39 results about "Data flow diagram" patented technology

The invention provides an MCM-GPU-oriented resource storage optimization method, device and equipment, and the method comprises the steps: carrying out the static analysis of an operator-level data flow diagram of a calculation task in a compiling stage, and extracting the data dependence relation and life cycle characteristics of each operator; generating a storage optimization scheme based on the data dependency relationship and life cycle characteristics of each operator; in the operation stage, task and data collaborative allocation is carried out according to a data prefetching strategy and a data replacement strategy, task and data collaborative allocation and the calculation task are executed in parallel, and a data flow diagram and an operator dependency relationship of the task are analyzed by utilizing a compiling period; in combination with the data locality characteristics of the MCM-GPU multi-level storage architecture and the concurrency requirements of different modules for data access, an appropriate GPU module is selected to carry out data optimization management, so that frequent data exchange between a GPU and a CPU is reduced, and the performance potential of the MCM-GPU architecture in a super-large-scale task is brought into full play.

The invention discloses a coarse-grained reconfigurable architecture cyclic mapping method and device based on a graph neural network, and relates to the technical field of computer reconfigurable computing. The method comprises the following steps: based on a priority prediction model, performing list scheduling according to a data flow diagram and hardware information to obtain a list scheduling table; performing modular scheduling according to the data flow diagram and the hardware information; pre-scheduling the data flow diagram on the basis of a list scheduling table according to the modular data flow diagram and the time extension coarse-grained array to obtain a time step attribute data flow diagram; obtaining a mapping result by using a mapping algorithm based on pattern diagram matching according to the time step attribute data flow diagram on the basis of the time extension coarse-grained array; based on the hardware information, processing unit isomorphism verification is carried out according to the mapping result; and compiling the verified mapping result to obtain an executable configuration information file. The invention provides an efficient and accurate coarse-grained reconfigurable architecture cyclic mapping method based on a graph neural network.

The invention discloses a scheduling-driven high-level comprehensive array division method, which comprises the following steps of: creating an associated access instruction set for arrays in algorithm design, and analyzing an address calculation expression of each access instruction; on the basis of the control data flow diagram designed by the algorithm, instruction scheduling is executed according to an instruction topological sequence and circuit performance requirements, for an array access instruction, a schedulable interval of the array access instruction is calculated, control steps in the interval are traversed, and incremental address conflicts introduced by each scheduling mode are determined; aiming at each scheduling mode of the array access instruction, a minimum overhead array division scheme capable of solving all address conflicts is searched, and the overhead of the division scheme comprehensively considers the number of storage modules after division, address control logic complexity and time delay; the address conflicts comprise the incremental address conflicts and the stock address conflicts. The method has the advantages that compared with an existing array division scheme, calculation scheduling and array division are organically combined, the cost of array division is reduced, and the scheduling performance is improved.

The embodiment of the invention provides a software vulnerability mining method and device based on static analysis and big and small model collaboration.The method comprises the following steps that attack faces are recognized and classified, and a code line annotation node set is generated; performing first-stage filtering on the code line annotation node set based on rules, and performing second-stage filtering on the annotation node set after primary filtering based on a twin neural network; taking a high-confidence node in the high-confidence attack surface set as a tracking starting point, generating a basic data flow diagram, obtaining a front-edge node set through static analysis, expanding the front-edge node set through a large language model and a path expansion algorithm, and generating a complemented data flow diagram; and detecting vulnerabilities based on the complemented data flow diagram to obtain a software vulnerability mining result. According to the scheme, through cooperation of the large language model and the twinning neural network, the false alarm rate is reduced, and the coverage rate and accuracy of vulnerability mining are improved.

The invention relates to the technical field of computer software and digital signal processing, and discloses an audio engine real-time processing method and system based on topological sorting, and the method comprises the following steps: packaging an audio processing logic into an independent Block unit; all the Blocks exchange data through the shared audio bus, and each Block reads and writes data on the audio bus according to the input bus identifier and the output bus identifier of the Block, so that decoupling of the functional unit is realized. The core of the invention lies in that the system dynamically generates a unique and correct execution sequence of all Blocks by carrying out topological sorting on the data flow diagram before processing. The calculation ensures that any Block is executed after its data source Block by reversely traversing the data flow diagram from the final output Block. According to the method, the time sequence correctness and the system stability of the data stream in any complex and dynamically variable audio processing link are effectively ensured, and meanwhile, the flexibility and the intuition of audio processing flow construction are greatly improved.

The invention discloses a mold project progress lag risk early warning method, which is applied to the technical field of risk early warning, and comprises the following steps: defining a key monitoring node of an automobile mold, and constructing a risk judgment rule base containing a threshold value, a key index and a task dependency relationship; the plan data and the multi-source actual feedback data are integrated, the plan data and the actual execution data are compared in real time through an intelligent linkage engine, a progress deviation value is calculated, and an early warning node is recognized according to a threshold value in a risk judgment rule base; based on the dependency relationship in the risk decision rule base, the identified early warning node is evaluated, the influence path of the early warning node is simulated, and a visual data flow diagram is generated; and triggering a grading early warning notification according to the risk grade in the evaluation result. According to the method, various risk factors are fused into the comprehensive risk index through the dynamic aggregation algorithm, so that the accuracy and reliability of risk early warning are effectively improved.

The invention discloses an intelligent application recommendation and aggregation method and device based on scene perception, and relates to the technical field of mobile computing and human-computer interaction. The method comprises the steps of inputting multi-dimensional data of a current user scene into a pre-trained intention recognition model, and outputting a current task type of a user and an associated application function demand; screening application components meeting all application function requirements; constructing a cross-application API bus, and generating a data flow diagram; generating a dynamic aggregation interface through an adaptive layout engine; in the interaction process, data field change is monitored in real time, and preloading and data updating of downstream application components are triggered through an API bus; if the user leaves the current task scene, unused application components are automatically unloaded. By adopting the technical scheme provided by the invention, the task completion steps can be reduced by more than half; the cross-application data synchronization delay is maintained at a hundred millisecond level; and a multi-mode input triggering aggregation service is supported.

The invention belongs to the technical field of astronomical star-pointing explanation software, and discloses a master control method of an intelligent astronomical star-pointing explanation instrument, which comprises an intelligent voice interaction module, a celestial body positioning calibration module and a large model knowledge engine and interaction module. The invention also provides a modularized layered architecture which covers three core modules, namely a voice interaction module, a celestial body positioning module and a large-model knowledge engine module. Through a use case diagram and a data flow diagram, interaction logic between a user and a system and a flow mode of data between software and hardware are presented. Meanwhile, the software and hardware list and the deployment diagram further define resource and environment configuration required by system operation. The key technology design focuses on the problems of data interaction protocols, voice recognition optimization, user experience enhancement and the like, for example, the voice recognition error rate is reduced through fuzzy matching, the telescope operation precision is improved through rocker hierarchical control, and the learning requirements of different users are met through hierarchical knowledge display.

The embodiment of the invention provides a vehicle safety risk control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a business data flow diagram and asset category information of a target vehicle, the business data flow diagram being used for representing the data flow relationship among a plurality of information safety assets associated with the target vehicle, and the asset category information being used for representing the asset category information of the target vehicle; the asset category information is used for representing asset types and security attributes of the plurality of information security assets; determining a risk attack path based on the business data flow diagram, and determining target risk scene information based on the business data flow diagram and the asset category information; performing assessment processing on the target risk scene information and the risk attack path to obtain a risk assessment result; and determining a target risk control strategy of the target vehicle according to the risk assessment result. The technical problems that a vehicle safety risk control method provided in the related technology is low in standardization degree and high in implementation threshold are solved.

1. The name of the design product: electronic device data flow display graphical user interface. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the present design graphical user interface is used to display data flow. Design 1 front view is a data flow display page, the interface displays multiple function modules and the flow direction between each data module, the current page displays data overview, when the user clicks the left first function icon of data source management, design 1 interface change state diagram is presented, which is used to view index overview. Design 2 front view is a data flow display page, the interface displays multiple function modules, data flow direction and index overview, the current page displays data overview, when the user clicks the "index panel" button at the bottom of the interface, design 2 interface change state diagram is presented, which is used to display index details.

This invention discloses a DSP-based synthetic aperture radar (SAR) imaging component design method. The main idea is to build a processing system for this DSP-based SAR imaging component design method. First, a command parsing framework is built in the signal processing board (DSP). Then, a data flow diagram for the DSP-based SAR imaging component design method is constructed. Finally, the RD algorithm is implemented using the DSP, controlled by the main control board, to process the radar echo data, thereby realizing the software-based implementation of SAR imaging technology and decoupling the SAR imaging algorithm from the hardware. This design method can adapt to different hardware resources.

The invention discloses a fully homomorphic encryption operation method, a fully homomorphic encryption operation system and a non-transient computer readable recording medium thereof. The fully homomorphic encryption operation method comprises the following steps: receiving a homomorphic encryption application; converting the homomorphic encryption application into a data flow diagram; and scheduling the data flow diagram according to the connection relationship of the plurality of processing modules and the execution time to generate a scheduling result. Wherein the processing modules have at least two different processor types.

The invention provides a high-reliability multi-data flow diagram execution device, which is characterized in that a proxy distribution module is used for storing a pre-generated data flow diagram pool when a current program is executed, and a plurality of data flow diagrams in the data flow diagram pool are loaded to a reconfigurable array in parallel under the control of a feedback control module; when the data flow diagram is wrongly calculated, other data flow diagrams which belong to the same program with the data flow diagram which is wrongly calculated are scheduled; the reconfigurable computing array is used for executing a plurality of heterogeneous data flow diagrams corresponding to the same to-be-executed program in parallel; the strategy judgment module is used for judging whether calculation is correct or not, outputting a result when the calculation is correct, marking a data flow diagram of a calculation error when the calculation result is wrong, and feeding back the data flow diagram to the reconfigurable calculation array and the feedback control module; and the feedback control module is used for controlling the operation of the whole device and sending the received feedback information to the proxy distribution module so as to control the proxy distribution module to schedule and calculate other data flow diagrams, belonging to the same program, of the wrong data flow diagrams in the diagram pool.

The invention discloses a fusion safety-oriented potential hazard identification method for a high-level intelligent driving system, and belongs to the technical field of intelligent networked automobiles. Based on the requirements of three types of standards of ISO26262, ISO21448 and ISO / SAE21434, the method is integrated in a unified hazard identification process, and the method comprises the following steps: defining system related items and assets, analyzing and identifying vehicle hazards by HAZOP, establishing a system safety control structure, mapping a network safety data flow diagram, and identifying unsafe control behaviors and causes including component faults, insufficient safety of expected functions and STRIDE network threats. Potential hazards of system-level hazards caused by system faults, function limitation and network attacks are comprehensively recognized in the same framework, the problems of incomplete dimension coverage, repeated recognition, hazard omission and the like of an existing method are solved, hazard recognition integrity and development efficiency are improved, and the method is suitable for safe development of various high-level intelligent driving systems and has wide application prospects. And the method has wide engineering application value.

The invention relates to the field of data processing, in particular to a visual data pipeline generation method and system.The method comprises the forward process of converting an initial data flow diagram into a target language code and the reverse process of converting the target language code into the initial data flow diagram; the method comprises the following steps: after obtaining a target language code depending on a forward or reverse process, storing the target language code into a preset database, and finally, responding to trigger started by a user, converting the target language code stored in the database into a final data flow diagram and executing line production according to the final data flow diagram. Compared with the prior art, the method solves the problem that in the prior art, the consistency of data processing assembly lines is difficult to synchronize.

The invention relates to the technical field of building engineering information, and discloses an engineering project digital archive management method based on BIM. The method comprises the following steps: initializing a BIM platform environment, importing a BIM model and related archive data, and carrying out standardization processing; constructing a project component association graph and an archive data flow graph by using a graph technology; and capturing state change through event monitoring, and synthesizing a project operation state diagram and an archive data dynamic flow diagram in real time. The core innovation lies in that a row calls a semantic analyzer and an authority checker to scan and check a double-dynamic graph, and outputs an abnormal identifier set; positioning an abnormal node and performing dependency chain backtracking along an archive flow graph, and accurately extracting a problem root; a test case is generated by combining static analysis and a novel test strategy, and defect details are monitored and recorded during operation. And integrating the problem root and the defect record to generate a comprehensive management report. According to the invention, the real-time performance of engineering file management and the accuracy of problem tracing are improved.

The embodiment of the invention discloses an encrypted circuit generation method and device, equipment and a medium, and the method comprises the steps: obtaining a data flow diagram of a cryptographic algorithm, and enabling different types of nodes in the data flow diagram to represent electronic devices corresponding to different types of encryption operations in the cryptographic algorithm; according to the type of the node in the data flow diagram, a time sequence score and a power consumption score of the node are determined from a preset security score library, the time sequence score represents the time delay of the node in the encryption process, and the power consumption score represents the power consumption of the node in the encryption process; determining a plurality of security type diagrams according to the connection relationship of the sub-diagrams of the data flow diagram and the time sequence score and the power consumption score of each node; and generating a compatibility graph according to the plurality of security type graphs, determining a target fusion graph according to the compatibility graph, and generating an encrypted circuit according to the target fusion graph. According to the technical scheme provided by the invention, the comprehensive performance and safety of the encrypted circuit can be improved, and the quality of the encrypted circuit is improved.

The invention relates to the technical field of data processing, and discloses a code page generation method and system based on AI and a historical page, and the method comprises the steps: obtaining historical page configuration data stored in a code platform, analyzing the historical page configuration data based on an AI algorithm, mining a business concept entity and a business operator, and generating the business concept entity and the business operator; meanwhile, on the basis of data processing, the logic dependency relationship among the elements is recognized, a domain service concept map is generated, through the generated domain service concept map, conversion from isolated component features to a semantic service knowledge system is achieved, complex service association among the components is accurately captured, and through a declarative data flow diagram, the content of the components in the domain service knowledge system is improved. According to the method, data format compatibility and transmission efficiency are ensured, rapid delivery of a platform native application package is realized through an executable application mirror image and a hot deployment mechanism, and it is ensured that the generated code user interface has a complete service function and stable operation performance.

The invention relates to the field of electronic design automation, in particular to an integrated circuit power consumption analysis method based on source code analysis, and the method mainly comprises the steps: collecting a source code of an integrated circuit to be analyzed, and converting the source code into an initial control data flow diagram through a compiling tool; executing hardware logic optimization on the initial control data flow diagram to obtain a hardware perception diagram structure diagram; calculating a node signal activity rate of the hardware perception graph structure diagram to obtain a customized control data flow diagram; constructing a hierarchical power consumption model, wherein the hierarchical power consumption model comprises a data operation hierarchy, an inner-layer circulation hierarchy and an outer-layer design hierarchy; and analyzing the customized control data flow diagram through the hierarchical power consumption model to obtain the total power consumption of the integrated circuit to be analyzed. According to the method, efficient and accurate power consumption estimation can be directly realized from the programming language before the HLS stage, and an EDA tool chain does not need to be called, so that the power consumption analysis efficiency is improved, the optimization space is expanded, and the noise influence is inhibited.

1. The name of the design product: electronic device graphical user interface for data analysis and risk assessment early warning. 2. The use of the design product: the design product is used for electronic devices. 3. The design points of the design product: the content of the graphical user interface displayed in the view. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the design is a graphical user interface for integrating, analyzing, evaluating, and early warning and visualizing data. 6. The change state of the graphical user interface: the front view is a function selection page, clicking the function button in the front view can enter the corresponding function interface, showing the overall risk assessment analysis, selecting the "state" in the front view jumps to interface change state figure 1; interface change state figure 1 shows the real-time evaluation state of XX dimensions, clicking XX1 of manufacturer 1 in interface change state figure 1 jumps to interface change state figure 2, which shows the account information of XX1, the basic information and real-time situation of managing XX1, and clicking the "evaluation" in interface change state figure 2 jumps to interface state figure 3; interface change state figure 3 shows the situation curve result of situation 1 through the data flow diagram of data involved fusion.

The invention relates to the technical field of deep learning, in particular to a deep learning analysis method and system for big data processing, and the method comprises the following steps: obtaining a node and port sequence to construct a path table, recognizing tensor merging nodes, dynamically extracting and updating nodes to analyze a delay sequence, and screening a main path mapping relation. And constructing a data flow diagram to generate an analysis result. According to the method, tensor combination nodes are extracted to construct a path fusion structure, structural state resetting is achieved by combining input data changes of training batches, path stability is analyzed and recognized through combination of a delay difference sequence and a peak sequence, main paths are screened with delay and resource parameters as standards, and a node chain relation is mapped; according to the method, a calculation graph sequence is subjected to visual archiving in a structured data flow form, so that comprehensive optimization of a structure evolution trend, path execution performance and a resource scheduling strategy in a large-scale heterogeneous training scene is realized, and the response adaptation capability of a training process in a dynamic data environment is improved.

The invention discloses a heuristic verification method and system for anti-side channel mask non-interference security, and belongs to the technical field of information security. In order to solve the problems of complex safety verification process and low efficiency of a high-order mask scheme, a probe numbering mode based on a data flow diagram is mainly adopted, a simulation set is constructed through a heuristic method, and the statistical independence of the simulation set and a detection set is judged, so that whether the detection set is safe or not is verified. According to the method, efficient and safe verification of a complex mask scheme under side channel attack resistance can be achieved, and the method has the advantages of being high in simulation set hit rate, high in verification efficiency and wide in application range.

The invention relates to the technical field of integrated circuit hardware security, in particular to a robust hardware Trojan horse detection model generation method based on adversarial training, and the method comprises the steps: obtaining an integrated circuit design infected by a hardware Trojan horse; flattening each integrated circuit design, converting the integrated circuit design into a control-data flow diagram, and extracting a statement path from an input signal to an output signal; carrying out segmentation and label labeling on each extracted statement path, generating an original sample set to train the initial network, and further generating an original hardware Trojan horse detection model; on the basis of the signal significance score and an original hardware Trojan horse detection model, carrying out adversarial attack on all original hardware Trojan horse samples in the original sample set, and generating a hardware Trojan horse adversarial sample set; and confrontation training is performed on the original hardware Trojan horse detection model based on the two sample sets to generate the robust hardware Trojan horse detection model, so that confrontation sample attack in the hardware Trojan horse detection process can be effectively resisted, and the detection precision is improved.

The invention belongs to the technical field of data information processing, and relates to a process-based information system data quality evaluation method, which comprises the following steps of: 1, drawing an information system data flow chart; 2, a DQ-Petri network is constructed; 3, constructing a data quality evaluation model; 4, calculating data quality loss caused by data transmission; 5, evaluating the data quality of the information system; according to the method, black boxes of all links are opened through the evaluation model based on the process, and a manager can locate a source node of a quality problem in real time; the visual and quantitative evaluation of the data quality condition of each link in the data flow is realized, and fine management is supported; by identifying the problem generation link, the implementation of a'source control 'strategy instead of'post cleaning' in the prior art is assisted, the generation of new quality problems is reduced, and the high cost of long-term repeated cleaning is avoided.

The invention discloses a data processing system and method, electronic equipment, a storage medium and a program product. The system comprises a configuration layer and an operation layer, wherein the configuration layer comprises a rule configuration module. The rule configuration module is used for creating logic for operating data at any node associated with a data flow executed on a computing platform, converting the generated logic into an initial data flow diagram, converting the initial data flow diagram into a target data flow diagram matched with different operating environments, and transmitting the target data flow diagram to the computing platform. And sending the target data flow diagram to an operation layer. The operation layer is used for loading a target data flow diagram and deploying the target data flow diagram to a corresponding computing platform for execution, the operation layer comprises a data access module, a data processing module and a data output module, and the data input module is used for receiving to-be-processed data and outputting the to-be-processed data; the data processing module is used for processing the to-be-processed data based on the target data flow diagram by utilizing a calculation engine corresponding to the operation layer to obtain a data processing result; and the data output module is used for outputting the data processing result.

Techniques described herein relate to a method for performing threat modeling. The method includes obtaining a threat modeling request associated with a process executing on a node of a cluster; in response to the obtaining: generating node information associated with the process; generating a data flow diagram associated with the process using the node information; comparing the node information with a threat database to predict at least one threat associated with the process; generating a threat report based on the at least one threat; providing the threat report and data flow diagram to a user associated with the process; and initiating performance of threat mitigation based on the threat report and the data flow diagram.

1. The name of the design product: the drawing area of the data flow diagram drawing graphical user interface of an electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the local part of the graphical user interface in the electronic device is requested for protection. 4. The picture or photo that best indicates the design points: design 1 change state diagram 1. 5. Design 2 is designated as the basic design. 6. The use of the graphical user interface: the graphical user interface is used to draw a data flow diagram. The local part of the graphical user interface requested for protection is used to draw a data flow diagram. 7. The human-computer interaction mode of the graphical user interface: in response to the user dragging an asset from the asset library on the left side of the design 1 main view to the canvas area, the graphical user interface changes from the design 1 main view to the design 1 change state diagram 1 to display the AI function prompt and highlight the associated assets; in response to the user dragging the asset to the AI function prompt area in the design 1 change state diagram 1, the graphical user interface changes from the design 1 change state diagram 1 to the design 1 change state diagram 2 to expand the AI function prompt area and display the associated assets therein; in response to the user dragging the asset to a certain associated asset in the design 1 change state diagram 2, the graphical user interface changes from the design 1 change state diagram 2 to the design 1 change state diagram 3 to highlight the associated asset; in response to the user ending the dragging, the graphical user interface changes from the design 1 change state diagram 3 to the design 1 change state diagram 4 to add the asset to its associated asset; in response to the user moving the cursor out of the AI function prompt area in the design 1 change state diagram 4, the graphical user interface changes from the design 1 change state diagram 4 to the design 1 change state diagram 5 to hide the AI function prompt area. In response to the user dragging an asset from the asset library on the left side of the design 2 main view to the canvas area, the graphical user interface changes from the design 2 main view to the design 2 change state diagram 1 to display the AI function prompt and highlight the associated assets; in response to the user dragging the asset to the AI function prompt area in the design 2 change state diagram 1, the graphical user interface changes from the design 2 change state diagram 1 to the design 2 change state diagram 2 to expand the AI function prompt area and display the associated assets therein; in response to the user dragging the asset to a certain associated asset in the design 2 change state diagram 2, the graphical user interface changes from the design 2 change state diagram 2 to the design 2 change state diagram 3 to add the asset to its associated asset; in response to the user moving the cursor out of the AI function prompt area in the design 2 change state diagram 3, the graphical user interface changes from the design 2 change state diagram 3 to the design 2 change state diagram 4 to hide the AI function prompt area. In response to the user dragging a certain asset from the asset library on the left side of the design 3 main view to the canvas area, the graphical user interface changes from the design 3 main view to the design 3 change state view 1 to display the AI function prompt and highlight the associated assets; in response to the user dragging the asset to the AI function prompt area in the design 3 change state view 1, the graphical user interface changes from the design 3 change state view 1 to the design 3 change state view 2 to expand the AI function prompt area and display the associated assets therein; in response to the user dragging the asset to a certain associated asset in the design 3 change state view 2, the graphical user interface changes from the design 3 change state view 2 to the design 3 change state view 3 to add the asset to the associated asset. In response to the user dragging a certain asset from the asset library on the left side of the design 4 main view to the canvas area, the graphical user interface changes from the design 4 main view to the design 4 change state view 1 to display the AI function prompt and highlight the associated assets; in response to the user dragging the asset to the AI function prompt area in the design 4 change state view 1, the graphical user interface changes from the design 4 change state view 1 to the design 4 change state view 2 to add the asset to the associated asset. 8. Other situations needing to be explained Other explanations: The part of the graphical user interface shown by the dashed line in each view of design 1 to design 4 does not constitute the part required to be protected by the present design.

The invention provides a railway bridge digital twin system architecture design method and system, and belongs to the technical field of railway disaster prevention risk early warning technology and architecture design. System requirements are analyzed according to a system overall target, a system requirement table is formed, system function processes are deeply mined and analyzed based on the requirements, and a system function table and a database are established; constructing a data flow diagram, and converting the data flow diagram into a weighted directed graph; based on a node relation in the weighted directed graph, a system fuzzy correlation intensity matrix is calculated in a qualitative and quantitative combined mode; a system physical architecture is obtained based on mapping of a system logic architecture, and then subsystems are divided according to a fuzzy hierarchical clustering method. According to the method, the function processes are sorted out based on the requirements, the function processes are aggregated into the function domain, and the functions with close data connection are divided into one function domain, so that the internal structure of the function domain is more compact, the correlation and influence degrees among the function domains are reduced, the corresponding speed of the system is increased, and the cost is saved.

The invention relates to the technical field of data fusion, in particular to a multi-source data fusion analysis method for distributed photovoltaic aggregation prediction under a virtual power plant framework, and the method comprises the following steps: S1, deploying a meteorological sensor network, covering a main photovoltaic power station in a target area, obtaining the operation parameters of a photovoltaic inverter in real time through an SCADA system, obtaining the data of a grid-connected point, and carrying out the data fusion analysis of the grid-connected point; a power data flow diagram is constructed according to data, numerical weather prediction data, satellite cloud picture data and historical photovoltaic output data are accessed, and the space-time correlation characteristics of distributed photovoltaic output are mined by constructing a complete system of data acquisition, feature extraction, fusion modeling and prediction evaluation and utilizing a multi-source data fusion technology. Meanwhile, data localization preprocessing is achieved through edge calculation, the communication burden is reduced, a space-time diagram neural network is adopted to capture space dependence between photovoltaic power stations at different geographic positions, and prediction robustness in an uncertain scene is improved in combination with the meteorological ensemble forecasting technology.