliable data foundation for subsequent data analysis and decision-making. Through the three-dimensional data matrix, the running state of the power plant can be comprehensively reflected, providing support for decision-making at different levels.

[0051] The edge computing deployment is to deploy KubeEdge edge nodes at the power plant side, and collect DCS system data (such as unit vibration frequency, boiler temperature) in real time through OPC UA protocol. Modbus-TCP protocol is used to obtain smart meter data (fuel flow per hour, power generation). Data cleaning (3σ rule to remove outliers) and normalization processing (convert different unit indicators to 0-1 standardized values) are completed at the edge side.

[0052] Step S102. Obtain business team job description information and group leader job description information, parse the business team job description information and the group leader job description information according to natural language processing, and construct a business team three-dimensional user portrait and a group leader three-dimensional user portrait; the business team three-dimensional user portrait and the group leader three-dimensional user portrait both include decision level, business field and attention dimension.

[0053] Specifically, the job description information of the business team and the group leader is parsed by natural language processing technology. The three-dimensional user portraits of the business team and the group leader are constructed, including decision level, business field and attention dimension. The natural language processing technology is used to perform semantic analysis on the job description information and extract key information. According to the extracted information, the user portrait is constructed to clearly define the data needs and decision preferences of different users. The accuracy of the user portrait is improved, so that the cockpit system can better meet the individual needs. Through the user portrait, the individual display and push of data are realized, and the user experience is improved. The decision level is, for example, factory level / group level, the business field is, for example, production / finance / safety, and the attention dimension is, for example, cost control / equipment health. When calculating the weight of the portrait, the decision level weight = TF-IDF("strategic planning")*0.6. The business field correlation = Word2Vec similarity("safety production", job description). The group leader three-dimensional user portrait can be as shown in the following table:

[0054]

[0055] Step S103. Generate a business visualization interface and a group visualization interface according to the historical operation information corresponding to the business team and the group leader, respectively; the visualization interface at least includes a data dashboard, a trend graph and a warning component.

[0056] Specifically, according to the historical operation information of the user, the business visualization interface and the group visualization interface are generated. The interface includes data dashboard, trend graph and warning component, etc. For example, analyze the user's historical operation data to understand the user's usage habits and preferences. According to the analysis results, the visualization interface that meets the user's needs is designed and generated. The interface design focuses on interactivity and intuitiveness, making it easy for users to quickly access key information. The friendliness and ease of use of the user interface are improved, so that users can more intuitively understand the data. Through the warning component, potential problems are discovered and warned in time, improving the timeliness of decision-making.

[0057] The warning rules corresponding to the warning component can be, for example: if the unit vibration > 7.5mm / s and the duration > 30min, trigger an orange warning and push it to the group leader cockpit.

[0058] Step S104. Determine the business team data access authority and the group leader data access authority according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leader.

[0059] Specifically, the data access authority of the business team and the group leader is determined according to the user portrait. In combination with the decision level, business field and attention dimension in the user portrait, the corresponding data access authority is set. The dynamic management of the authority is realized, and the authority setting is adjusted in time according to the change of the user role. The safety and compliance of the data are ensured, and the data leakage is prevented. The fine management of the data is realized, and the data utilization efficiency is improved.

[0060] Specifically, the content corresponding to the access authority can be as follows:

[0061]

[0062]

[0063] Step S105. Build the business cockpit and the group leader cockpit according to the three-dimensional data matrix, the associated information, the business visualization interface, the group visualization interface, the business team data access authority and the group leader data access authority.

[0064] Specifically, as shown in Figure 2 and Figure 3 , the business cockpit and the group leader cockpit are built according to the three-dimensional data matrix, the associated information, the business visualization interface, the group visualization interface, the business team data access authority and the group leader data access authority. The results of steps S101 to S104 are integrated to build a complete cockpit system. The cockpit system can dynamically adjust the data and interface displayed according to the user role and the authority. The data integration and display across levels and across businesses are realized, and the complex decision-making requirements are supported.

[0065] In some embodiments, the three-dimensional data matrix is established according to real-time operation data, including: performing data cleaning and standardization processing on the real-time operation data to generate a device layer basic data pool; based on a preset association rule library, dynamically mapping the device layer data with a business index logical chain to build a business layer derived index set; through an industry benchmarking algorithm, dynamically weighting the management layer data to generate a management layer index topology network containing a strategic weight coefficient; using a space-time association modeling technology, establishing a bidirectional data traceability channel between the device layer, the business layer and the management layer to form a three-dimensional data matrix architecture with a dynamic feedback mechanism.

[0066] Real-time operation data of multiple power plants are collected by edge computing nodes, including equipment status, performance parameters, environmental monitoring data, etc. The collected raw data is cleaned to remove noise data, missing data and abnormal data, ensuring the accuracy and integrity of the data. The cleaned data is standardized according to a unified format and standard, ensuring that data from different sources have consistent formats and units, facilitating subsequent analysis and processing. The cleaned and standardized device layer data is stored in the basic data pool as the basis for subsequent analysis.

[0067] Based on industry standards and business needs, a set of association rule library is preset to define the logical relationship between device layer data and business indicators. Using the association rule library, the data in the device layer basic data pool is dynamically mapped with the business indicator logical chain to generate a set of business layer derived indicators. These derived indicators reflect key performance indicators (KPIs) at the business level, such as production efficiency, cost effectiveness, etc. The generated set of business layer derived indicators is integrated to form business layer data, providing support for subsequent management layer analysis.

[0068] An industry benchmarking algorithm is used to dynamically weight the management layer data. This algorithm compares the best practices within the industry and the performance of competitors to assign strategic weight coefficients to the management layer data. Based on the dynamically weighted management layer data, a management layer indicator topology network is generated that includes strategic weight coefficients. This network reflects the indicators and their importance that the management layer focuses on in strategic decision-making. The generated management layer indicator topology network is integrated to form management layer data, providing support for the construction of the three-dimensional data matrix.

[0069] A space-time correlation modeling technique is used to establish a two-way data traceability channel between the device layer, business layer and management layer. This technique analyzes the correlation between data in time and space to ensure traceability and consistency between data at different levels. Through the two-way data traceability channel, a dynamic feedback mechanism is achieved between the device layer, business layer and management layer. When data at one level changes, the system can automatically adjust the data at other levels to ensure data consistency and real-time performance. Combining the device layer basic data pool, business layer derived indicator set and management layer indicator topology network, as well as the two-way data traceability channel and dynamic feedback mechanism, a three-dimensional data matrix architecture with dynamic feedback mechanism is formed.

[0070] Through data cleaning and standardization processing, the accuracy and consistency of the device layer data are ensured, providing a reliable foundation for subsequent analysis. The two-way data traceability channel and dynamic feedback mechanism ensure the consistency and real-time nature of the device layer, business layer, and management layer data, avoiding data silos and inconsistencies. Through dynamic mapping and business layer derived indicator set, the system can extract key performance indicators at the business level from device layer data, providing deeper insights for business decision-making. The generation of business layer data enables the management layer to better understand business operation conditions, optimize business processes, and improve business efficiency.

[0071] During data cleaning and standardization processing, first, an improved DBSCAN clustering algorithm is used to dynamically detect outliers in real-time data streams, and a unified data coordinate system is established for data alignment, as shown in the following table:

[0072] Original data type Standardization method Storage format Unit set Z-score standardization float32 Coal heating value (kcal / kg) Min-Max normalization uint16 Flue gas SO2 concentration (mg / m 3 )]]> Log transformation float32

[0073] In some embodiments, the business team three-dimensional user portrait and the group leader three-dimensional user portrait are constructed according to natural language processing analysis of the business team job description information and the group leader job description information, including: performing entity relationship extraction on the business team job description information and the group leader job description information according to the domain knowledge graph, to identify the core decision-making elements corresponding to the business team job description information and the group leader job description information; using an attention mechanism driven semantic analysis model to obtain the decision preference intensity coefficients corresponding to the business team job description information and the group leader job description information, respectively; performing feature extraction on the business team job description information and the group leader job description information to obtain the job level features corresponding to the business team job description information and the group leader job description information, respectively; obtaining the historical behavior features corresponding to the historical operation information; and constructing the business team three-dimensional user portrait and the group leader three-dimensional user portrait according to the core decision-making elements, the decision preference intensity coefficients, the job level features, and the historical behavior features.

[0074] Feature vectors are extracted from the business team three-dimensional user portrait and the group leader three-dimensional user portrait, which represent the user's key attributes and preferences. A dynamic permission matrix is constructed using the portrait feature vectors, which defines the access permissions of different users to different data. The decision level determines the vertical penetration depth of the data, i.e., the depth of data that users can access. The business domain limits the horizontal data range of the dynamic permission matrix, i.e., the breadth of data that users can access. According to the dynamic permission matrix and the user portrait feature vectors, the data access permissions of the business team and the group leaders are determined. Through the dynamic permission matrix, more refined data permission management is achieved, improving data security. While ensuring that data access complies with organizational compliance requirements, permissions are adjusted flexibly according to changes in user roles. Users can quickly access the data they need, improving work efficiency and data utilization efficiency.

[0075] The method also includes, based on a dynamic attenuation algorithm, establishing a user portrait updating mechanism to automatically adjust the portrait dimension weights corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait according to the user operation logs corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait.

[0076] Based on the dynamic attenuation algorithm, a user portrait updating mechanism is established. According to the user operation logs, the portrait dimension weights of the business team three-dimensional user portrait and the group leader three-dimensional user portrait are automatically adjusted. The operation logs of the user are collected and analyzed to identify the operation habits and preference changes of the user. According to the behavior characteristics in the operation logs, the weights of each dimension in the user portrait are dynamically adjusted. According to the dynamic attenuation algorithm, the weights of the decision level, business field and focus dimension in the user portrait are dynamically adjusted. It ensures that the user portrait can timely reflect the latest needs and preferences of the user. An automatic user portrait updating mechanism is established to update the user portrait regularly according to the latest user operation logs. Manual intervention is reduced to improve the real-time and accuracy of the user portrait. Through the dynamic attenuation algorithm and the automatic updating mechanism, the user portrait can reflect the latest needs and preferences of the user in real time. The portrait dimension weights are dynamically adjusted to make the system better adapt to the changes of the user and improve the flexibility and adaptability of the system. The automatic updating mechanism reduces manual intervention and improves the efficiency and accuracy of user portrait management.

[0077] In some embodiments, the business visualization interface and the group visualization interface are generated according to the historical operation information corresponding to the business team and the group leader, including: analyzing the historical operation information to obtain component interaction frequency and path jump characteristics for constructing a visualization element heat map; determining the interface template corresponding to the business visualization interface and the group visualization interface according to the visualization element heat map; determining the warning components and the corresponding dynamic threshold mechanism corresponding to the business visualization interface and the group visualization interface according to the business field and the focus dimension; and generating the business visualization interface and the group visualization interface according to the interface template, the warning components and the corresponding dynamic threshold mechanism.

[0078] Collect the historical operation logs of business teams and group leaders. Analyze the logs using data analysis techniques to extract component interaction frequencies and path jump characteristics. Based on the component interaction frequencies and path jump characteristics, construct a heat map of visual elements to identify the most frequently accessed and focused interface elements by users. According to the heat map of visual elements, select or design interface templates suitable for business teams and group leaders to improve the usability and user satisfaction of the interface. According to the business domain and focus dimensions, determine the warning components that need to be included in the business visualization interface and the group visualization interface. Design a dynamic threshold mechanism for the warning components to automatically adjust the warning trigger conditions based on real-time data. Combine the interface template, warning components, and dynamic threshold mechanism to generate the final business visualization interface and group visualization interface.

[0079] By analyzing user behavior, generate interfaces that better fit user habits and improve user experience. The dynamic threshold mechanism allows the warning system to dynamically adjust based on actual business data, improving the accuracy and timeliness of warnings. Through the heat map and warning components, users can quickly identify key issues and trends, thereby optimizing the decision-making process.

[0080] In some embodiments, determining the business team data access permissions and group leader data access permissions based on the business team three-dimensional user portrait and the group leader three-dimensional user portrait includes: respectively obtaining the portrait feature vectors corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait; constructing a dynamic permission matrix based on the portrait feature vectors; determining the data longitudinal penetration depth of the dynamic permission matrix corresponding to the decision level, and limiting the horizontal data range of the dynamic permission matrix corresponding to the business domain; and determining the business team data access permissions and the group leader data access permissions based on the dynamic permission matrix corresponding to the business team three-dimensional user portrait and the group leader three-dimensional user portrait.

[0081] From the business team three-dimensional user portrait and the group leader three-dimensional user portrait, extract feature vectors that represent the key attributes and preferences of users.

[0082] Use the portrait feature vectors to construct a dynamic permission matrix that defines the access permissions of different users to different data. The decision level determines the data longitudinal penetration depth, i.e., the depth of data that users can access. The business domain limits the horizontal data range of the dynamic permission matrix, i.e., the breadth of data that users can access. Based on the dynamic permission matrix and the user portrait feature vectors, determine the data access permissions of the business team and the group leader.

[0083] Through the dynamic permission matrix, achieve more refined data permission management and improve data security. Ensure that data access complies with organizational compliance requirements while flexibly adjusting permissions according to changes in user roles. Users can quickly access the data they need, improving work efficiency and data utilization efficiency.

[0084] In some embodiments, the business cockpit group leader cockpit is constructed according to the three-dimensional data matrix, the association information, the business visualization interface, the group visualization interface, the business team data access permission and the group leader data access permission, including: based on the graph database technology, the dynamic association relationship between the equipment layer, the business layer and the management layer is established according to the three-dimensional data matrix, the association information, the business team data access permission and the group leader data access permission; according to the dynamic association relationship, the business data corresponding to the business visualization interface and the group visualization interface is obtained in the three-dimensional data matrix, which is used to add the business data to the business visualization interface and the group visualization interface, and the construction of the business cockpit group leader cockpit is completed.

[0085] Using the graph database technology, the dynamic association relationship between the equipment layer, the business layer and the management layer is established according to the three-dimensional data matrix, the association information, the business team data access permission and the group leader data access permission. According to the dynamic association relationship, the business data required by the business visualization interface and the group visualization interface is obtained in the three-dimensional data matrix. The obtained business data is added to the business visualization interface and the group visualization interface, and the construction of the business cockpit and the group leader cockpit is completed. Through the graph database technology, multiple data sources are integrated, deep analysis and data mining are realized, and more comprehensive data support is provided. The business cockpit and the group leader cockpit provide a centralized platform, so that decision makers can quickly obtain key information and improve decision efficiency. Through real-time updated business data and dynamic association relationship, the data-driven decision-making ability is enhanced, helping the management layer to make more accurate business decisions.

[0086] In some embodiments, a data cleaning model can be trained using machine learning algorithms to automatically identify and process noisy data, missing data and abnormal data. The model can dynamically adjust the cleaning rules according to the characteristics of historical data, improving the accuracy and efficiency of data cleaning. A smart standardization engine can be developed to automatically identify the format and unit of different data sources and convert them into a unified format and standard. The engine uses natural language processing technology to analyze the semantics of data fields, ensuring the accuracy and consistency of standardization processing.

[0087] AI-driven data cleaning and standardization processing significantly improve the accuracy and consistency of data, providing a more reliable foundation for subsequent analysis. Automation reduces human intervention, improves data processing efficiency and shortens data processing cycle.

[0088] In some embodiments, a business layer derivative index generation model is constructed using graph neural network (GNN) technology. The model represents device layer data and business index logical chains as a graph structure and performs dynamic mapping and index generation through a graph neural network. The model can respond to changes in device layer data in real time, dynamically update business layer derivative indexes, and ensure the real-time and accuracy of indexes. By introducing an attention mechanism, the model can automatically identify key business indexes, improving the relevance and effectiveness of index generation.

[0089] The business layer derivative indexes generated by the graph neural network can more accurately reflect business operation conditions and provide deeper insights for business decisions. The dynamic index update mechanism ensures the real-time and dynamic nature of business layer data, improving the timeliness and accuracy of business decisions.

[0090] In some embodiments, a strategy weight coefficient optimization model is trained using reinforcement learning algorithms. The model dynamically adjusts the strategic weight coefficients of management layer data by simulating industry benchmarks and strategic decision-making processes. The model can dynamically optimize strategic weight coefficients based on real-time industry data and strategic objectives, ensuring the scientificity and effectiveness of the management layer index topology network. By introducing a reward mechanism, the model can automatically identify key strategic indexes, improving the relevance and effectiveness of weight coefficient optimization. The reinforcement learning optimized strategic weight coefficients provide a more scientific basis for strategic decision-making, improving the accuracy and effectiveness of decisions. The dynamic optimization mechanism enables the strategic weight coefficients to respond to industry changes and strategic objectives in real time, improving the adaptability and flexibility of the system.

[0091] In some embodiments, a two-way data traceability channel is constructed using blockchain technology to ensure traceability and consistency between device layer, business layer, and management layer data. The distributed ledger technology of blockchain ensures data transparency and immutability, improving data credibility and security. Smart contracts are developed to implement a dynamic feedback mechanism between the device layer, business layer, and management layer. When data in one level changes, the smart contract can automatically trigger data adjustments in other levels, ensuring data consistency and real-time performance.

[0092] Blockchain technology ensures data transparency and immutability, improving data credibility and security. Smart contracts enable automated data adjustment and real-time feedback, improving the real-time and dynamic nature of the system.

[0093] In some embodiments, a visual business cockpit and group leadership cockpit are constructed using augmented reality (AR) and virtual reality (VR) technologies. Users can intuitively view and analyze three-dimensional data matrices, business layer derived indicators, and management layer indicator topology networks through AR / VR devices. Interactive data exploration functions are developed, allowing users to interact with data in the cockpit through gestures and voice commands to obtain more in-depth analysis and insights. By introducing machine learning algorithms, the system can automatically adjust the interface and functions of the cockpit according to the user's operation habits and preferences, improving user experience. AR / VR technology makes data display more intuitive and vivid, improving user understanding and analysis efficiency. Interactive data exploration and personalized adjustment functions improve user operation experience and satisfaction, enhancing the intelligence and adaptability of the system.

[0094] Please refer to Figure 4 as shown, Figure 4 is a structural schematic diagram of a business and group leadership cockpit construction device 200 provided by the embodiments of the present application. The business and group leadership cockpit construction device 200 is used to execute the steps of the business and group leadership cockpit construction method shown in each of the above embodiments. The business and group leadership cockpit construction device 200 can be a single server or a server cluster, or the business and group leadership cockpit construction device 200 can be a terminal, which can be a handheld terminal, a notebook computer, a wearable device, or a robot, etc.

[0095] As Figure 4 shown, the business and group leadership cockpit construction device 200 includes:

[0096] A data acquisition unit 201 is configured to collect real-time operation data of a plurality of power plants through an edge computing node, and establish a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix includes a device layer, a business layer, and a management layer; the data corresponding to the device layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPI and operating cost, and the data corresponding to the management layer at least includes strategic indicators and industry benchmark data;

[0097] An information acquisition unit 202 is configured to acquire business team job description information and group leadership job description information, parse the business team job description information and the group leadership job description information according to natural language processing, and construct a business team three-dimensional user portrait and a group leadership three-dimensional user portrait; the business team three-dimensional user portrait and the group leadership three-dimensional user portrait both include a decision level, a business field, and a focus dimension;

[0098] The interface generation unit 203 is configured to generate a business visualization interface and a group visualization interface according to historical operation information corresponding to the business team and the group leader, respectively; the visualization interface at least includes a data dashboard, a trend graph, and a warning component.

[0099] The permission acquisition unit 204 is configured to determine business team data acquisition permission and group leader data acquisition permission according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leader.

[0100] The construction completion unit 205 is configured to construct a business cockpit and a group leader cockpit according to the three-dimensional data matrix, the association information, the business visualization interface, the group visualization interface, the business team data acquisition permission, and the group leader data acquisition permission, respectively.

[0101] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the construction device and each unit of the business and group leader cockpit described above can refer to the corresponding process in the construction embodiment of the business and group leader cockpit described in each of the above embodiments, which will not be repeated here.

[0102] The construction of the business and group leader cockpit described above can be realized in the form of a computer program, which can run on the device as shown. Figure 4 The computer program includes program instructions that, when executed, cause the processor to perform any kind of construction of the business and group leader cockpit.

[0103] Please refer to Figure 5 , Figure 5 is a structural schematic block diagram of a computer device provided by the embodiment of the present application. The computer device includes a processor, a memory, and a network interface connected through a device bus, wherein the memory can include a storage medium and an internal memory.

[0104] The storage medium can store an operating device and a computer program. The computer program includes program instructions that, when executed, cause the processor to perform any kind of construction of the business and group leader cockpit.

[0105] The processor is configured to provide computing and control capabilities to support the operation of the entire computer device.

[0106] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium, which, when executed by the processor, causes the processor to perform any kind of construction of the business and group leader cockpit.

[0107] The network interface is configured to perform network communication, such as sending assigned tasks. Those skilled in the art can understand that Figure 5The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. A specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0108] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0109] In one embodiment, the processor is configured to run a computer program stored in the memory to perform the following steps:

[0110] The edge computing node collects real-time operation data of a plurality of power plants, and establishes a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix includes a device layer, a business layer and a management layer; the data corresponding to the device layer at least includes unit efficiency, fuel consumption and environmental indicators, the data corresponding to the business layer at least includes production KPI and operating cost, and the data corresponding to the management layer at least includes strategic indicators and industry benchmark data;

[0111] The business team post description information and the group leader post description information are obtained, the business team post description information and the group leader post description information are parsed according to natural language processing, and a business team three-dimensional user portrait and a group leader three-dimensional user portrait are constructed; the business team three-dimensional user portrait and the group leader three-dimensional user portrait each include a decision level, a business field and a focus dimension;

[0112] A business visualization interface and a group visualization interface are respectively generated according to historical operation information corresponding to the business team and the group leader; the visualization interface at least includes a data dashboard, a trend graph and a warning component;

[0113] The business team data access permission and the group leader data access permission are determined according to the business team three-dimensional user portrait and the group leader three-dimensional user portrait;

[0114] According to the three-dimensional data matrix, the association information, the business visualization interface, the group visualization interface, the business team data acquisition permission and the group leader data acquisition permission, a business cockpit and a group leader cockpit are constructed.

[0115] It should be noted that, for the convenience and brevity of description, the specific working process of the processor described above can refer to the corresponding process in the construction of the business and group leader cockpits described in the above embodiments, which will not be described here.

[0116] In the embodiments of the present application, a computer readable storage medium is also provided, which stores a computer program. The computer program includes program instructions. The processor executes the program instructions to implement the steps of the construction method of the business and group leader cockpits provided in the above embodiments of the present application.

[0117] The computer readable storage medium can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0118] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed in the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for constructing a business and group leadership cockpit, characterized in that, include: Real-time operating data from multiple power plants is collected via edge computing nodes, and a three-dimensional data matrix is ​​established based on the real-time operating data. The three-dimensional data matrix includes an equipment layer, a business layer, and a management layer. The data corresponding to the equipment layer includes at least unit efficiency, fuel consumption, and environmental indicators; the data corresponding to the business layer includes at least production KPIs and operating costs; and the data corresponding to the management layer includes at least strategic indicators and industry benchmarking data. Establishing the three-dimensional data matrix based on the real-time operating data includes: performing data cleaning and standardization on the real-time operating data to generate a basic data pool for the equipment layer. Based on a pre-defined association rule base, the device layer data is dynamically mapped to the business indicator logic chain to construct a business layer derived indicator set; the management layer data is dynamically weighted through an industry benchmarking algorithm to generate a management layer indicator topology network containing strategic weight coefficients; and a spatiotemporal association modeling technology is used to establish a two-way data traceability channel between the device layer, business layer, and management layer to form a three-dimensional data matrix architecture with a dynamic feedback mechanism. The system acquires job descriptions for business teams and group leaders, parses these descriptions using natural language processing, and constructs three-dimensional user profiles for both business teams and group leaders. Both profiles include decision-making level, business domain, and focus dimension. Based on the historical operation information of the business teams and group leaders, a business visualization interface and a group visualization interface are generated respectively; the visualization interface includes at least a data dashboard, a trend chart, and an early warning component. The data access permissions of the business team and the group leaders are determined based on the aforementioned 3D user profiles of the business team and the group leaders. Based on the aforementioned three-dimensional data matrix, related information, business visualization interface, group visualization interface, business team data access permissions, and group leader data access permissions, a business dashboard and a group leader dashboard are constructed respectively.

2. The method according to claim 1, characterized in that, The process of constructing three-dimensional user profiles for business teams and group leaders based on natural language processing analysis of job descriptions for business team members and group leaders includes: Based on the domain knowledge graph, entity relationships are extracted from the job descriptions of business teams and group leaders respectively, and the core decision-making elements corresponding to the job descriptions of business teams and group leaders are identified. An attention-driven semantic analysis model is used to obtain the corresponding decision preference intensity coefficients from the job description information of business teams and the job description information of group leaders, respectively. Feature extraction is performed on the job description information of the business teams and the job description information of the group leaders to obtain the job level features corresponding to the job description information of the business teams and the job description information of the group leaders respectively; Obtain the historical behavior features corresponding to the historical operation information; Based on the core decision-making elements, decision preference intensity coefficient, job level characteristics, and historical behavioral characteristics, construct a three-dimensional user profile of the business team and a three-dimensional user profile of the group leaders.

3. The method according to claim 2, characterized in that, The method further includes: A user profile update mechanism is established based on a dynamic decay algorithm to automatically adjust the profile dimension weights corresponding to the business team's 3D user profile and the group leader's 3D user profile based on the user operation logs.

4. The method according to claim 1, characterized in that, The process of generating business visualization interfaces and group visualization interfaces based on historical operation information corresponding to business teams and group leaders includes: The historical operation information is analyzed to obtain the component interaction frequency and path jump characteristics, which are used to construct a visual element heat map. The interface templates corresponding to the business visualization interface and the group visualization interface are determined based on the heat map of the visualization elements. Based on the business areas and focus dimensions, determine the early warning components and corresponding dynamic threshold mechanisms for the business visualization interface and the group visualization interface; Based on the interface template, early warning component, and corresponding dynamic threshold mechanism, a business visualization interface and a group visualization interface are generated respectively.

5. The method according to claim 1, characterized in that, The step of determining the data access permissions of the business team and the group leaders based on the three-dimensional user profiles of the business team and the group leaders includes: Obtain the feature vectors corresponding to the 3D user profiles of the business team and the 3D user profiles of the group leaders, respectively. Construct a dynamic permission matrix based on profile feature vectors; the decision level corresponds to the vertical data penetration depth of the dynamic permission matrix, and the business domain limits the horizontal data range of the dynamic permission matrix; The data access permissions of the business team and the data access permissions of the group leaders are determined based on the dynamic permission matrix corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders.

6. The method according to claim 1, characterized in that, The business dashboard and group leadership dashboard are constructed based on the three-dimensional data matrix, related information, business visualization interface, group visualization interface, business team data access permissions, and group leadership data access permissions, respectively, including: Based on graph database technology, dynamic relationships are established between the device layer, business layer, and management layer according to the three-dimensional data matrix, related information, data access permissions of business teams, and data access permissions of group leaders. Based on the dynamic relationship, the business data corresponding to the business visualization interface and the group visualization interface are obtained from the three-dimensional data matrix. The business data is then added to the business visualization interface and the group visualization interface to complete the construction of the business cockpit and the group leadership cockpit.

7. A device for constructing a business and group leadership cockpit, characterized in that, The device includes: A data acquisition unit is used to collect real-time operating data from multiple power plants through edge computing nodes and establish a three-dimensional data matrix based on the real-time operating data. The three-dimensional data matrix includes an equipment layer, a business layer, and a management layer. The data corresponding to the equipment layer includes at least unit efficiency, fuel consumption, and environmental indicators; the data corresponding to the business layer includes at least production KPIs and operating costs; and the data corresponding to the management layer includes at least strategic indicators and industry benchmarking data. Establishing the three-dimensional data matrix based on the real-time operating data includes: performing data cleaning and standardization on the real-time operating data to generate a basic data pool for the equipment layer; dynamically mapping the equipment layer data to the logical chain of business indicators based on a preset association rule base to construct a set of business layer derived indicators; dynamically weighting the management layer data using an industry benchmarking algorithm to generate a management layer indicator topology network containing strategic weight coefficients; and using spatiotemporal correlation modeling technology to establish a bidirectional data traceability channel between the equipment layer, business layer, and management layer to form a three-dimensional data matrix architecture with a dynamic feedback mechanism. The information acquisition unit is used to acquire job description information for business teams and job description information for group leaders, and to parse the job description information for business teams and job description information for group leaders using natural language processing to construct three-dimensional user profiles for business teams and group leaders. The three-dimensional user profiles for business teams and group leaders both include decision-making level, business domain, and focus dimension. The interface generation unit is used to generate business visualization interfaces and group visualization interfaces respectively based on the historical operation information of the business teams and group leaders; the visualization interfaces include at least data dashboards, trend charts and early warning components. The permission acquisition unit is used to determine the data acquisition permissions of the business team and the data acquisition permissions of the group leaders based on the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders. The completed unit is used to construct the business dashboard and the group leader dashboard based on the three-dimensional data matrix, related information, business visualization interface, group visualization interface, business team data access permissions, and group leader data access permissions, respectively.

8. A computer device, characterized in that, It includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and, when executing the computer program, implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause one or more processors to perform the steps of the method as described in any one of claims 1 to 6.

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