108 results about "Associative processing" patented technology

The invention provides a case quality intelligent evaluation method and system based on a large language model, and the method comprises the steps: building an evaluation standard library covering various cases based on a law normative file and judgment practice; designing a complete evaluation reasoning chain based on the evaluation standard library; constructing a multi-agent system based on the evaluation reasoning chain; based on the multi-agent system, realizing distributed task allocation for unplanned online tasks by applying an imprecise alternating direction multiplier method algorithm; based on the distributed task allocation result, combining planning and reinforcement learning technologies to solve a relational multi-agent case association problem; based on the multi-agent case association processing result, applying a forced zero method sparse graph technology to realize effective learning based on a case graph; and constructing a case quality assessment knowledge graph based on the effective learning result of the case graph. By adopting the technical scheme, the accuracy, comprehensiveness and efficiency of case quality evaluation are improved.

The invention provides a network security risk early warning method and system based on multi-source data fusion, and relates to the technical field of network security, and the method comprises the steps: collecting multi-source security data; performing entity identification and association processing on the multi-source security data to obtain entity association information; performing space-time alignment fusion processing on the entity association information, and constructing a threat fusion matrix; performing risk analysis and threat identification on the threat fusion matrix based on rule engine matching, a behavior anomaly detection AI model and a graph neural network; and performing graded early warning based on a risk analysis and threat identification result. According to the network security risk early warning method and system based on multi-source data fusion, the accuracy and the real-time performance of network security risk early warning are remarkably improved through multi-source data fusion and multi-dimensional analysis.

The invention discloses a multi-modal fusion bank receipt intelligent processing system and method based on vision and NLP, and the method comprises the steps: receiving a bank receipt picture or a PDF document, and completing the text detection, direction correction and character recognition through a visual processing engine; a three-level receipt independent segmentation mechanism is applied, and independent receipt records are divided through spatial clustering analysis, semantic analysis, visual verification and cross-page association processing; jointly extracting text features and layout features of each receipt through a double-flow multi-modal fusion model, and fusing the text features and the layout features; field-level data extraction is executed through a field extraction engine, and financial data verification including account number, amount, date and abnormity quadruple verification is carried out; and generating structured JSON output to obtain a bank receipt processing result. According to the invention, the innovative five-layer processing architecture realizes high-precision analysis of the bank receipts through an independently researched and developed receipt independent segmentation engine, a vision-semantic fusion model and a financial data verification system.

The invention provides a cross-domain collaborative information tracking and positioning auxiliary method and system, and the method comprises the steps: firstly collecting an original data set generated by a target event in a plurality of associated domains, carrying out the cross-domain identifier matching processing to obtain a standardized event data set, and then carrying out the information association processing of the standardized event data set, according to the method, context semantic features and cross-domain time sequence behavior features of a target event are generated, then collaborative analysis is performed on the features based on a preset collaborative analysis model, a cross-domain collaborative tracking index set is generated, and a dynamic tracking path topology is constructed according to the cross-domain collaborative tracking index set. According to the method and the device, the target event is tracked and positioned, the positioning auxiliary strategy matched with the target event is generated, and finally the positioning auxiliary strategy is synchronized to the cross-domain tracking system to activate the cooperative positioning operation, so that the cooperative processing of multi-domain information is realized, and the target event tracking and positioning accuracy and efficiency are improved.

The invention discloses an intelligent conference recording and recording method and system. According to the invention, cloud service equipment receives multi-modal information sent by edge equipment; processing the multi-modal information, and generating conference record information in combination with context sensing error correction, content segmentation, a dynamic segmentation strategy and a preset storage strategy; carrying out encryption processing on the conference record information based on the participant role information, and generating target format conference information; processing the target format conference information to generate initial conference scene mode information including a conference outline, a PPT and a mind map; processing the target format conference information and the initial conference scene mode information to generate conference information data after priority ranking and strategy processing; performing semantic analysis, feature fusion and cross-modal association processing on the conference information data to generate target conference scene mode information; and determining a target application program based on the target conference scene mode information, and sending the target format instruction information to the target application program.

The invention relates to a high-speed target detection and tracking method using infrared event information, which comprises the following steps of: performing information filtering and image noise reduction on a multi-frame accumulated image by using a high-frequency infrared event stream and a low-frequency infrared image to finish preprocessing of event and image information; and a multi-channel input deep neural network comprising a spatio-temporal information association processing module is used for reasoning to realize target detection, finally, construction of a target trajectory is completed, and target tracking is realized through a trajectory association algorithm. According to the method, static information contained in an infrared image is combined with dynamic information in an event stream, high-speed weak and small targets are detected and tracked more accurately and quickly by utilizing the advantages of the two kinds of data, the detection sensitivity and the detection frame rate of the high-speed infrared moving small targets can be improved after the method is deployed in an infrared detection system, and the detection efficiency of the high-speed infrared moving small targets is improved. The method can reduce the energy consumption of the system, and can be widely applied to an infrared detection system with limited processing resources.

The invention provides a factory production quality detection method and system based on the Internet of Things, and the method comprises the steps: carrying out the regional semantic perception association of sensor combinations in different regions, and carrying out the three-dimensional association processing of physical data through a self-adaptive transmission protocol, and obtaining a structured quality data flow; according to the structured quality data flow and the quality inspection parameters, performing differential quality inspection load balanced distribution and multi-stop collaborative reasoning on the logistics stop network to obtain semi-structured quality inspection result data; according to the quality inspection result data, topological path quality decline analysis and quality anomaly spatial-temporal clustering processing are carried out on the goods allocation and the product quality state, and a quality knowledge graph is obtained; and according to the quality knowledge graph, performing multi-dimensional quality control limit self-learning adjustment and quality early warning grading response processing on the quality inspection parameters of different goods locations and paths. According to the method, accurate traceability and rapid improvement of product quality problems are realized, and the efficiency and accuracy of quality detection are improved.

The invention discloses a system evaluation-oriented multi-source heterogeneous data association method and device. The method comprises the following steps of: acquiring a system evaluation-oriented multi-source heterogeneous data set; the multi-source heterogeneous data set comprises a multi-source heterogeneous data subset of each technical index obtained by measuring the equipment system; the multi-source heterogeneous data subset comprises a picture data sequence, a text data sequence and a test data sequence; preprocessing the multi-source heterogeneous data set to obtain a preprocessed data set; and performing heterogeneous data association processing on the preprocessed data set to obtain a multi-source heterogeneous data information set of the same equipment system.

The embodiment of the invention provides a multi-modal data processing method and system based on a knowledge graph, and aims to solve the problems of semantic association deficiency and potential association mining difficulty in multi-source information processing. The method comprises the following steps: firstly, acquiring a multi-source information set containing different expression form information units and source identifiers, and performing entity mapping on the multi-source information set and a preset semantic association network to generate an information unit set with semantic association tags; performing cross-source feature association processing to obtain a comprehensive feature set; then, a semantic reasoning rule is called for association extension, and an extension feature set is generated; and finally, based on the extended feature set, generating an information processing result conforming to an application scene and feeding back the information processing result to a corresponding interface, thereby effectively integrating multi-source information and mining potential association.

The invention discloses a project cost analysis method, electronic equipment, a readable storage medium and a program product, and relates to the technical field of project management, and the project cost analysis method comprises the steps: obtaining various types of original data of a target project in a target system to which the target project belongs; each type of original data comprises project type data, system type data and product type data; generating each associated data combination according to the data with the association relationship between every two data in each type of original data; determining the similarity between two pieces of data contained in each associated data combination, and taking each associated data combination with the similarity greater than a preset similarity threshold as each target combination; performing association processing on data contained in all the target combinations to obtain an associated data set of the target project; and analyzing the cost of the target project based on the associated data set. The analysis efficiency and the analysis accuracy of the project cost can be improved.

The invention provides an AI-based financial service product personalized recommendation generation method and system, and relates to the technical field of digital financial services, and the method comprises the steps: firstly obtaining a multi-modal financial data set comprising a user text type financial interaction record, a voice type financial consultation segment and a video type financial product explanation and watching record; carrying out cross-modal association processing on the multi-modal financial data set to obtain an association chain of text semantics, voice emotion and video concern areas, generating a user financial demand reference map containing user demand tendency and association weight based on the association chain, carrying out demand tendency enhancement processing on the user financial demand reference map, adjusting the association weight, and carrying out demand tendency enhancement processing on the user financial demand reference map; and finally, a financial service product personalized recommendation sequence sorted according to the matching degree is generated according to the enhanced user financial demand reference map, so that the user demand can be comprehensively analyzed, and the recommendation accuracy and the user satisfaction are improved.

The invention relates to the technical field of data delivery, and discloses an engineering data digital delivery method and system based on a BIM large model, and the system comprises a data collection unit, a data integration unit, an association processing unit, and a data delivery unit. According to the method, various data are collected from each related system and terminal of the project, rich contents such as a BIM model and a design drawing are covered, a complete data basis is provided for project management, and information loss is avoided; a specific conversion algorithm is adopted for data of different sources, for example, CAD drawings and the like are subjected to accurate format conversion and association, an information base is constructed with a BIM model component as a core, and data availability and management efficiency are improved; by assigning a unique identifier to the component and establishing association between multiple aspects and the component, information of each stage of the component can be conveniently traced, and engineering management is powerfully supported; by means of correlation analysis, the data value is improved, data potential relations are mined, problems are found, the scheme is optimized, and more valuable information is provided for operation and maintenance management.

The invention discloses a financial field knowledge base construction method, device and equipment. The method comprises the following steps: firstly, identifying a text region, a table region and an image region from a target image; then extracting text data of the text region by using an OCR algorithm, and extracting semantic features and visual features of the image region and a second entity set and an entity type corresponding to the table region by using a multi-modal AI model; carrying out illusion detection by utilizing the similarity of the two entity sets, and when judging that the illusion of the AI model does not trigger a fault-tolerant mechanism by utilizing a detection result, carrying out intelligent alignment processing on the two entity sets, and screening out an optimal entity matching pair; carrying out formatting verification on the entity type; and then context knowledge association processing is carried out on text data corresponding to the text region, semantic features and visual features corresponding to the image region and entity matching pairs passing verification, and a more stable and accurate knowledge base is constructed by utilizing the obtained graph structure document to represent corresponding structured knowledge.

A method for concurrently performing multiple computations in an associative processing unit (APU) includes having data in two matrices, representing data in two portions of a memory array of the APU, creating a Tartan matrix by computing an outer product between a first bit vector indicating selected rows and a second bit vector indicating selected columns, the Tartan matrix representing data stored in a third portion of the memory array wherein all cells having a value 1 in the Tartan matrix indicate selected cells, concurrently activating all cells of the matrices and storing a result of Boolean operations therebetween in one of the two matrices, wherein a new value is obtained on cells located at a same row and a same column as the selected cells in the Tartan matrix and an original value remains on other cells.

This invention belongs to the field of intelligent maritime surveillance technology, specifically a smart waterway monitoring and management system based on light beacons. It synchronously acquires multi-source heterogeneous information about vessels through integrated light beacon equipment, performs spatiotemporal registration and target association processing on this information, generates dynamic vessel trajectories, and extracts static attributes, motion behavior characteristics, visual activity characteristics, and environmental interaction characteristics. Utilizing a multi-evidence chain collaborative decision-making mechanism, it accurately identifies four fundamentally different vessel states: normal anchoring, illegal anchoring, active navigation, and uncontrolled dragging of anchor. This achieves a leap from state perception to behavioral cognition, significantly improving the accuracy of vessel anchoring identification and its robustness in complex scenarios. Based on the identification results, it triggers differentiated alarm strategies matching the state, generating handling instructions with reasons for the state determination, thereby greatly optimizing the allocation of surveillance resources and improving emergency response efficiency.

A method for calculating the N-bit square root B of a 2N-bit number X comprises: performing a multiplication of the bits b of the square root B. i Iterate starting from the most significant bit of the square root B and working your way down to the least significant bit. For each iteration, the method includes: positioning a 1 at bit b in the CHECK variable. i The bit b is determined based on the comparison of the number X with all previously found bits and a function of the previous comparison results. i shift all previously found bits in the CHECK variable right by 1 position; and i The determined value is added to its square position in the CHECK variable.

The present disclosure provides an image processing and classification method and apparatus, an electronic device, and a storage medium, wherein the method comprises: obtaining a first image selected from an image set, and a feature set stored in a storage buffer; performing a first enhancement process and a second enhancement process on the first image to obtain corresponding first enhanced images and second enhanced images; inputting the first enhanced image and the second enhanced image into a trained neural network for feature extraction to obtain first features and second features; performing association process on the first features and the second features with features in the feature set, and adjusting the neural network based on the similarity or difference between the first associated features and the second associated features obtained by the process. The loss function value in the present disclosure comprehensively considers the associated features of enhanced images with different enhancement strengths. This limitation can improve the training performance of the neural network, thereby improving the accuracy in subsequent classification applications.

A calculator for calculating a plurality of square roots includes a memory array, at least two registers, a bit subtractor, and a controller. The memory array is organized into columns and rows. The registers store a fixed value. The controller, operatively coupled to the other components, allocates a first set of rows to test variables and a second set to result variables, and initially stores each of a plurality of radicands in a separate column. For multiple iterations, the controller concurrently activates selections of rows to form current operands and current guesses for each column. The controller then instructs the bit subtractor to perform subtraction operations. For each column with a positive subtraction result, the controller selectively writes a new bit of the square root and selectively overwrites values with a new remainder derived from the subtraction result, without performing an explicit data-shifting operation.

The present invention provides a method and system for automatically associating classroom recording videos with knowledge graphs, and relates to the field of data processing technology. The present invention utilizes the rule that under normal circumstances, there must be continuous segments in a teaching video that belong to the same knowledge point or continuous knowledge points, adopts a derivation calculation starting from a point to perform forward and backward knowledge point matching, and realizes calculation from point to surface, thereby realizing the association between the entire video and the knowledge points, and the sequential relationship of the teaching knowledge conforms to the objective distribution law. In the derivation process, the knowledge point continuity rule is combined with a large model. When it is not necessary, the rule is used for association processing, and the large model is used for auxiliary judgment only when it is necessary. The setting of fixed rules reduces the amount of calculation, can achieve a great improvement in efficiency, and maintains the objectivity of the matching results and avoids the influence of hallucinations to the greatest extent.

The invention provides a maintenance fund data management method and device, equipment, a medium and a product. Relates to the technical field of data processing. The method comprises the following steps: acquiring index design demand data and maintenance fund data of a plurality of cells; determining at least three index dimensions according to the index design demand data, and determining a main body and a to-be-combined attribute of each index dimension; storing the maintenance fund data of each cell as an independent attribute table in an attribute value manner according to the main body of each index dimension and the to-be-combined attribute; obtaining user query request data, and determining a plurality of to-be-combined attributes of the at least three index dimensions according to the user query request data; generating corresponding index query conditions according to the to-be-combined attributes of the at least three index dimensions; and carrying out association processing on the attribute table of the index dimension corresponding to each to-be-combined attribute and the business process data to obtain an index result meeting the index query condition. The method has the technical effect of improving the flexibility and real-time performance of maintenance fund data processing.

The invention relates to the technical field of large language models, and discloses an intelligent geographical name and address data matching method based on a large language model, which comprises the following steps: collecting geographical name and address related data and corresponding spatial graphic data, and carrying out fusion association processing on the geographical name and address related data and the corresponding spatial graphic data to obtain processed information; carrying out textualization and vectorization conversion on the processed information to form a place name address knowledge base adaptive to a large language model; based on a place name and address knowledge base and a big language model enhanced retrieval and cue word fine tuning technology, obtaining a place name and address matching model with address hierarchy matching result evaluation; receiving a to-be-matched place name address text, performing retrieval based on the place name address knowledge base after preprocessing, and obtaining a candidate matching result set; and calling a place name and address matching model to perform hierarchical evaluation on the candidate matching result set, and outputting an optimal matching result and a matching hierarchy thereof.

The invention discloses an artificial intelligence security operation central system, and particularly relates to the technical field of network security operation management. The system comprises a data fusion layer, an intelligent analysis layer, a decision response layer and a digital twinborn layer. The data fusion layer is responsible for performing real-time receiving, standardization and association processing on the multi-source heterogeneous security data to generate a security event sequence in a unified format; the intelligent analysis layer is used for identifying security threats and detecting abnormal behaviors through a multi-mode neural network and a behavior mode analysis module; the decision response layer automatically matches a response strategy according to a dynamic risk assessment result; the digital twinborn layer constructs a system virtual mirror image and supports attack and defense deduction and strategy pre-verification. According to the system, intelligence and automation of the whole safety operation process are realized, and the threat detection precision, the response speed and the overall safety defense capability are effectively improved.

This invention relates to the technical field of robot training. Specifically, it relates to a robot adaptive training method, apparatus, and medium based on reinforcement learning. The method includes generating task sub-objective information using a high-level policy network, inputting the task sub-objective information into a low-level execution network, generating action control commands based on the task sub-objective information, collecting interaction feedback information during execution, calculating a reward value based on the interaction feedback information, associating the reward value with scene complexity parameters, performing dynamic reward shaping operations to generate an adjusted reward signal, generating a policy model optimized by meta-learning based on the adjusted reward signal, loading the policy model into a simulation environment to generate a target policy model optimized by simulation training, loading the target policy model into the robot, and controlling the robot to perform task operations in an actual interactive scenario. This invention achieves the effect of adaptive task learning for robots in multi-interaction scenarios.

The embodiment of the invention discloses a space anchor point sharing method, head-mounted display equipment and a computer readable medium. A specific implementation mode of the method comprises the steps that according to acquired space anchor point data information, space anchor point position and posture information of a to-be-generated space anchor point in a current scene is generated, and the current scene is displayed in a head-mounted display device; generating a space anchor point corresponding to the position and attitude information of the space anchor point according to the position and attitude information of the space anchor point; and in response to determining that the associated scene object included in the space anchor point data information exists in the current scene, performing association processing on the space anchor point and the associated scene object included in the space anchor point data information so as to share the space anchor point included in the space anchor point data information. According to the embodiment, synchronous movement of the shared space anchor point and the corresponding real object can be realized, and the user experience is further improved.

The application discloses a power distribution Internet of Things data real-time processing system and method based on lake warehouse integration, the system comprises an Internet of Things pre-acquisition module and a lake warehouse integration core processing module deployed by using a Docker container; the Internet of Things pre-acquisition module is used for acquiring power distribution Internet of Things data and sending the data to the lake warehouse integration core processing module; the lake warehouse integration core processing module comprises a data processing unit and a multidimensional analysis unit; the data processing unit comprises an original data processing unit, a dimension model processing unit, a fact data processing unit, an aggregation association processing unit and an application data processing unit; the application can effectively process and store massive heterogeneous data, thereby improving the confusion of data calculation analysis and statistics, reducing repeated calculation, realizing reuse of calculation results, improving the rapid retrieval efficiency of data, simultaneously providing multidimensional data support for the application side, and ensuring the response performance during large-scale complex data calculation.

The invention provides a voucher processing method which can be applied to the technical field of big data and artificial intelligence. The method comprises the following steps: based on a field mapping rule, carrying out mode mapping on preprocessed historical certificates from different service systems according to a standard field unified mode; performing multi-dimensional association processing on the historical vouchers after mode mapping and the multi-source real-time information associated with the historical vouchers to obtain a unified voucher data model; in response to the service request, preprocessing target service associated information associated with the service request, and generating a target service voucher by using the preprocessed target service associated information and the unified voucher data model; and carrying out anomaly detection on the service request by using the preprocessed feature clustering result of the historical voucher, and carrying out compliance check on the generation process of the target service voucher by using a compliance rule determined by the unified voucher data model. The invention further provides a voucher processing system, voucher processing equipment, a storage medium and a program product.

A system includes a secure, in-memory unit implemented on an associative processing unit (APU) for performing a secure similarity search. The unit implements a decryptor, a neural proxy hash encoder, an encoded vector store and a similarity searcher. The decryptor decrypts an encrypted data vector into a data vector. The neural proxy hash encoder encodes the data vector into an encoded search data vector. The encoded vector data store stores a plurality of encoded search candidate vectors and the similarity searcher performs a similarity search between an encoded search query vector and the plurality of encoded search candidate vectors.

The invention provides a priori knowledge-based earthquake disaster road damage determination method and device, belongs to the technical field of computer information processing, and solves the problems that the traditional pixel or object-based method gradually exposes strong dependence on data quality and insufficient feature expression. The method comprises the following steps: acquiring road remote sensing data of a target area within a preset target time range; preprocessing the road remote sensing data to obtain preprocessed road remote sensing data; obtaining road network vector data of the target area; performing association processing on the road network vector data to obtain buffer data; and performing extraction processing on the road remote sensing data according to the buffer area data to obtain road damage data. According to the scheme, efficient extraction of the damaged road after the disaster is achieved through the processes of dynamic buffer area generation, self-adaptive threshold segmentation and topological repair.

This invention provides a method and system for abnormal event association processing based on an operation and maintenance knowledge graph, belonging to the field of operation and maintenance management technology. The method includes: taking each abnormal event entity in a structured abnormal event sequence as an input node set; based on the topological mapping position of the input node set in a preset operation and maintenance knowledge graph, aggregating the k-order adjacency topological features and business semantic embedding features of each input node to obtain a graph event representation vector; performing pairwise comparison and temporal alignment of the feature vectors representing different abnormal event entities in the graph event representation vector; iteratively calculating the temporal lag correlation index and state transition probability matrix between each abnormal event entity; and converging to obtain a candidate abnormal event association subgraph based on the state transition probability matrix and a preset association confidence threshold. This invention realizes abnormal event association and handling instruction generation, improving operation and maintenance efficiency and the accuracy of fault root cause location.

The application relates to the technical field of data processing, in particular to a business data processing method and device, equipment and a storage medium. The method comprises the following steps: obtaining a to-be-processed data source, the to-be-processed data source comprising user information and business data; performing association processing on the business data and a data lake table based on the user information to obtain a first association result, the data lake table being used for indicating a table of label information corresponding to the business data; performing screening processing on the first association result according to a rule broadcast stream to obtain a target association result, the rule broadcast stream being used for indicating a screening rule corresponding to the business data; and determining corresponding target business data according to the target association result and performing push processing on the target business data. The method realizes real-time computing and processing of data and push processing, improves the efficiency and accuracy of real-time data processing, realizes accurate push processing of data, and provides real-time, efficient and accurate data processing services for users.