174 results about "Branch node" patented technology

The invention discloses a power transmission line fault positioning method and system based on ground potential end transient information perception, and relates to the technical field of line fault positioning, and the method comprises the steps: obtaining a voltage traveling wave signal and a current abrupt change rate signal detected by a trunk line and branch node sensor array in a power transmission line; processing the voltage traveling wave signal and the current abrupt change rate signal to obtain traveling wave components and polarity-amplitude calibration results of different modes; according to traveling wave components and polarity-amplitude calibration results of different modes, in combination with topological parameters of the power transmission line and spatial distribution of a ground potential end sensor, adjusting edge weights or connection relationships in the graph structure to obtain a composite feature matrix and an edge weight matrix of each node; and inputting the composite feature matrix and the edge weight matrix of each node into a graph neural network positioning model, and outputting a power transmission line fault positioning result. According to the invention, through ground potential end information fusion and the dynamic graph neural network, accurate fault positioning under a complex power transmission topology is realized.

The invention relates to the technical field of database management, and discloses a hybrid memory index management method and device, equipment and a medium. Receiving an access request, providing a target index node from the cache when the access request is hit, and reading the target index node from the nonvolatile storage medium when the access request is not hit; writing branch nodes into a high-bandwidth memory cache according to node types, writing leaf nodes into a dynamic random access memory cache, and registering information; when the cache of the high-bandwidth memory meets a first trigger condition, migrating the branch node to the cache of the dynamic random access memory and updating information; and when the cache of the dynamic random access memory meets a second trigger condition, migrating the branch node to the high-bandwidth memory cache, replacing the node and updating the information. According to the method, the node residence position is dynamically adjusted by distinguishing the node types and combining the cache performance, and the index node mapping table is synchronously updated, so that the index request processing performance and the storage resource utilization efficiency are improved.

The invention relates to the technical field of network communication and video processing, in particular to an intelligent global cloud live broadcast system based on AI and multi-operator and multi-cloud optimization, and the system comprises a data collection module which is used for collecting live broadcast video streams; the video compression module adopts H.265 coding; the content review module is used for performing multi-modal review; the RPMTS packaging module is used for accessing three operator cloud private line POP nodes through a public network after packaging; the decoding module is used for decoding POP nodes in the middle area; the translation module is used for generating multi-language subtitles or dubbing; the multi-operator and multi-cloud adaptability matrix module calculates an optimal path in combination with an AI algorithm and a multi-cloud cost adaptability matrix; the multi-branch access module is used for realizing branch node cooperative forwarding; and the multi-language distribution module is used for generating multi-language subtitles and dubbles and pushing the multi-language subtitles and dubbles to each global live broadcast platform, so that synchronous distribution is realized, and the system can reduce global live broadcast delay, improve multi-language coverage capability and realize high reliability and cost optimization.

The invention provides a digital twin unmanned aerial vehicle circuit state monitoring method and system, and the method comprises the steps: firstly collecting a partial discharge pulse sequence of an unmanned aerial vehicle switching power supply circuit, separating environment electromagnetic noise through polarization filtering operation, and extracting real discharge pulses to generate partial discharge fingerprint data; inputting the fingerprint data into a pre-established fault search tree model, judging the type of a capacitor or inductor component through a first-stage branch node, and matching a degradation mode such as capacitance attenuation or magnetic saturation through a second-stage branch node to determine the fault type; then, corresponding component parameters of the equivalent circuit model are dynamically updated in the digital twin body, and the circuit operation state change trend is simulated; and finally, according to the state change trend, predicting the residual effective working time of the fault component and outputting a monitoring result. According to the invention, the accuracy of service life evaluation of key components in a complex electromagnetic environment is improved.

The invention discloses a transformer area topology identification method and device based on multi-feature fusion, and the method comprises the steps: S1, distributing an initial branch node for each user, constructing an initial topological structure identification model, and obtaining a preliminary branch node-user association relation adjacency matrix; s2, constructing a topological optimization model based on difference characteristics, and enabling the error between branch node power difference and user power difference combinations to be minimum; s3, constructing a topological optimization model based on peak-valley feature matching, and enabling the matching degree of the peak-valley feature combination of the branch node and the peak-valley feature combination of the user to be maximum; s4, constructing an optimization model based on total fitting error correction, and enabling the total error between the actual power and the fitting power of the branch node to be minimum; s5, judging whether undistributed users exist or not, if not, obtaining a final topology identification result, and otherwise, performing S1 to S4 again; according to the method, the area topology connection relation is effectively identified.

The invention relates to a broadband power grid oscillation positioning method and device based on modal analysis. The method comprises the steps of obtaining broadband oscillation data in a power grid, extracting frequency spectrum characteristics of the broadband oscillation data, identifying an oscillation mode based on the frequency spectrum characteristics, determining an oscillation positioning index of each branch node in the power grid based on the broadband oscillation data, and determining the frequency spectrum characteristics of each branch node in the power grid based on the oscillation positioning index of each branch node. And constructing a spatial-temporal feature tensor containing a time feature and a spatial feature, adding the identified oscillation mode as a tag to the spatial-temporal feature tensor, and inputting the spatial-temporal feature tensor to a trained oscillation source positioning model to obtain an oscillation source positioning result. The oscillation source positioning model is obtained by training a long short-term memory network based on a historical spatial-temporal feature tensor carrying an oscillation source position label. By adopting the method, the oscillation source can be efficiently and accurately positioned.

The invention discloses a container isolation and double-node management fused data integration governance method and system, and relates to the technical field of data integration governance. Communication time sequence data between a plurality of groups of main nodes and branch nodes of a hydropower station is monitored in real time, and deep analysis is performed by using a neural network model CNN; indexes such as data drift rate and data coverage difference can be accurately identified, and the data synchronization condition can be evaluated in real time. The accuracy of data synchronization between the nodes is promoted to be improved, and the data consistency and timeliness are ensured. By constructing the communication state model and deeply analyzing the data, the communication state can be accurately evaluated, and key communication indexes such as the uplink and downlink transmission ratio, the burst load index and the like can be identified. Once it is found that the communication state is unstable, the first governance strategy, the second governance strategy and the third governance strategy can be triggered, so that the data transmission path is optimized, the network load is adjusted, resource allocation is effectively optimized, and the overall operation efficiency of the system is improved.

The invention is suitable for the technical field of aircraft obstacle avoidance, and particularly relates to an aircraft obstacle avoidance control method and system, and the method comprises the steps: delimiting a flight region of an aircraft, collecting the stereoscopic optical remote sensing data of the flight region, drawing an obstacle recognition graph, marking the position of an obstacle, and configuring the color of the obstacle. Wherein one obstacle at least corresponds to one color, calculating the height of each obstacle, and marking the height in the obstacle identification graph; and segmenting the height into a plurality of layers, and creating branch nodes and leaf nodes. By constructing the obstacle avoidance tree, the color data of all obstacles can be visually displayed, and the color image can be quickly verified, so that the flight safety is greatly improved while the normal flight of the aircraft is ensured, the suspicious obstacles on the flight path can be verified by extracting the RGB values, the flight path planning is optimized, and the flight path planning efficiency is improved. And the flight safety is further improved.

The invention discloses a question and answer intention recognition and classification method for an infant care robot. A question rewriting node, an intention recognition node and a branch node are included. The input data of the question rewriting node are questions input by a user, the training data of the question rewriting node are phrases for mothers, infants and child rearing scenes, the model parameters of the question rewriting node are obtained through adjustment based on the training data, and the question rewriting node processes the input data according to the model parameters of the question rewriting node and outputs the data; the intention recognition node obtains data output by the problem rewriting node and recognizes a user intention and an expected result; the branch nodes provide a plurality of large language models in mother and child breeding scenes, and the branch nodes select the corresponding large language models to execute data processing according to output data of the intention recognition nodes. Original user input is clarified through standardization and rewriting, then the accuracy and response efficiency of subsequent intention recognition nodes are remarkably improved, and finally the overall user experience is improved.

The invention relates to a traveling wave device stationing and fault positioning method suitable for a load transfer operation mode, and belongs to the technical field of power system fault distance measurement. The method comprises the following steps: obtaining a branch forest in a normal operation mode based on a line topological structure; obtaining a branch forest in a load transfer operation mode according to the load transfer operation of the two connection lines; if the topological tree structures and leaf nodes of the two branch forests under the same root node change, preferentially arranging traveling wave devices at the leaf nodes appearing in the two different topological trees under the same root node, otherwise, calculating the weight coefficient of each branch in the topological tree structures, and arranging traveling wave devices at the branch nodes with high weight coefficients; when a single-phase earth fault occurs on the line, the distance between each traveling wave device and the fault point is calculated, fault section tracing is carried out, and the position of the earth fault point is determined. The objective of the invention is to solve the technical problem that the prior art cannot adapt to a new topological structure after load transfer.

The invention discloses a question answering method and device, electronic equipment and a computer program product. The method comprises the steps that a to-be-replied question is acquired, the to-be-replied question at least comprises management information and to-be-replied question data, and the management information at least comprises multiple levels of management grids for managing the to-be-replied question; in a plurality of knowledge nodes of a preset question and answer knowledge tree, a management path matched with the management information is determined, historical question data and corresponding historical reply data are pre-configured in each preset leaf node, and the management path comprises a plurality of branch nodes arranged according to the level sequence of management grids; in the at least one first leaf node, screening a target leaf node matched with the question data to be replied; and determining the historical reply data in the target leaf node as question reply data of the to-be-replied question. According to the invention, the technical problem of high computing resource consumption in a question answering mode in the prior art is solved.

The invention discloses a multi-role branch chain node state linkage management method and system, and belongs to the field of node collaborative management, and the management method comprises the following specific steps: S101, setting role nodes, adding attribute information of each role node, setting a node basic identification rule, and generating a branch chain according to an intervention approach; the method ensures that different role node numbering systems are independent and not confused, fundamentally avoids the problems of serial number repetition, vacancy or logic fracture, avoids branch structure chaos after role node upgrading, ensures that the hierarchical relationship of nodes in branches before and after conversion is coherent, avoids misadjustment of irrelevant role nodes during exception handling, and reduces system resource consumption. The state adjustment efficiency is improved, manual operation and maintenance links are reduced, manual operation errors are avoided, and meanwhile the response speed of node management and state adjustment is improved.

The invention provides an anti-registration error graph interaction remote sensing image change detection method and equipment. The method comprises the following steps: respectively extracting local texture features and a spatial dependency relationship of a dual-temporal remote sensing image through a CNN branch and a GCN branch which are arranged in parallel; the CNN features and the GCN features of the same time phase are fused, the two kinds of features are projected into graph structure representation, cross-branch node feature interaction is achieved through an attention mechanism, and fusion features are generated through gating weighting; inputting the dual-time-phase fusion features into an adaptive neighborhood graph sensing module, dynamically constructing an interactive edge relationship between cross-time-phase nodes, jointly updating edge features and node features to model a neighborhood change mode, and outputting a change feature graph; and generating a final change detection result according to the change feature map. By introducing a structure modeling capability and a dynamic message passing mechanism in the graph neural network, image registration error interference is effectively relieved, and precision, robustness and complex ground feature layout adaptability of remote sensing image change detection are remarkably improved.

The invention discloses an intention recognition processing method and device based on a learning machine and a terminal, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining request information input by a user, converting the request information into text information, and performing data cleaning to obtain cleaned text information; intention recognition analysis is carried out, and standard scene processing matching is carried out through a preset rule; meanwhile, in combination with the deep semantic understanding ability of a large language model, intelligent analysis of user intentions is carried out on the cleaned text information, a multi-dimensional optimization process is started for different analyzed branch paths, and optimized branch nodes are obtained by dynamically adjusting algorithm parameters and resource allocation; and performing context relevance check and historical behavior pattern analysis on the optimized branch nodes, generating an execution path considering both efficiency and accuracy, and obtaining an intention recognition result through the execution path. According to the intention recognition method, the expression of the user is understood by combining a large model, and the recognition accuracy is greatly improved.

The invention discloses a vehicle data query method and a related device, a cloud server is divided into a branch node and a coordination node, the coordination node does not store vehicle data and is responsible for query request verification, authority token generation and query result forwarding, and the branch node stores data and is responsible for query request verification. In the whole query process, verification permissions are not concentrated on a single node, multiple verification of identities and permissions is achieved, the whole vehicle query process is encrypted, the query result is further verified at a user side, and a set of high-security data query method is achieved.

The invention relates to the technical field of data processing, in particular to a distributed intelligent customer service database updating method, which comprises the following steps of: based on configured customer service dialogue data, matching an initial node of a fault tree; according to the customer service dialogue data corresponding to the initial node, dividing process nodes, and generating an execution state label by utilizing the rule type and the text content of each process node; based on the execution state label of the current process node, combining the rule type violation record and the branch parameter of the current process node, and generating a communication portrait corresponding to the process node; comparing the intention identification deviation between each process node and the adjacent process node by using the communication portrait of each process node, and correcting the abnormal branch node according to the branch node corresponding to the intention identification deviation; performing node association analysis on the corrected branch nodes, and adjusting the branch positions of the branch nodes in the fault tree; the efficiency and accuracy of updating the customer service database are realized.

The invention relates to the technical field of path planning, and discloses a path optimization method for multi-vehicle circulating goods taking three-dimensional boxing, a terminal and a medium. The method comprises the following steps: acquiring related data, uniformly mapping part requirements of suppliers into a box body set taking a packaging box as a unit, and determining a unit residual space opportunity cost coefficient; constructing an original model according to the related data, wherein a target function of the original model comprises vehicle driving cost, vehicle starting fixed cost and compartment remaining space opportunity cost; a Dantzigzag-Wolfe decomposition method is adopted to decompose the original model into a limiting main problem and a pricing sub-problem; iteratively solving a limitation main problem and a pricing sub-problem through a column generation algorithm; and if the solution for limiting the main problem contains a non-integer, entering a branch and bound process, repeatedly executing a column generation algorithm on branch nodes until a preset termination condition is met, and outputting an optimal circulating goods taking scheme including vehicle path planning and carriage three-dimensional boxing layout. According to the invention, the transportation efficiency of circulating goods taking can be improved.

The present invention discloses a gas pipeline network simulation and analysis system, comprising a gas pipeline network data acquisition unit, a pipeline network topology structure construction unit, a pipeline network data value influencing factor analysis unit, a gas pipeline network data prediction model construction unit, a gas pipeline network data periodicity prediction unit, a gas pipeline network data control unit, a risk warning unit, and a gas pipeline network data storage unit. The present invention realizes gas pipeline network simulation by constructing a pipeline network topology structure in a virtual environment; at the same time, it realizes periodicity prediction of gas pipeline network data through a time recurrent neural network model, compares the real data value collected on the gas pipeline network with the gas pipeline network data periodicity prediction range value, and judges the risk of the gas pipeline network. If the real data value exceeds the gas pipeline network data periodicity prediction range value, the valves on the branches and branch nodes in each component of the virtual pipeline network are adjusted to realize the real data value of the gas pipeline network exceeding the preset threshold value and control.

The invention is suitable for the field of computer vision, provides a crowd evacuation path dynamic recommendation method and system based on visual data, and discloses a crowd evacuation path dynamic recommendation method and system based on visual data in the field of computers. Crowd motion video streams are collected in real time, pedestrian head orientation vectors are extracted after preprocessing, a crowd motion velocity field is formed, and a crowd motion state database is established; constructing a visual inertia dynamic model to predict future crowd evacuation path distribution change; the real-time bearing rate of each channel is calculated, and grading early warning is generated by combining capacity threshold pre-judging saturation time; and when the channel reaches the optimal capacity threshold value, determining an upstream branch node, calculating a diversion starting time window and strength, generating a control instruction, and transmitting the control instruction to an indication execution end. Accurate dynamic path recommendation is realized, and evacuation safety and efficiency are improved.

The invention relates to the field of data access, and particularly provides an MPT-based block chain database system, a data access method, a terminal and a medium, the system comprises a native MPT storage engine used for realizing an MPT node structure in a disk and a memory, and the node structure comprises branch nodes, extension nodes and leaf nodes; the asynchronous I / O module is used for realizing non-blocking disk operation based on Linux iouring; the file system bypass module is used for supporting direct access to the block device; the versioning concurrency control module is used for realizing lock-free reading through an immutable Trie structure and atomic pointer updating; and the dynamic compression module is used for dynamically adjusting a historical data retention strategy according to the disk space utilization rate. The MPT structure storage engine is realized, basic data support is provided for a high-performance block chain system, serialization overhead is eliminated, and storage efficiency is improved.

The invention relates to the technical field of block chain storage, in particular to a data storage matching method and system for block chain evidence storage, and provides the following scheme: generating a first block chain, constructing a recommendation path tree containing a user recommendation relationship, and identifying and initializing an on-chain behavior event as a temporary branch node; and behavior verification is carried out through an on-chain self-certification declaration mechanism. If verification succeeds, the node is promoted to be a path node, a second intelligent contract completes path structure verification and treatment, an updated path recommendation tree is written into a second block chain to serve as a credible basis for data affiliation and storage, and on-chain right confirmation and dynamic excitation of a resource conversion path are achieved.

The invention discloses a functional entity code mapping method, device and equipment, a medium and a product. The method comprises the following steps: constructing a first functional entity tree of a first service system and a second functional entity tree of a second service system; according to a leaf node coding mapping relation between a first leaf node in the first functional entity tree and a second leaf node in the second functional entity tree, determining a similarity matrix between a first branch node in the first functional entity tree and a second branch node in the second functional entity tree; and determining a coding mapping relationship between the first functional entity in the first service system and the second functional entity in the second service system according to the similarity matrix. According to the method, the existing functional entity code mapping result is fully utilized, and the standardized mapping of the functional entity codes in different business systems is realized through the similarity of the functional entities in the organization architecture of the business systems, so that the manual maintenance cost is saved, and the standardized mapping efficiency of the functional entity codes is improved.

The invention provides a model training method, a communication protocol analysis method, a system, equipment and a medium. The training method comprises the following steps: acquiring original message data as training data; analyzing the original message data to obtain a corresponding discrete unit; marking model input data to obtain a corresponding protocol syntax tree, wherein the protocol syntax tree comprises a root node, branch nodes and leaf nodes; taking the model input data as input, taking the corresponding protocol syntax tree as model output data, and training the basic model to obtain an initial protocol analysis model; verifying the initial protocol analysis model based on a root node, a branch node and a leaf node of the protocol syntax tree; adjusting a corresponding initial weight coefficient in an initial loss function of the initial protocol analysis model until the initial protocol analysis model meets a preset verification condition; the initial protocol analysis model meeting the preset verification condition is used as the target protocol analysis model, so that the model can quickly adapt to different protocol types, and the analysis accuracy is greatly improved.

The embodiment of the invention provides a branch topology priority dynamic sorting and collaborative allocation method and device based on a graph neural network, node attributes and branch section connection relations are assembled into a branch topology directed graph through skeleton extraction and branch node geometric attribute calculation, and accurate expression of a tree space structure is achieved. And constructing a graph attention risk inference mechanism, fusing an intrusion distance, a growth rate and a trunk involved weight, carrying out weighted fusion to obtain a node risk score, and generating a priority ranking table according to a descending order. Double-constraint cluster task collaborative allocation is introduced, and a task allocation table is generated according to a nearest constraint and a load balancing constraint in combination with a cluster real-time position and a load state and is issued and executed, so that the defects of a traditional technology in aspects of branch topology modeling, multi-factor risk sorting, cluster collaborative scheduling and the like are effectively overcome; and a technical guarantee is provided for power transmission corridor tree barrier hidden danger disposal.

The invention relates to a service execution track tree generation method and device, computer equipment and a storage medium. The method comprises the following steps: generating a target node log set according to each target node log data; performing branch structure tiling analysis according to the service execution process branch tree to obtain first key value mapping of each service execution process branch node, obtaining a current canvas configuration tree, and performing node information analysis according to the current canvas configuration tree to obtain second key value mapping of child nodes of each parallel gateway node; the service execution process branch nodes are service execution process nodes having node branches in the service execution process branch tree; and updating the corresponding target node log data according to each first key value mapping, removing the target node log data corresponding to each second key value mapping from the target node log set, and generating a service execution track tree according to the target node log set and the current canvas configuration tree. By adopting the method, the visibility of the trajectory data and the comprehensiveness of the trajectory data can be improved.

The application provides an engine strategy data merging method and device, electronic equipment and medium, the data merging method executes a target engine strategy constructed in advance; determines the execution order of each branch node in the target engine strategy, and sequentially stacks the data of each branch node according to the execution order of the branch node; determines the execution order of each summary node in the target engine strategy, and sequentially de-stacks the data of the branch node according to the execution order of the summary node; wherein the data of the branch node corresponding to the summary node executed next is located at the top of the stack; each summary node merges the data of the summary node; in this way, the front-end data is better decoupled from the back-end data, and the algorithm of the back-end is more efficient.

The present application provides an approval process configuration method, apparatus, device and storage medium; the method includes: on the approval process management page, entering the process configuration page in response to a preset creation operation, and displaying the basic process layout corresponding to the preset creation operation on the process configuration page, wherein the process direction line in the basic process layout includes an add-type control; in response to a branch addition operation for the add-type control, creating and displaying a first branch process in parallel with the initial branch process in the basic process layout in the basic process layout, thereby obtaining the current process layout; receiving a configuration operation for at least one of a condition setting node, a basic node and a first branch node, generating and publishing target process configuration data corresponding to the current process layout, the target process configuration data being used to present and drive the corresponding target approval process on the approval terminal running the approval process. Through the present application, the flexibility and efficiency of the approval process configuration can be improved.

The invention discloses a bid evaluation method and system based on artificial intelligence, relates to the technical field of artificial intelligence, solves the problem that the text feature recognition degree is not high enough, and comprises the following steps: extracting a representative first feature and a representative second feature by locking the total number of branch nodes and the sorting relationship of branch lines of a feature map; quantifying text features from the text structure dimension; on the basis, the text similarity is calculated through difference processing and a multi-dimensional measurement space, and compared with a traditional mode based on keywords or simple text matching, the similarity between the texts can be more comprehensively and deeply mined; therefore, identification of bid invitation texts with similar contents is facilitated, repeated review is avoided, objective text comparison basis can be provided for bid evaluation personnel, subjective judgment deviation is reduced, and accuracy and fairness of bid evaluation results are improved.

The present invention belongs to the field of data processing technology, and specifically relates to a data information processing method and system based on big data. The method includes: constructing a Huffman tree based on frequency statistics of all data in the data information; obtaining a special layer in which the increase in data volume is less than the decrease in data volume when the path code from the root node to the branch node is replaced with a fixed-length code of the sequence number of the branch node in the layer; and subsequently encoding all data through the Huffman tree and the special layer. For target data corresponding to the special layer, the branch node of the leaf node corresponding to the target data in the special layer is used as a guide node, and the fixed-length code of the guide node in the special layer is spliced with the path code from the guide node to the leaf node corresponding to the target data to obtain the encoding result of the target data. The present invention improves the compression rate of the data information compression result.

Systems and methods for current limit sense compensation for self-charge bias current are described. In one embodiment, a control system for a power converter includes: a branch node coupled to receive a first current from a primary side of an energy transfer element and configured to deliver a main current and a branch current; at least one branch switch coupled to the branch node and configured to receive the branch current; a capacitor coupled to the at least one branch switch, the capacitor being configured to store electrical charge received from the branch current; a first current mirror coupled to the branch node and configured to receive the main current and produce a scaled main current; and a second current mirror coupled to the at least one branch switch and configured to receive the branch current and produce a scaled branch current. A first ratio between the main current and the scaled main current is substantially the same as a second ratio between the branch current and the scaled branch current. A scaled current mirror and adder is coupled to receive the scaled main current and the scaled branch current and configured to produce a summed current. A variable driver is coupled to the scaled current mirror and adder and configured to produce a variable drive signal in response to the summed current, wherein the variable drive signal is coupled to modulate the main current.