Construction method and device of business and group leader cockpit, equipment and medium

Abstract

The invention discloses a business and group leader cockpit construction method and device, equipment and a medium. The method comprises the following steps: acquiring real-time operation data of a plurality of power plants through edge computing nodes, and establishing a three-dimensional data matrix according to the real-time operation data; business team post description information and group leader post description information are obtained, the business team post description information and the group leader post description information are processed and analyzed according to a natural language, and a business team three-dimensional user portrait and a group leader three-dimensional user portrait are constructed; respectively generating a business visual interface and a group visual interface according to the historical operation information corresponding to the business team and the group leader; determining a business team data acquisition permission and a group leader data acquisition permission according to the business team three-dimensional user portrait and the group leader three-dimensional user portrait; and completing the construction of the leader cockpit of the business cockpit group. The problem of role demand dynamic matching of a traditional energy enterprise cockpit is solved, and cross-level and business data integration and display are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and particularly to a method, device, equipment and medium for constructing a business and group leadership cockpit. Background Art

[0002] Currently, 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. Traditional cockpit construction methods usually rely on fixed templates and static indicator configurations, and it is difficult to meet the personalized data needs of users with different roles. For example, in the prior art, the construction of a cockpit often relies on manual configuration, lacking intelligent indicator matching and dynamic update mechanisms, resulting in a single function of the cockpit and being unable to effectively support cross-level and cross-business decision-making needs. Summary of the Invention

[0003] The present application provides a method, device, equipment and medium for constructing a business and group leadership cockpit, aiming to solve the problem that traditional cockpit construction methods usually rely on fixed templates and static indicator configurations and it is difficult to meet the personalized data needs of users with different roles.

[0004] In a first aspect, the present application provides a method for constructing a business and group leadership cockpit, the method comprising:

[0005] Collecting real-time operation data of multiple power plants through edge computing nodes, and establishing a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix includes an equipment layer, a business layer, and a management layer; the data corresponding to the equipment layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data;

[0006] Obtaining business team position description information and group leadership position description information, and constructing a three-dimensional user portrait of the business team and a three-dimensional user portrait of the group leadership according to natural language processing to parse the business team position description information and the group leadership position description information; both the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leadership include a decision-making level, a business area, and a dimension of concern;

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

[0008] Determining the data acquisition permissions of the business team and the data acquisition permissions of the group leadership according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leadership;

[0009] Construct a business cockpit and a group leader cockpit respectively based on the three-dimensional data matrix, association information, business visualization interface, group visualization interface, data acquisition permissions of business teams, and data acquisition permissions of group leaders.

[0010] In some embodiments, constructing the three-dimensional data matrix according to the real-time operation data includes: performing data cleaning and standardization processing on the real-time operation data to generate a basic data pool at the device layer; dynamically mapping the device layer data to the business indicator logic chain based on a preset association rule library to construct a set of derived indicators at the business layer; dynamically weighting the management layer data through an industry benchmarking algorithm to generate a management layer indicator topology network including strategic weight coefficients; adopting a spatio-temporal association modeling technique to establish a two-way data traceability channel among the device layer, business layer, and management layer to form a three-dimensional data matrix architecture with a dynamic feedback mechanism.

[0011] In some embodiments, constructing the three-dimensional user portraits of business teams and group leaders according to the business team position description information and group leader position description information parsed by natural language processing includes: respectively extracting entity relationships from the business team position description information and group leader position description information according to the domain knowledge graph to identify the core decision-making elements corresponding to the business team position description information and group leader position description information; adopting a semantic analysis model driven by an attention mechanism to respectively obtain the decision preference intensity coefficients corresponding to the business team position description information and group leader position description information; performing feature extraction on the business team position description information and group leader position description information to respectively obtain the position level features corresponding to the business team position description information and group leader position description information; obtaining the historical behavior features corresponding to the historical operation information; constructing the three-dimensional user portraits of business teams and group leaders according to the core decision-making elements, decision preference intensity coefficients, position level features, and historical behavior features.

[0012] Exemplarily, the method further includes: establishing a user portrait update mechanism based on a dynamic decay algorithm to automatically adjust the portrait dimension weights corresponding to the three-dimensional user portraits of business teams and group leaders according to the user operation logs corresponding to the three-dimensional user portraits of business teams and group leaders.

[0013] In some embodiments, 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 includes: parsing the historical operation information to obtain the component interaction frequency and the path jump feature for constructing a heat map of visualization element popularity; determining the interface templates corresponding to the business visualization interface and the group visualization interface according to the heat map of visualization element popularity; determining the warning components and the corresponding dynamic threshold mechanisms corresponding to the business visualization interface and the group visualization interface according to the business domain and the attention dimension; and generating the business visualization interface and the group visualization interface respectively according to the interface templates, the warning components and the corresponding dynamic threshold mechanisms.

[0014] In some embodiments, determining the data acquisition permissions of the business team and the group leader according to the three-dimensional user portraits of the business team and the group leader includes: respectively obtaining the portrait feature vectors corresponding to the three-dimensional user portraits of the business team and the group leader; constructing a dynamic permission matrix based on the portrait feature vectors; the decision-making level corresponding to the vertical penetration depth of the data of the dynamic permission matrix, and the business domain defining the horizontal data range of the dynamic permission matrix; and determining the data acquisition permissions of the business team and the group leader according to the dynamic permission matrix corresponding to the three-dimensional user portraits of the business team and the group leader.

[0015] In some embodiments, constructing 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 data acquisition permissions of the business team and the group leader respectively includes: establishing dynamic association relationships corresponding to the device layer, the business layer and the management layer based on the graph database technology according to the three-dimensional data matrix, the association information, the data acquisition permissions of the business team and the group leader; and obtaining the business data corresponding to the business visualization interface and the group visualization interface from the three-dimensional data matrix according to the dynamic association relationships for adding the business data to the business visualization interface and the group visualization interface to complete the construction of the business cockpit and the group leader cockpit.

[0016] In a second aspect, the present application provides a device for constructing a business and group leader cockpit, including:

[0017] A data acquisition unit, configured to collect real-time operation data of multiple 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 KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data;

[0018] An information acquisition unit, configured to acquire job description information of the business team and job description information of the group leaders, parse the job description information of the business team and the job description information of the group leaders according to natural language processing, and construct a three-dimensional user portrait of the business team and a three-dimensional user portrait of the group leaders; both the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders include a decision-making level, a business area, and a dimension of concern.

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

[0020] A permission acquisition unit, configured to determine the data acquisition permissions of the business team and the data acquisition permissions of the group leaders according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders.

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

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

[0023] In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer-readable instruction is executed by the processor, one or more processors are caused to execute the method provided in any embodiment of the present application.

[0024] The present application discloses a method, device, equipment, and medium for constructing a business and group leader cockpit. The method first constructs an equipment-business-management three-dimensional data association model by real-time collecting power plant equipment layer data (such as unit efficiency, fuel consumption, etc.), business layer data (such as production KPIs, operating costs), and management layer data (such as strategic indicators, industry benchmarking data) through edge computing nodes, so as to realize the full-dimensional data fusion from the bottom-layer equipment operation to the high-level decision-making.

[0025] Then, natural language processing technology is used to parse the job description, extract three elements of the decision-making level (such as the operation layer / tactical layer / strategic layer), the business area (such as production / finance / security), and the dimension of concern (such as efficiency / cost / risk), and analyze the user behavior pattern in combination with the historical operation log to establish a dynamic portrait update mechanism including the time dimension.

[0026] Then, based on the user profile, data permissions are automatically matched to generate an interactive interface that includes a data dashboard (comprehensive dashboard), a trend graph (time series analysis), and an early warning component (threshold trigger mechanism). Component-based design is adopted to support the dynamic combination of visualization elements, achieving personalized adaptation of the interface layout.

[0027] Finally, a matrix-style permission control model is established to dynamically associate data access permissions with the three-dimensional features of the user profile (decision-making level × business domain × dimension of concern). An edge-cloud collaboration mechanism is introduced to ensure that sensitive data is preprocessed and desensitized at the edge node.

[0028] In summary, this solution creatively combines edge computing, three-dimensional data modeling, and dynamic user profiles, breaking through the static display limitations of traditional cockpits. By establishing a three-dimensional permission model of decision-making level - business domain - dimension of concern, precise adaptation of data presentation is achieved; a dual-profile construction mechanism of NLP + behavior analysis is adopted to solve the problem of dynamic matching of role requirements.

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

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0031] Figure 1 is a schematic flowchart of the steps of a method for constructing a business and group leadership cockpit provided by an embodiment of this application;

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

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

[0034] Figure 4 is a schematic structural diagram of a device for constructing a business and group leadership cockpit provided by an embodiment of this application;

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

[0036] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. Detailed implementation manners

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0038] The flowcharts shown in the accompanying drawings are only illustrative examples, not necessarily including all contents and operations / steps, nor necessarily executed in the described order. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order may be changed according to the actual situation.

[0039] It should be understood that, in order to facilitate the clear description of the technical solutions in the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that the terms "first" and "second" do not limit the quantity and execution order, and the terms "first" and "second" do not necessarily limit to be different.

[0040] It should be understood that the terms used in the specification of 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 specification of the present application and the appended claims, unless otherwise clearly specified in 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 specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0042] The following will describe in detail some implementation manners of the present application with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0043] Currently, in the management of energy enterprises, how to effectively integrate multi-source heterogeneous data and build cockpit systems suitable for different roles has always been a technical difficulty in the industry. Traditional cockpit construction methods usually rely on fixed templates and static index configurations, which are 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, lacking intelligent index matching and dynamic update mechanisms, resulting in a single function of the cockpit and being unable 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 which 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 including a computer device.

[0046] To solve the above problems, please refer to Figure 1 . Specifically, as Figure 1 shown, the provided method includes steps S101 to S105. Among them, the computer device can be a handheld terminal, a laptop, a wearable device, or a robot, etc. It is used to implement steps S101 to S105 and their corresponding embodiments.

[0047] The steps are detailed 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 an equipment layer, a business layer, and a management layer; the data corresponding to the equipment layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data.

[0049] Specifically, collect real-time operation data from multiple power plants by using edge computing nodes. Based on the collected data, construct a three-dimensional data matrix that covers three dimensions: the equipment layer, the business layer, and the management layer.

[0050] For example, the data collection of the equipment layer includes key performance indicators such as unit efficiency, fuel consumption, and environmental indicators. The data collection of the business layer includes business-related data such as production KPIs (key performance indicators) and operating costs. The data collection of the management layer includes management-level data such as strategic indicators and industry benchmarking 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 achieved, providing a reliable data basis for subsequent data analysis and decision-making. Through the three-dimensional data matrix, the operation status of the power plant can be comprehensively reflected, providing support for decision-making at different levels.

[0051] The edge computing deployment is as follows: deploy KubeEdge edge nodes on the power plant side, and collect DCS system data (such as unit vibration frequency, boiler temperature) in real time through the OPC UA protocol. Obtain smart meter data (hourly fuel flow, power generation) by using the Modbus-TCP protocol. The edge side completes data cleaning (removing outliers by the 3σ rule) and normalization processing (converting different unit indicators into 0-1 standardized values).

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

[0053] Specifically, parse the job description information of the business team and the group leaders through natural language processing technology. Construct three-dimensional user portraits of the business team and the group leaders, including the decision-making level, business area, and attention dimension. Use natural language processing technology to perform semantic analysis on the job description information and extract key information. According to the extracted information, construct user portraits to clarify the data requirements and decision-making preferences of different users. Improve the accuracy of the user portraits, enabling the cockpit system to better meet personalized needs. Through the user portraits, personalized display and push of data are realized, enhancing the user experience. The decision-making level is such as factory level / group level, the business area is such as production / finance / safety, and the attention dimension is such as cost control / equipment health. When calculating the corresponding weights of the portraits, the decision-making level weight = TF-IDF("Strategic Planning") * 0.6. The business area correlation = Word2Vec similarity("Work Safety", job description). The three-dimensional user portrait of the group leaders can be shown in the following table:

[0054]

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

[0056] Specifically, generate a business visualization interface and a group visualization interface according to the user's historical operation information. The interface includes a data dashboard, a trend graph, a 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, design and generate a visualization interface that meets the user's needs. The interface design focuses on interactivity and intuitiveness, facilitating the user to quickly obtain key information. Enhance the friendliness and usability of the user interface, enabling the user to more intuitively understand the data. Through the warning component, timely discovery and warning of potential problems are realized, improving the timeliness of decision-making.

[0057] The warning rule corresponding to the warning component can be: If the vibration of the unit > 7.5 mm / s and the duration > 30 min, trigger an orange warning and push it to the cockpit of the group leaders.

[0058] Step S104. Determine the data acquisition permissions for the business team and the group leaders based on the three-dimensional user portraits of the business team and the group leaders.

[0059] Specifically, determine the data acquisition permissions for the business team and the group leaders according to the user portraits. Combine the decision-making levels, business areas, and attention dimensions in the user portraits to set corresponding data access permissions. Implement dynamic management of permissions, and adjust the permission settings in a timely manner according to changes in user roles. Ensure the security and compliance of data, and prevent data leakage. Achieve refined management of data and improve data utilization efficiency.

[0060] Specifically, the content corresponding to the access permissions can be as follows in the table:

[0061]

[0062]

[0063] Step S105. Construct a business cockpit and a group leader cockpit respectively based on the three-dimensional data matrix, association information, business visualization interface, group visualization interface, data acquisition permissions for the business team, and data acquisition permissions for the group leaders.

[0064] Specifically, as Figure 2 and Figure 3 shown, construct a business cockpit and a group leader cockpit based on the three-dimensional data matrix, association information, business visualization interface, group visualization interface, data acquisition permissions for the business team, and data acquisition permissions for the group leaders. Integrate the results of steps S101 to S104 to construct a complete cockpit system. The cockpit system can dynamically adjust the displayed data and interface according to the user role and permissions. Achieve cross-level and cross-business data integration and display, and support complex decision-making requirements.

[0065] In some embodiments, establish a three-dimensional data matrix based on real-time operation data, including: performing data cleaning and standardization processing on the real-time operation data to generate a basic data pool at the device layer; based on a preset association rule library, dynamically map the device layer data to the business indicator logic chain to construct a set of derivative indicators at the business layer; dynamically weight the management layer data through an industry benchmarking algorithm to generate a management layer indicator topology network including strategic weight coefficients; adopt a spatio-temporal association modeling technique 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.

[0066] Collect real-time operation data of multiple power plants through edge computing nodes, including equipment status, performance parameters, environmental monitoring data, etc. Clean the collected raw data to remove noise data, missing data, and abnormal data to ensure the accuracy and integrity of the data. Standardize the cleaned data according to a unified format and standard to ensure that data from different sources has a consistent format and unit, facilitating subsequent analysis and processing. Store the cleaned and standardized equipment layer data in the basic data pool as the basis for subsequent analysis.

[0067] Based on industry standards and business requirements, preset a set of association rule libraries to define the logical relationship between equipment layer data and business metrics. Using the association rule libraries, dynamically map the data in the equipment layer basic data pool to the business metric logic chain to generate a set of business layer derived metrics. These derived metrics reflect the key performance indicators (KPIs) at the business level, such as production efficiency, cost-effectiveness, etc. Integrate the generated business layer derived metric set to form business layer data to provide support for subsequent management analysis.

[0068] Adopt an industry benchmarking algorithm to dynamically weight the management layer data. This algorithm assigns strategic weight coefficients to the management layer data by comparing best practices within the industry and the performance of competitors. Based on the dynamically weighted management layer data, generate a management layer indicator topological network containing strategic weight coefficients. This network reflects the indicators and their importance that the management layer focuses on in strategic decision-making. Integrate the generated management layer indicator topological network to form management layer data to provide support for the subsequent construction of a three-dimensional data matrix.

[0069] Adopt spatio-temporal association modeling technology to establish a two-way data traceability channel between the equipment layer, business layer, and management layer. This technology ensures the traceability and consistency of data between different levels by analyzing the spatio-temporal correlation relationships of data. Through the two-way data traceability channel, implement a dynamic feedback mechanism between the equipment layer, business layer, and management layer. When the data at a certain level changes, the system can automatically adjust the data at other levels to ensure data consistency and real-time performance. Combine the equipment layer basic data pool, business layer derived metric set, and management layer indicator topological network, as well as the two-way data traceability channel and dynamic feedback mechanism, to form a three-dimensional data matrix architecture with a dynamic feedback mechanism.

[0070] Through data cleaning and standardization, the accuracy and consistency of device-layer data are ensured, providing a reliable basis for subsequent analysis. The two-way data traceability channel and dynamic feedback mechanism ensure the consistency and real-time nature of data across the device layer, business layer, and management layer, avoiding data silos and inconsistencies. Through dynamic mapping and the business-layer derived metric 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 the business operation status, optimize business processes, and improve business efficiency.

[0071] During the data cleaning and standardization process, first, an improved DBSCAN clustering algorithm is adopted to perform dynamic outlier detection on the real-time data stream, and a unified data coordinate system is established for data alignment, as shown in the following table:

[0072] Original data type Normalization method Storage format Unit vibration (mm / s) Z-score normalization float32 Calorific value of coal (kcal / kg) Min-Max normalization uint16 <![CDATA[Flue gas SO2 concentration (mg / m 3 )]]> Logarithmic transformation float32

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

[0074] Feature vectors are extracted from the three-dimensional user portraits of the business team and the group leadership, and these vectors represent the key attributes and preferences of the users. A dynamic permission matrix is constructed using the portrait feature vectors, which defines the access permissions of different users to different data. The decision-making level determines the vertical penetration depth of the data, that is, the depth of the data that a user can access. The business domain limits the horizontal data scope of the dynamic permission matrix, that is, the breadth of the data that a user 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 leadership 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, the permissions are flexibly adjusted according to changes in user roles. Users can quickly access the data they need, improving work efficiency and data utilization efficiency.

[0075] Exemplarily, the method further includes: establishing a user profile update mechanism based on a dynamic decay algorithm to automatically adjust the profile dimension weights corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders according to the user operation logs corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders.

[0076] Based on the dynamic decay algorithm, establish a user profile update mechanism. This mechanism automatically adjusts the profile dimension weights of the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders according to the user operation logs. Collect and analyze the user operation logs to identify changes in the user's operation habits and preferences. Dynamically adjust the weights of each dimension in the user profile according to the behavioral characteristics in the operation logs. Dynamically adjust the weights of dimensions such as the decision-making level, business area, and attention dimension in the user profile according to the dynamic decay algorithm. Ensure that the user profile can timely reflect the user's latest needs and preferences. Establish an automated user profile update mechanism to regularly update the user profile according to the latest user operation logs. Reduce manual intervention and improve the timeliness and accuracy of the user profile. Through the dynamic decay algorithm and the automatic update mechanism, ensure that the user profile can reflect the user's latest needs and preferences in real time. Dynamically adjust the profile dimension weights so that the system can better adapt to the changes of the user and improve the flexibility and adaptability of the system. The automated update mechanism reduces manual intervention and improves the efficiency and accuracy of user profile management.

[0077] In some embodiments, generating a business visualization interface and a group visualization interface according to the historical operation information corresponding to the business team and the group leaders respectively, includes: parsing the historical operation information to obtain the component interaction frequency and the path jump characteristics for constructing a heat map of visualization element popularity; determining the interface templates corresponding to the business visualization interface and the group visualization interface according to the heat map of visualization element popularity; determining the warning components and the corresponding dynamic threshold mechanisms corresponding to the business visualization interface and the group visualization interface according to the business area and the attention dimension; generating the business visualization interface and the group visualization interface respectively according to the interface templates, the warning components, and the corresponding dynamic threshold mechanisms.

[0078] Collect the historical operation logs of the business team and group leaders. Use data analysis techniques to parse the logs and extract the component interaction frequency and path jump characteristics. Based on the component interaction frequency and path jump characteristics, construct a heat map of visual elements to identify the most frequently accessed and concerned interface elements by users. According to the heat map of visual elements, select or design an interface template suitable for the business team and group leaders to improve the usability of the interface and user satisfaction. According to the business domain and the dimension of concern, 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 so that the warning trigger conditions can be automatically adjusted according to 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 an interface that better conforms to user habits and enhances the user experience. The dynamic threshold mechanism enables the warning system to be adjusted dynamically according to actual business data, improving the accuracy and timeliness of warnings. Through the heat map and warning components, help users identify key issues and trends faster, thus optimizing the decision-making process.

[0080] In some embodiments, determine the data access rights of the business team and group leaders according to the three-dimensional user portraits of the business team and the three-dimensional user portraits of the group leaders, including: respectively obtaining the portrait feature vectors corresponding to the three-dimensional user portraits of the business team and the three-dimensional user portraits of the group leaders; constructing a dynamic permission matrix based on the portrait feature vectors; the decision level corresponds to the vertical penetration depth of the data in the dynamic permission matrix, and the business domain limits the horizontal data range of the dynamic permission matrix; determine the data access rights of the business team and group leaders according to the dynamic permission matrices corresponding to the three-dimensional user portraits of the business team and the three-dimensional user portraits of the group leaders.

[0081] Extract feature vectors from the three-dimensional user portraits of the business team and the three-dimensional user portraits of the group leaders, and these vectors represent the key attributes and preferences of users.

[0082] Use the portrait feature vectors to construct a dynamic permission matrix, which defines the access rights of different users to different data. The decision level determines the vertical penetration depth of the data, that is, the depth of the data that users can access. The business domain limits the horizontal data range of the dynamic permission matrix, that is, the breadth of the data that users can access. According to the dynamic permission matrix and the portrait feature vectors of users, determine the data access rights of the business team and group leaders.

[0083] Implement more refined data permission management through the dynamic permission matrix to improve data security. While ensuring that data access complies with organizational compliance requirements, flexibly adjust 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, a business cockpit and a group leader cockpit are respectively constructed based on a three-dimensional data matrix, association information, a business visualization interface, a group visualization interface, business team data access rights, and group leader data access rights, including: establishing dynamic association relationships corresponding to the device layer, business layer, and management layer based on the three-dimensional data matrix, association information, business team data access rights, and group leader data access rights by using graph database technology; obtaining business data corresponding to the business visualization interface and the group visualization interface from the three-dimensional data matrix according to the dynamic association relationships, for adding the business data to the business visualization interface and the group visualization interface to complete the construction of the business cockpit and the group leader cockpit.

[0085] Using graph database technology, dynamic association relationships are established among the device layer, business layer, and management layer according to the three-dimensional data matrix, association information, business team data access rights, and group leader data access rights. According to the dynamic association relationships, the business data required for the business visualization interface and the group visualization interface is obtained from the three-dimensional data matrix. The obtained business data is added to the business visualization interface and the group visualization interface to complete the construction of the business cockpit and the group leader cockpit. By integrating multi-source data through graph database technology, in-depth analysis and data mining are realized, providing more comprehensive data support. The business cockpit and the group leader cockpit provide a centralized platform, enabling decision-makers to quickly obtain key information and improve decision-making efficiency. Through real-time updated business data and dynamic association relationships, the data-driven decision-making ability is enhanced, helping the management to make more accurate business decisions.

[0086] In some embodiments, a machine learning algorithm can be used to train a data cleaning model to automatically identify and process noisy data, missing data, and abnormal data. The model can dynamically adjust the cleaning rules according to the historical data characteristics to improve the accuracy and efficiency of data cleaning. An intelligent standardization engine is developed, which can automatically identify the formats and units 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 to ensure the accuracy and consistency of the standardization process.

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

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

[0089] The business layer derivative metrics generated by the graph neural network can more accurately reflect the business operation status, providing deeper insights for business decision-making. The dynamic metric update mechanism ensures the timeliness and dynamics of the business layer data, improving the timeliness and accuracy of business decision-making.

[0090] In some embodiments, a strategic weight coefficient optimization model is trained using reinforcement learning algorithms. The model dynamically adjusts the strategic weight coefficients of the management layer data by simulating the industry benchmarking and strategic decision-making processes. The model can dynamically optimize the strategic weight coefficients according to real-time industry data and strategic goals, ensuring the scientificity and effectiveness of the management layer metric topology network. By introducing a reward mechanism, the model can automatically identify key strategic metrics, improving the pertinence and effect of weight coefficient optimization. The strategic weight coefficients optimized by reinforcement learning provide a more scientific basis for strategic decision-making, improving the accuracy and effectiveness of decision-making. The dynamic optimization mechanism enables the strategic weight coefficients to respond in real time to industry changes and strategic goals, 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 the traceability and consistency among the device layer, business layer, and management layer data. The distributed ledger technology of the blockchain ensures the transparency and immutability of the data, improving the credibility and security of the data. Smart contracts are developed to implement a dynamic feedback mechanism among the device layer, business layer, and management layer. When the data at a certain level changes, the smart contract can automatically trigger data adjustments at other levels to ensure data consistency and timeliness.

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

[0093] In some embodiments, augmented reality (AR) and virtual reality (VR) technologies are utilized to construct a visual business cockpit and a group leadership cockpit. Users can intuitively view and analyze three-dimensional data matrices, business layer derivative metrics, and management layer metric topology networks through AR / VR devices. An interactive data exploration function is developed, enabling users to interact with the data in the cockpit through gestures and voice commands to obtain deeper 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, enhancing the user experience. AR / VR technologies make data display more intuitive and vivid, improving the user's understanding and analysis efficiency. The interactive data exploration and personalized adjustment functions enhance the user's operation experience and satisfaction, and strengthen the intelligence and adaptability of the system.

[0094] Please refer to Figure 4 as shown in Figure 4 FIG. 7 is a schematic structural diagram of a construction device 200 for a business and group leadership cockpit provided by an embodiment of the present application. The construction device 200 for the business and group leadership cockpit is used to execute the steps of the construction method for the business and group leadership cockpit shown in the above embodiments. The construction device 200 for the business and group leadership cockpit can be a single server or a server cluster, or the construction device 200 for the business and group leadership cockpit can be a terminal, which can be a handheld terminal, a laptop, a wearable device, or a robot, etc.

[0095] As Figure 4 shown in FIG. 8, the construction device 200 for the business and group leadership cockpit includes:

[0096] A data acquisition unit 201, configured to 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 an equipment layer, a business layer, and a management layer; the data corresponding to the equipment layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data;

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

[0098] An interface generation unit 203 is configured to generate a business visualization interface and a group visualization interface respectively according to the 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 an early warning component;

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

[0100] A construction completion unit 205 is configured to construct a business cockpit and a group leader cockpit respectively 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.

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

[0102] The above construction of the business and group leader cockpits can be implemented in the form of a computer program, and this computer program can run on a device as shown in Figure 4 shown.

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

[0104] The storage medium can store an operating device and a computer program. This computer program includes program instructions, and when the program instructions are executed, the processor can be made to execute any construction of the business and group leader cockpits.

[0105] The processor is used 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. When the computer program is executed by the processor, the processor can be made to execute any construction of the business and group leader cockpits.

[0107] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 5The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the terminal to which the solution of this application is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

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

[0109] Among them, in one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0110] 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 an equipment layer, a business layer, and a management layer; the data corresponding to the equipment layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data;

[0111] Obtain the job description information of the business team and the job description information of the group leaders, and parse the job description information of the business team and the job description information of the group leaders according to natural language processing to construct a three-dimensional user portrait of the business team and a three-dimensional user portrait of the group leaders; both the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders include a decision-making level, a business area, and a dimension of concern;

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

[0113] Determine the data acquisition permissions of the business team and the data acquisition permissions of the group leaders according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders;

[0114] Construct a business cockpit and a group leader cockpit respectively according to the three-dimensional data matrix, associated information, business visualization interface, group visualization interface, data acquisition permissions of the business team, and data acquisition permissions of the group leader.

[0115] 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 above-described processor can refer to the corresponding process in the construction embodiments of the business and group leader cockpits described in the above embodiments, and will not be elaborated herein.

[0116] An embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and 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] Among them, the computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the computer device.

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

Claims

1. A method for constructing a business and group leadership cockpit, characterized in that Including: Collecting real-time operation data of multiple power plants through edge computing nodes, and establishing a three-dimensional data matrix according to the real-time operation data; the three-dimensional data matrix includes an equipment layer, a business layer, and a management layer; the data corresponding to the equipment layer at least includes unit efficiency, fuel consumption, and environmental indicators, the data corresponding to the business layer at least includes production KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data; Obtaining job description information of business teams and job description information of group leaders, parsing the job description information of business teams and job description information of group leaders according to natural language processing, and constructing three-dimensional user portraits of business teams and three-dimensional user portraits of group leaders; both the three-dimensional user portraits of business teams and the three-dimensional user portraits of group leaders include decision-making levels, business areas, and attention dimensions; Generating a business visualization interface and a group visualization interface respectively according to the 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; Determining the data acquisition permissions of the business team and the data acquisition permissions of the group leader according to the three-dimensional user portraits of the business team and the three-dimensional user portraits of the group leader; Constructing a business cockpit and a group leader cockpit respectively according to the three-dimensional data matrix, association information, business visualization interface, group visualization interface, data acquisition permissions of the business team, and data acquisition permissions of the group leader.

2. The method according to claim 1, wherein The establishing of the three-dimensional data matrix according to the real-time operation data includes: Performing data cleaning and standardization processing on the real-time operation data to generate a basic data pool for the equipment layer; Based on a preset association rule library, dynamically mapping the equipment layer data with the business indicator logic chain to construct a set of derivative indicators for the business layer; Dynamically weighting the management layer data through an industry benchmarking algorithm to generate a management layer indicator topological network including strategic weight coefficients; Adopting a spatio-temporal association modeling technology to establish a two-way data traceability channel between the equipment layer, the business layer, and the management layer, and forming a three-dimensional data matrix architecture with a dynamic feedback mechanism.

3. The method according to claim 1, characterized in that The parsing of the job description information of business teams and job description information of group leaders according to natural language processing to construct three-dimensional user portraits of business teams and three-dimensional user portraits of group leaders includes: Performing entity relationship extraction on the job description information of business teams and job description information of group leaders respectively according to a domain knowledge graph, and identifying the core decision-making elements corresponding to the job description information of business teams and job description information of group leaders; Adopting a semantic analysis model driven by an attention mechanism to respectively obtain the decision-making preference intensity coefficients corresponding to the job description information of business teams and job description information of group leaders; Performing feature extraction on the job description information of business teams and job description information of group leaders to respectively obtain the job level features corresponding to the job description information of business teams and job description information of group leaders; Obtaining the historical behavior features corresponding to the historical operation information; Constructing three-dimensional user portraits of business teams and three-dimensional user portraits of group leaders according to the core decision-making elements, decision-making preference intensity coefficients, job level features, and historical behavior features.

4. The method according to claim 3, characterized in that, The method further includes: Establish a user profile update mechanism based on a dynamic attenuation algorithm to automatically adjust the profile dimension weights corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders according to the user operation logs corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders.

5. The method according to claim 1, characterized in that, Generating a business visualization interface and a group visualization interface respectively according to the historical operation information corresponding to the business team and the group leaders, including: Analyze the historical operation information to obtain component interaction frequencies and path jump characteristics for constructing a heat map of visualization element popularity; Determine the interface templates corresponding to the business visualization interface and the group visualization interface according to the heat map of visualization element popularity; Determine the warning components and corresponding dynamic threshold mechanisms corresponding to the business visualization interface and the group visualization interface according to the business domain and the dimensions of interest; Generate a business visualization interface and a group visualization interface respectively according to the interface templates, warning components and corresponding dynamic threshold mechanisms.

6. The method according to claim 1, wherein Determining the data access rights of the business team and the data access rights of the group leaders according to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders, including: Respectively obtain the profile feature vectors corresponding to the three-dimensional user profiles of the business team and the three-dimensional user profiles of the group leaders; Construct a dynamic permission matrix based on the profile feature vectors; the decision-making level corresponds to the vertical penetration depth of the data of the dynamic permission matrix, and the business domain defines the horizontal data range of the dynamic permission matrix; Determine the data access rights of the business team and the data access rights of the group leaders according to 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.

7. The method according to claim 1, characterized in that Constructing a business cockpit and a group leader cockpit respectively according to the three-dimensional data matrix, association information, business visualization interface, group visualization interface, data access rights of the business team and data access rights of the group leaders, including: Establish dynamic association relationships corresponding to the device layer, business layer and management layer based on the three-dimensional data matrix, association information, data access rights of the business team and data access rights of the group leaders according to graph database technology; Obtain the business data corresponding to the business visualization interface and the group visualization interface from the three-dimensional data matrix according to the dynamic association relationships, and use the business data to add to the business visualization interface and the group visualization interface to complete the construction of the business cockpit and the group leader cockpit.

8. A construction device for a business and group leadership cockpit, characterized in that, The device includes: A data acquisition unit for collecting real-time operation data of multiple power plants through edge computing nodes and establishing 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 KPIs and operating costs, and the data corresponding to the management layer at least includes strategic indicators and industry benchmarking data; An information acquisition unit, configured to acquire the job description information of the business team and the job description information of the group leaders, parse the job description information of the business team and the job description information of the group leaders according to natural language processing, and construct a three-dimensional user portrait of the business team and a three-dimensional user portrait of the group leaders; both the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders include the decision-making level, business areas, and attention dimensions. An interface generation unit, configured to generate a business visualization interface and a group visualization interface respectively according to the historical operation information corresponding to the business team and the group leaders; the visualization interface at least includes a data dashboard, a trend graph, and a warning component. A permission acquisition unit, configured to determine the data acquisition permissions of the business team and the data acquisition permissions of the group leaders according to the three-dimensional user portrait of the business team and the three-dimensional user portrait of the group leaders. A construction completion unit, configured to construct a business cockpit and a group leader cockpit respectively according to the three-dimensional data matrix, the association information, the business visualization interface, the group visualization interface, the data acquisition permissions of the business team, and the data acquisition permissions of the group leaders.

9. 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 implement the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer-readable instructions are executed by the processor, one or more processors are caused to execute the steps of the method according to any one of claims 1 to 7.

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