32 results about "Tree diagram" patented technology

The invention discloses an intelligent archive information security protection method and system, and belongs to the technical field of information security protection. The method is used for solving the technical problem that the reliability and interpretability of an algorithm for archive information security protection in an existing scheme cannot be actively supervised and optimized. Initial weight distribution of sensitive levels is realized through an analytic hierarchy process, the Bayesian network quantifies the influence degree of real-time risk factors, weights are dynamically adjusted in combination with time attenuation factors, finally, a multi-dimensional archive information security risk assessment model capable of being dynamically optimized is constructed, an explicit logic basis is provided through rule reasoning, and an archive information security risk assessment model is established. A machine learning model quantifies a risk probability and explains key features, multi-source information is fused through a D-S evidence theory, finally, a decision path is tracked through a visual tree diagram, and multi-dimensional improvement of risk identification accuracy-decision transparency-system adaptability is realized through adaptive parameter adjustment and closed-loop optimization of an abnormal response strategy.

The invention provides a photovoltaic power station intelligent monitoring system and method based on a dynamic weight tree diagram and edge-cloud collaboration, and relates to the technical field of photovoltaic power station intelligent monitoring, and the method comprises the steps: obtaining environment parameters such as illumination intensity and temperature of a photovoltaic power station, and equipment operation state data such as voltage and current; calculating and adjusting the dynamic weight of each monitoring index in real time according to the illumination / temperature deviation condition and the equipment health state; a multi-level tree diagram is constructed based on the dynamic weight, the upper layer represents the overall operation state of the power station, the lower layer represents a subsystem evaluation result, and the node priority and the hierarchical structure are synchronously updated; the edge computing node preliminarily processes abnormal data, uploads data conforming to a threshold value and adjusts a local control strategy; and the cloud platform issues optimization model parameters after deep diagnosis, and iteratively updates the dynamic weight calculation model. According to the invention, the fault false alarm rate is effectively reduced, and the fault detection precision and response efficiency of the photovoltaic power station in a complex environment are improved.

The invention provides a large-scale knowledge graph visualization method and system, and relates to the field of knowledge graph visualization. The method comprises the following steps: acquiring knowledge graph data, and clustering the knowledge graph data through a modularity-based discovery algorithm; obtaining each sub-graph corresponding to the clustered knowledge graph data, and for each sub-graph, selecting a representative node based on a PageRank algorithm or a Leader Rank algorithm; carrying out force-oriented layout on the clustered knowledge graph data through a tree diagram space filling technology; and for the knowledge graph data subjected to the force-oriented layout, distributing priorities and use times of a Barnes-Hut algorithm and a random vertex sampling algorithm according to a preset mode, and dynamically displaying a visualization result in a layered manner through an affine transformation technology. According to the method and the device, the problem that the structural expression clarity of the drawn knowledge graph is greatly reduced due to the fact that semantic clusters and hierarchical organizations in the graph are difficult to accurately present in a traditional visualization method is solved.

A text segmentation and sensitive word detection method based on matrix multiplication, comprising the following steps: obtaining an original text string and a sensitive word library; constructing a deterministic finite state automaton tree diagram of sensitive words according to the sensitive word library; converting the original text string into a text character two-dimensional matrix and recording the length of the text character two-dimensional matrix; constructing a matching two-dimensional matrix according to a horizontal matching rule, a vertical matching rule, an oblique matching rule and an inverse oblique matching rule, the length of the matching two-dimensional matrix being the same as that of the text character two-dimensional matrix; performing dot multiplication processing on the text character two-dimensional matrix and the matching two-dimensional matrix to obtain a corresponding result matrix; generating a corresponding matching text string according to the result matrix, and matching with the deterministic finite state automaton tree diagram to determine whether there is a sensitive word. The application supports interval text character information detection, improves the sensitive word detection accuracy and detection efficiency.

An information processing apparatus includes: an acquisition unit configured to acquire a plurality of tracks; a tree drawing unit configured to draw a tree diagram with the tracks as nodes; and a group editing unit configured to edit a plurality of tracks that are shared in a group including a plurality of users and are derived from a certain track in such a way that the plurality of tracks are not open to an outside of the group. The group editing unit selects one or more public tracks to be open to the outside of the group from among the plurality of tracks edited in such a way that the plurality of tracks are not open to the outside of the group, and the tree drawing unit draws the tree diagram based on the one or more public tracks selected by the group editing unit.

The invention discloses a hydraulic loading device multi-fault diagnosis method based on a decision tree algorithm. The method comprises the following steps: firstly, preprocessing imported data; secondly, for a multi-channel time sequence signal, extracting time domain statistical characteristics of each sample and each channel; then carrying out standardization processing on the extracted time domain statistical features; a decision tree algorithm is adopted, a Gini coefficient is used as a standard, optimal split features and threshold values are selected at each layer and divided, recursive growth is started from a root node, and a discrimination tree of various typical faults of the hydraulic loading device is obtained through training; after training is completed, tree nodes are traversed, and a complete discrimination path is formed from the root to each leaf; finally, the judgment path and the threshold condition are converted into a tree diagram, the relation between the features and the fault category is visually displayed, and the interpretability is improved. According to the method, feature construction, decision tree analysis and rule tree visualization are integrated for multi-channel time sequence data, and the interpretability of a diagnosis result is improved.

The present disclosure relates to a bridge information processing method, device, equipment and storage medium. The method comprises: determining a plurality of structure information corresponding to a plurality of bridge structures in the bridge, and a plurality of component positions corresponding to a plurality of bridge components in each bridge structure; for each bridge structure, generating a component identifier corresponding to each component type in the bridge structure according to the assembly information and the component detail information, and assigning the component identifier to the corresponding bridge component according to the component type and the component position; determining a plurality of component models according to the component types corresponding to a plurality of bridge components, and adding the plurality of component models to the corresponding component positions to obtain a bridge model corresponding to the bridge; establishing a component tree diagram of the bridge according to the component identifier, and associating and displaying the component tree diagram and the bridge model. Thus, the belonging relationship of the bridge components is intuitively displayed through the component tree diagram, and the unified collaborative management of information is realized.

This invention discloses a preoperative risk prediction method for cerebral aneurysms based on multimodal deep learning. To address the problems of time-consuming computational fluid dynamics simulations and difficulty in quickly obtaining individualized hemodynamic indicators, this invention reconstructs vascular geometry and a tree diagram by aligning computed tomography angiography, magnetic resonance angiography, and blood pressure and heart rate time series. It employs a graph network that satisfies Kirchhoff conservation and connects differentiable Wendt-Kessel impedance learning boundary conditions. Combining physical constraints of cardiac phase conditional neural operators, Helmholtz projection, and signed distance function boundary embedding, it approximates the flow field, calculates and closes the loop to correct wall shear stress, oscillatory shear exponent, and pressure gradient. Then, it fuses the risk features of the imaging branch, clinical branch, and text branch through expert product to output lesion-level and patient-level risks and confidence levels. This achieves the technical effect of rapidly estimating hemodynamics and performing interpretable preoperative risk assessment under physically consistent constraints.

The application discloses a network slice method based on data clustering, and comprises the following steps: firstly, a plurality of user data are acquired, the characteristics in the user data are normalized, and corresponding threshold values are set; it is judged whether the characteristic values are greater than the corresponding threshold values; if yes, 1 is assigned; if no, 0 is assigned; secondly, the characteristic frequent occurrence times of each characteristic are defined as the total times of the characteristic values being 1 in single user data, and the characteristic frequent occurrence times of each characteristic are obtained by scanning the user data; then, the minimum characteristic frequent occurrence time is set, the characteristics with the characteristic frequent occurrence times less than the minimum characteristic frequent occurrence time are deleted, and the remaining characteristics are arranged according to the characteristic frequent occurrence times; a tree diagram is constructed according to the arranged characteristics, frequent item sets are found in the tree diagram, and a normalized hypergraph is made; finally, the strong correlation between the characteristics is judged by using the obtained hypergraph, and a network slice resource allocation scheme is made. The application can reasonably, efficiently and fairly allocate the network slice resources.

To easily present information on content included in composite content.SOLUTION: The content management device includes an acquisition unit that acquires content posted by a user and system information indicating a system of a plurality of pieces of content connected in a tree shape, and a display composition unit that generates a display screen including a tree diagram visually indicating the system of the content connected in the tree shape to be displayed when the content or the composite content is distributed to the user on the basis of the system information. A content management device includes an acquisition unit that acquires content posted by a user and additional information related to the content, a statistics unit that performs statistics of the additional information for each user and outputs the additional information as performance information of the user, and a display composition unit that generates a display screen including the performance information.SELECTED DRAWING: Figure 12

This application discloses a programmable data processing method and system for multi-level users, involving power plant scheduling and data processing technologies. The method includes: constructing a tree diagram based on collected multi-source data; configuring the displayable node range for users at each user level; and dividing the displayable node range into the smallest data elements according to the tree diagram; setting default display methods and associated operations for any data element based on the semantic tag set for users with different permissions; monitoring changes in user permissions or node status to trigger corresponding decision scenarios, thereby instantiating a view within the decision scenario. The VDF is a set of data element query and assembly rules to achieve view instantiation after VDF execution. By introducing a semantic tag set, decision scenarios, and dynamic VDF execution, the method solves the problems of event flow situation awareness and the balance between permission security and user experience in existing technologies.

The invention discloses a zero-sample Chinese character recognition method based on radical structure tree graph level representation, and belongs to the technical field of Chinese character recognition. The method comprises the following steps: establishing a Chinese character database and constructing a directed radical structure tree of each Chinese character from top to bottom; adding direction position codes to nodes in the tree to distinguish the spatial relationship of brother nodes; inputting the radical structure tree with the direction and position codes into a GraphSAGE-based tree encoder to obtain normalized vector representation of the Chinese characters; extracting vector representation of the sample image by using ResNet; aligning the Chinese character vector and the image vector through comparative learning; and finally, zero sample recognition is realized by calculating the similarity between the to-be-recognized image and all candidate Chinese character vectors, and the highest similarity is selected as a recognition result. According to the method, the structure perception capability is improved through the directed tree, fine-grained spatial differences are perceived through directional coding, and the recognition capability of the model on unseen Chinese characters is effectively improved.

A method for modeling a digital power generation and transformation equipment includes the following steps: Step 1: Establishing an instantiated power plant structure model: referencing KKS coding rules and dictionaries, and automatically generating an equipment KKS coding tree based on the selected plant template; Step 2: Associating with physical equipment; Step 3: Configuring equipment information; Step 4: Configuring the tree diagram; Step 5: Determining whether to update the instantiated data based on notifications of new standards and standard changes; Step 6: Importing and exporting the power plant system equipment coding table. This invention provides a digital modeling method for power generation and transformation equipment that is open and extensible, allowing for flexible expansion based on the characteristics of different power generation and transformation equipment. It is applicable to digital model calculation and analysis fields such as power generation and transformation equipment status trend prediction and fault diagnosis.

The invention provides a method and system for automatically generating a movie script and a movie abstract, and relates to the technical field of computers. After a target movie video is obtained, a key frame set, a voice transcription text and a character action recognition result are extracted from the target movie video, a visual feature vector is extracted from the set, a scene segmentation scheme with the minimum total bit cost is searched in combination with a preset scene division principle, and the target movie video is segmented into a plurality of scenes; extracting a target actor information image from the video clip containing the actor table to generate a first corresponding relation and a second corresponding relation, and further generating a target format script and a scene list of each target scene; generating a tree diagram according to the scene, and processing to obtain a plot summary and a database; based on the target format script and the database, the story outline is generated, and the movie script and the movie abstract are generated in combination with the scene list, so that the movie script and the plot abstract which are logically coherent, rich in information and matched with the visual content are automatically generated.

The invention relates to the technical field of medical research and development, in particular to a cost-reducing and efficiency-increasing drug development scheduling system, which comprises a data classification module, a data analysis module and a development scheduling optimization module, the time sequence features and the data features are deeply fused to construct multi-dimensional distribution features, development data of the same type are judged, a distributed storage technology is adopted for classification, and a hash value is allocated to each storage node; the data analysis module performs standardized processing on different types of development data, defines the development data as standard data, and judges whether the standard data have correlation or not; the development scheduling optimization module perceives the standard data with correlation to construct a standard tree diagram; and perceiving the development tree diagram, mapping and comparing the standard tree diagram, and if difference nodes exist in the development tree diagram and the standard tree diagram, calculating the influence degree.

The invention discloses a patient multi-dimensional data similarity measurement and queue discovery method based on artificial intelligence, relates to the technical field of smart medical treatment, and solves the technical problems that an intermediate state that a patient possibly crosses multiple clusters is ignored, the queue division dimension is single, and dynamic adaptability is lacked. By extracting dynamic characteristics, such as vital signs and symptom scores, of the patient, which change along with time, the limitation of only depending on static characteristics is avoided. And patients with short-term fluctuation but long-term stability and continuous deterioration can be distinguished conveniently. And subtype typing of chronic diseases is more accurate, and a time sequence mode is a key typing basis. And the time sequence track vector and the static feature are used for similarity calculation after being spliced or subjected to dimension reduction. And the single feature noise influence is reduced. Disease generality and individual heterogeneity are considered. Aggregate hierarchical clustering is adopted, similarity among samples is calculated, similar clusters are gradually combined, a tree diagram is generated, and patient grouping logic and correlation and causality distinguishing are visually displayed through a clustering tree.

This invention discloses a method, system, and apparatus for decomposing project information management work packages, relating to the field of project information management technology. The method includes: constructing a first tree diagram based on enterprise hierarchical structure data; constructing a second tree diagram based on project organizational structure data; obtaining preset project identifiers and a third tree diagram based on preset project basic information; generating task work packages based on the third tree diagram; assigning preset projects to preset units based on preset identifiers; setting data pools for each level of the third tree diagram; setting tag data for personnel based on preset unit personnel basic information and assigning it to the data pools; configuring corresponding personnel for each node based on the data pools and tag data; configuring task work packages and setting preset permissions for each node; storing data from the third tree diagram into nodes of the first tree diagram, thus completing the dynamic decomposition of task work packages. This invention significantly improves the management efficiency of multi-level enterprises for technological innovation projects.

The invention discloses a user-to-main transformer load convergence method and system based on a multi-level tree diagram. The method comprises the following steps of: acquiring a topological structure and related ledger and power data of each level of equipment from a user to a 220kV main transformer of a power grid as initial data; constructing a power grid topology tree diagram with a 220kV main root and a user leaf, calculating a load convergence value and a deviation rate of each node, and marking convergence participation conditions; and judging whether the deviation rate of the 220kV main transformer is normal or not based on a set threshold value. And if the abnormal main transformer lower-layer equipment is abnormal, marking a deviation label for the abnormal main transformer lower-layer equipment, analyzing a transaction data set by using an FPGrowth algorithm to find out an associated frequent item set, determining a problem topology layer through the maximum confidence coefficient, and carrying out optimization adjustment on the layer to correct load convergence. By implementing the method provided by the invention, hierarchical topology information can be effectively integrated, and refined load analysis and prediction are supported, so that the operation performance of the power distribution network is improved.

The embodiment of the application discloses a SysML diagram implementation method and device, the method comprises the following steps: dividing information in each SysML diagram into graphical element information, logical relationship information and element attribute information, wherein the graphical element information comprises an outer frame of the diagram; generating a tree diagram for storing SysML diagram information according to the graphical element information, the logical relationship information and the element attribute information, wherein the top node of the tree diagram corresponds to the outer frame of the diagram, the top node is associated with a first node and a second node, the first node is used for associating a graphical element node, the second node is used for associating a logical relationship node, the child node of the graphical element node is determined according to the corresponding logical relationship node of the graphical element node, and each node in the tree diagram stores element attribute information corresponding to the node. The application can effectively fuse the MBSE and the document-based method.

The invention provides a context semantic consistency control method and device supporting user correction, computer equipment and a storage medium. The method comprises the steps of obtaining a source interaction data tree and a context view tree corresponding to a current dialogue event flow; displaying the first tree diagram and the second tree diagram in a visual interface; based on the source interaction data tree and the context view tree, determining a semantic drift score of each interaction node, and determining whether a target interaction node exists; if so, highlighting the target interaction node in the context view tree; and in response to a processing operation of a user for the target interaction node, updating the source interaction data tree and the context view tree to update the first tree diagram and the second tree diagram, and returning to execute the step of determining the semantic drift score of each interaction node based on the source interaction data tree and the context view tree until the target interaction node does not exist. By adopting the method, the semantic distortion condition after the context content of the large language model is compressed can be reduced.

The invention discloses a data storage method applied to a block chain, a data access verification method and equipment, and is applied to the technical field of block chains. Processing the to-be-stored data according to the key information to obtain an encrypted data set and a binary addition tree diagram; and determining adder tree storage proof information based on the binary addition tree diagram, the encrypted data set and the user identification information, and performing uplink storage. The data access verification method comprises the steps that after a data access verification request is received, adder tree storage certification information and historical random path spot check space-time certification information are called; obtaining a second random number, processing the second random number according to the additive tree storage proof information or the historical random path spot check space-time proof information, and generating random path spot check space-time proof information; and the data state information is determined according to the random path spot check space-time proof information, so that data storage and access verification processing are realized, the computing resource consumption is reduced, and the deployment flexibility is improved.

This application provides a method and apparatus for visualizing query interpretation analysis results. The method includes: obtaining the text-based interpretation analysis results corresponding to a target query statement; determining, from the interpretation analysis results, multiple query nodes constituting the query plan corresponding to the target query statement, the dependencies between the multiple query nodes, and various query metrics corresponding to each of the multiple query nodes. Based on the dependencies between the multiple query nodes, displaying a tree diagram corresponding to the query plan on the target interface, and binding the multiple query metrics corresponding to each of the multiple query nodes to the tree diagram, thereby realizing the visual display of the query plan and the binding display of query nodes and query metrics in the visualization results.

The invention relates to the technical field of image generation, in particular to a decision tree visualization method and device, equipment and a storage medium, and the method comprises the steps: constructing a node tree based on the data of each original node of the decision tree; determining a tree node attribute of each tree node in the node tree to obtain tree node attribute information; the tree node attributes at least comprise a tree node hierarchy, a father node, a relation with the father node, a same-hierarchy serial number, a child node and tree node data; determining a node layout of each tree node based on the tree node attribute information and preset picture height parameters and picture width parameters to obtain node layout information; and rendering the node layout information to obtain a decision tree target tree diagram. According to the invention, the generation efficiency of the visual decision tree is improved.

The application discloses a legal label system-based document marking method and relates to the technical field of document marking. The technical problem of slow legal label marking efficiency of overall documents and easy mislabeling is solved. The obtained to-be-compared tree diagram is processed, uniform marking processing is performed on the extracted several color-labeled sentences, the common labels of the first classification are converted in a numerical conversion manner, the common labels of the original text are converted and color-identified, in the subsequent operation process, the corresponding common labels can be quickly found, the sentences with the common labels are directly extracted, the legal labels existing in the sentences are analyzed and marked, the accuracy of the legal label marking can be ensured, the efficiency of the legal label marking can be ensured, the marking processing can be quickly completed, and the timeliness is improved.

Embodiments of the present disclosure provide a data processing method, device, equipment, readable storage medium and product, the method comprising: obtaining at least one to be shunted data information and to be shunted calculation proportion information; generating at least one shunting rule tree diagram according to to be shunted calculation proportion information and preset configuration proportion; for each node in the shunting rule tree diagram, obtaining shunted data according to the storage location corresponding to the identification information of the shunting node corresponding to the node, and performing data shunting calculation on the shunted data according to the shunting proportion and the configuration proportion; generating a shunting result model according to the shunting result corresponding to each shunting node. Thus, data shunting calculation can be automatically performed on the nodes in the shunting rule tree diagram, without the need for encoding operation according to the calculation task. By generating a shunting result model according to the shunting result, based on the tree structure of the shunting rule tree diagram, the abnormal calculation node can be quickly located when a problem occurs in the shunting result subsequently.

This application provides a method and system for automatically generating movie scripts and movie summaries, relating to the field of computer technology. After acquiring a target movie video, it extracts a set of keyframes, speech-transcribed text, and character action recognition results. Visual feature vectors are then extracted from this set. Based on preset scene segmentation principles, a scene segmentation scheme with the lowest total bit cost is searched to divide the target movie video into multiple scenes. Target actor information images are extracted from video clips containing cast and crew information to generate a first correspondence and a second correspondence, thereby generating a target format script and scene list for each target scene. A tree diagram is generated based on the scenes, and after processing, a plot summary and database are obtained. Based on the target format script and database, a story outline is generated, and combined with the scene list, a movie script and movie summary are generated. This achieves the automatic generation of logically coherent, information-rich movie scripts and plot summaries that match the visual content.

The invention provides a circuit breaker fault analysis method and system based on big data. The method comprises the steps of obtaining a preset circuit breaker fault causal knowledge graph; performing standardization processing on the operation condition data and the environment monitoring data; extracting depth time sequence characteristics of the fault recording data; splicing the depth time sequence features with the operation condition data and the environment monitoring data after standardization processing, and constructing a multi-source heterogeneous feature vector; initializing each multi-source heterogeneous feature vector into an independent cluster; when the distance between any two clusters is calculated, a space-time correlation weighted mahalanobis distance is adopted; when the cluster pairs are iteratively merged, the cluster pair with the minimum comprehensive cost value is selected according to the merging criterion; after the merging process is repeated to generate a clustering tree diagram, the tree diagram is cut within a preset cluster number range, and a comprehensive evaluation index is calculated for each segmentation scheme; and taking a cluster set corresponding to the segmentation scheme with the optimal comprehensive evaluation index as a circuit breaker fault mode classification result.

The invention discloses an electric power data quality evaluation method and system based on artificial intelligence analysis, and belongs to the technical field of data processing. The system comprises a data acquisition module, an anomaly analysis module, a scheme setting module and a quality evaluation module. The data acquisition module is used for acquiring historical records, environmental parameters, electric power parameters, a project library and a relation set; the anomaly analysis module calculates a deviation coefficient of the electric power parameters according to historical records, analyzes a relation set to establish a relation tree diagram and a relation chain, and calculates anomaly indexes of the electric power parameters in combination with the deviation coefficient so as to set anomaly parameters; the scheme setting module marks evaluation items in the item library according to the abnormal parameters, and establishes different pre-selected schemes; analyzing the marked evaluation items contained in the pre-selected scheme, calculating a priority coefficient and setting a fixed selection scheme; and the quality evaluation module executes the fixed selection scheme, performs artificial intelligence analysis and summarization on execution results of all the marked evaluation items, generates a power data quality evaluation report and pushes the report to an intelligent terminal of a manager.

The present application relates to the technical field of water quality information monitoring, in particular to a water quality monitoring method, system and device for environmental protection. The method uses the hierarchical clustering algorithm, clusters the monitoring nodes based on the pollution degree difference between the monitoring nodes, obtains the tree diagram, and then segments the tree diagram to obtain the combination of the clustering clusters of each segmentation. For each segmentation, the representative nodes are selected based on the pollution degree difference between the nodes, the distribution of the representative nodes in the drainage pipe network is combined, and the feature saliency of the representative nodes obtained by the current segmentation is evaluated according to the influence degree of the key area to obtain the reasonable degree, select the optimal segmentation process and determine the key monitoring nodes. The present application is based on the hierarchical clustering algorithm, can determine the feature salient key monitoring node position based on the dynamic characteristics of the current drainage pipe network water area, and can extract the effective pollution information in the current drainage pipe network based on the key monitoring node position.

The invention discloses a CTC graph data updating and checking method based on a tree diagram mapping mechanism, and the method comprises the steps: S1, inputting a new CTC station graph and an old CTC station graph, and obtaining the station graph object information in batches based on the new CTC station graph and the old CTC station graph; s2, constructing a tree diagram model corresponding to the CAD station diagram, carding the association relationship of station diagram objects by using a hierarchical structure, and converting scattered object data into a comparable structured model; s3, drawing a tree diagram corresponding to the CTC station based on the station diagram object information obtained in batches and the constructed tree diagram model; s4, automatically calculating and comparing tree diagrams mapped by the new CAD drawing data and the old CAD drawing data so as to compare tree diagram structures to finish checking of station drawing updating objects; and S5, counting and generating a new and old CAD graph data comparison report based on the check result of the station graph update object. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium.