405 results about "Relational table" patented technology

The present invention relates to the technical field of algae proliferation risk prediction. Disclosed is a machine learning model-based algae proliferation risk prediction method. The present invention comprises collecting water quality data, geographic information and historical algae proliferation event data and preprocessing the collected data. In the present invention, a graph structure between monitoring points is constructed on the basis of spatial features, each monitoring point is represented as a node in a graph, and a relationship between nodes is represented as an edge, so that spatial dependency between monitoring points can be effectively captured. The weight of each edge is defined as the reciprocal of the distance between the nodes, so that the model can more accurately reflect the effect of adjacent monitoring points on each other. By constructing the graph structure to represent the relationship between the monitoring points, large-scale spatial data can be efficiently processed. A graph neural network is capable of performing a convolution operation on a graph structure, effectively aggregating information of adjacent nodes, thereby improving the spatial relationship expression capability and the model prediction accuracy.

The application provides a pollution site portrait construction method and system based on knowledge graph reasoning, which comprises the following steps: collecting key data in a pollution site investigation report; obtaining a pollution land block structured data table of each pollution land block based on the pollution site investigation report, and obtaining a knowledge graph ontology structure; integrating the pollution land block structured data table to form a pollution site structured data table; obtaining a node table, a relationship table and an attribute table of each node in the knowledge graph ontology structure to obtain a triple table; establishing a graph database based on the triple table, and performing reasoning based on the graph database to obtain known pollution information of the pollution site; performing potential risk reasoning on the triple table based on a graph neural network to obtain potential pollution information of the pollution site; and obtaining a pollution site portrait based on the known pollution information of the pollution site and the potential pollution information of the pollution site. The method of the application evaluates the pollution site based on known facts and potential risk reasoning, and improves the accuracy of the evaluation.

The invention discloses a door lock collaborative identity recognition method and system, and the method comprises the steps: obtaining a locally stored MAC-face binding relation table according to face recognition verification completed by a resident through an intelligent door lock; according to the moving path of the resident from the floor entrance to the home door lock, identity recognition is completed through cooperation of multicast communication and the home door lock, an identity confirmation result is obtained, and a directional multicast network is constructed; according to a leaving event that a resident opens a door lock from a room, triggering a passing door lock to collect leaving person information, and obtaining a leaving person identity confirmation result; and selecting to send a unicast or multicast confirmation message by the own door lock according to the completion degree of identity confirmation of the leaving person, and triggering the passing door lock to send an IGMP leaving message to the router to obtain a simplified multicast forwarding table. According to the embodiment of the invention, seamless identity cooperation of the whole process from home returning to home leaving can be realized, and the automation degree of home security and protection and the user experience are improved.

The invention relates to a full-unloading regular matching system and method based on an FPGA (Field Programmable Gate Array). The system comprises a regular rule compiling unit and an FPGA full matching unit, the regular rule compiling unit is used for receiving a regular rule set, extracting each rule fixed feature substring, compiling the uniform format isomorphic NFA, and constructing a mapping relation table of the substrings and the corresponding NFA; the FPGA full matching unit comprises a parallel high-speed character string matching engine array, a character string-NFA mapping table module, a full-quantity regular data memory, a reconfigurable general NFA engine module and a matching result output module; and the reconfiguration engine module is used for executing full unloading regular matching on the input network traffic: scanning the traffic through the engine array, screening to-be-verified traffic containing a fixed feature substring and outputting a substring identifier, querying the NFA identifier through the mapping table module, and loading NFA matching by the reconfiguration engine module. By adopting the method, low delay and high throughput performance of regular matching in a high-speed network environment can be ensured.

The invention discloses a hierarchical semantic enhanced large model zero sample learning method, which is characterized by comprising the following steps: firstly, performing semantic enhancement on category names by using a large language model to generate rich text description, and constructing a dynamic and hierarchical semantic prototype by combining original semantic information, the prototype comprising global concepts, local attributes and relation representations; secondly, extracting global semantic features and local detail features of the image by adopting a vision-language large model and convolutional neural network double-branch structure, and fusing the global semantic features and the local detail features through an attention mechanism to obtain enhanced visual representation; finally, multi-level global alignment, local alignment and relation alignment are designed and jointly optimized, accurate mapping of enhanced visual features and hierarchical semantic prototypes is achieved on multiple granularities, and classification of invisible categories is finally completed. The objective of the invention is to solve the problem of limited model generalization ability caused by insufficient semantic representation and single vision-semantic granularity in the existing zero sample learning method, and to enhance semantic representation by introducing knowledge of a large language model and innovatively implement hierarchical alignment, so that the robustness of the zero sample learning method is improved. And the recognition precision and robustness of the model in traditional and generalized zero sample learning scenes are remarkably improved.

The invention discloses an optimal control method and system for a central air conditioner. The method comprises the steps that a starting instruction is responded; selecting an operation parameter combination from a preset database and sending a test request to the central air-conditioning system; energy efficiency detection results are received, wherein the energy efficiency detection results comprise energy consumption, equipment efficiency and user thermal comfort indexes; determining a next round of test combination based on the detection result and the mapping relation table; and selecting the combination with the highest energy efficiency from the tested combinations as a final result and configuring the final result to the system. Energy efficiency self-adaptive optimization is achieved by establishing the preset database and the mapping relation table in combination with a multi-round test mechanism, the test is intelligently guided according to the divided energy efficiency value interval, blind traversal is avoided, and the search efficiency is improved. A termination test strategy is set to effectively control a period and reduce interference, a load prediction model is introduced to make optimization more targeted, energy waste caused by lagging response is avoided, key parameters are collaboratively optimized, comfort is improved, and energy consumption is reduced.

The invention discloses a fault recovery method of a storage pool, computer equipment, a storage medium and a product, and relates to the technical field of computers, and the method comprises the following steps: preferentially identifying and scanning a metadata area after the storage pool is offline, screening persistent effective metadata before offline, and storing the effective metadata in a database; metadata reconstruction is taken as a core to preferentially complete integration and restoration of a mapping relation between a logic address and a physical address instead of waiting for synchronous reconstruction of business data, so that the dilemma of long-time logic unavailability of a storage pool caused by synchronous processing of the metadata and the business data in a traditional restoration scheme is effectively broken through; according to the method, the target mapping relation table is quickly generated through conflict resolution and deletion completion processing, so that the interruption duration of the storage pool from offline to online can be remarkably shortened while the mapping accuracy is guaranteed, and the service access delay caused by unready metadata can be avoided.

The invention provides a product recommendation method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of artificial intelligence, the technical field of big data, the technical field of block chains and the technical field of privacy computing. The method comprises the following steps: acquiring structured data and unstructured data of a target user; extracting preference features based on the unstructured data, and obtaining a time sequence preference portrait by using a time sequence attention model; obtaining a target user portrait based on the time sequence preference portrait and the structured data; obtaining a multi-dimensional sequential relation graph, and reasoning the multi-dimensional sequential relation graph by using a graph neural network to obtain relation representation; executing collaborative filtering scoring based on the target user portrait and the relationship representation, and generating an intermediate product score; taking the generated intermediate product score as an input, and outputting a candidate product score based on a recommendation optimization function containing a space-time weight; and performing product recommendation based on the candidate product scores.

The invention discloses a human and house data comprehensive treatment method, system and equipment based on a multi-level address model, and a medium, belongs to the technical field of data treatment, and aims to solve the technical problem of how to effectively integrate human and house data sources of multiple parties and improve the accuracy, consistency and availability of human and house data. The defects that in the prior art, people and house data are scattered, address description is not standard, the incidence relation is inaccurate, data quality is uneven and a unified identification system is lacked are overcome. According to the technical scheme, the method comprises the steps that a five-level core data table comprising a community table, a building table, a house table, a people and house relation table and a personnel information table is constructed; the method comprises the following steps: accessing original human and house data from a plurality of data sources, performing intelligent analysis and standardization processing on address information, and obtaining data after standardization processing; establishing a house unique identification system and a human-house multi-dimensional relation model based on the standardized data; evaluating and repairing the data quality; and standardized human and house data service is provided for the outside through the data service interface.

The invention discloses an optical remote sensing ground feature relationship semantic understanding system and method in a localized environment, and the system constructs a remote sensing scene relationship analysis module, a multi-modal scene knowledge base module, a remote sensing scene graph construction module, a remote sensing scene representation module and a multi-modal sample pair construction module. Carrying out programmed modeling on the ground feature relationship by utilizing a code big language model adaptive to a domestic platform, and generating a scene graph triple; through a double-branch double-time phase comparison learning network, time sequence vision and structure knowledge are fused, and cross-modal joint representation learning is realized. According to the method, the problems of incomplete surface feature relationship expression, inaccurate modeling and lack of real-time semantics in the prior art are solved, deep optimization is carried out in the aspects of data annotation, heterogeneous computing power management and the like aiming at the localized environment, and the accuracy and integrity of semantic understanding of the surface feature relationship and the operation efficiency of the semantic understanding on a domestic software and hardware platform are remarkably improved.

The invention belongs to the technical field of cipher machines, and discloses an MCP protocol-based intelligent security service calling method, which comprises the following steps of: defining a standardized MCP message structure, and creating a mapping relation table of an MCP instruction and a cipher machine API (Application Program Interface); constructing an MCP server interface module, and receiving an MCP format request sent by the AI agent; analyzing the request to determine a password operation type; converting the operation type into a corresponding cipher machine API call based on the mapping relation table; aPI calling and transmitting parameters are sent to the server cipher machine; and receiving an operation result, packaging the operation result into a response message according to the MCP message structure, and returning the response message to the AI agent. Through a standardized message structure and a mapping mechanism, the calling process of the cipher machine is simplified, and the technical threshold is reduced; and meanwhile, seamless connection between the AI application and the cipher machine is realized through an interface module and a session management mechanism, so that the AI system can call the hardware-level cipher service on the premise of ensuring the safety.

The invention discloses a method for a substrate management controller to acquire and record hard disk positions and electronic equipment, and relates to the technical field of servers, and the method comprises the following steps: acquiring a hard disk logic view from a disk array card by establishing an out-of-band communication session, traversing each hard disk in sequence after ensuring that all hard disk positioning lamps are turned off, a mapping relation table of a hard disk logic identifier and physical slot position information is accurately established and persistently stored through an automatic closed-loop process of lighting on, querying a hard disk backboard monitoring module, recording a physical slot position and turning off, manual plugging and naked eye recognition are replaced, and automatic discovery and recording of the physical position of the hard disk are achieved; and slot position information is directly obtained through the hard disk backboard monitoring module, so that the accuracy of the corresponding relationship between logic and physical positions is ensured.

The invention provides a bridge health monitoring method and system based on Beidou grid codes, and the method comprises the following steps: S1, constructing a bridge spatial index model, generating a multi-level spatial index for a bridge structure according to a Beidou grid coding rule, and building a topological relation table of components and grids; s2, performing multi-modal data feature extraction, performing defect identification on bridge image data through a pre-trained convolutional neural network, and performing abnormal mode detection on sensor time sequence data through a long-short-term memory network; according to the invention, deep coupling of the spatial index and the intelligent algorithm is realized. According to the method, health state evaluation of adjacent areas is mutually referenced, spatial continuity is enhanced, and meanwhile, multi-scale feature aggregation is realized by utilizing a grid hierarchical structure, so that the model can capture relevance of local defects and overall structure response at the same time. In the model training process, space consistency regularization is introduced, it is ensured that evaluation results of adjacent grid units are kept reasonable and continuous, and the misjudgment rate is remarkably reduced.

The invention discloses a DCS (Distributed Control System) visualization system integrated with PLC (Programmable Logic Controller) communication, which relates to the technical field of DCS visualization systems and comprises a protocol adaptation module, a configuration analysis module, a variable mapping module, a data acquisition module, a quality evaluation module, an analysis early warning module and a visualization guide module. The protocol adaptation module is used for loading communication protocol plug-ins supporting different PLC brands, each plug-in realizes a unified communication interface specification, and a connection channel with PLC equipment is established; the configuration analysis module is used for analyzing a PLC hardware configuration file, extracting equipment address configuration information in the PLC hardware configuration file and generating structured configuration data containing equipment types, slot addresses and module parameters; and the variable mapping module is used for converting a PLC register address into a variable label with a service meaning based on physical address information in the structured configuration data in combination with a preset semantic naming rule, and establishing a mapping relation table of the address and the label.

The invention provides a grouting process dynamic control method based on statistical characteristics of a water permeability rate and a grouting amount per meter, which comprises the following steps: collecting water pressure test data (pressure P, flow Q and segment length L) and grouting process data (dry material weight M and segment length L) through a system, and calculating the water permeability rate q and the grouting amount per meter m; sorting and grouping the permeable rate data and the grouting amount data per meter, then carrying out normality test, and respectively establishing a mapping relation table between permeable rate groups and standard deviation values of the grouting amount per meter or percentile values per meter according to test results; in the grouting process, the water permeability is monitored and calculated in real time, the water permeability is matched with the mapping table, and the grout proportion is adjusted in a stepped mode according to the statistical interval where the current grouting amount per meter is located; and after grouting is finished, the grouting effect is evaluated according to the statistical interval where the final grouting amount is located. According to the method, quantitative control over the grouting process is achieved, and the problem that grout is wasted or the diffusion range is insufficient due to the fact that the proportion of the grout is adjusted through experience judgment is solved.

The invention relates to a data updating method and device, electronic equipment and a computer program product, relates to the technical field of communication, and can be applied to a dynamic data updating scene of a network function. The method comprises the following steps: receiving a network function dynamic data updating notification sent by a unified data storage function UDR, and updating a local network function group identifier and user identity mapping relation table; the network function dynamic data update notification is generated by a unified data storage function UDR when a change in the dynamic data is detected. According to the invention, after the unified data storage function UDR detects that the dynamic data is changed, the notification is sent to the consumer of the UDR, so that the consumer of the UDR updates the local network function group identifier and user identity mapping relation table, and dynamic data updating is realized.

The invention discloses a backup method and device based on NBD mapping, and relates to the technical field of system backup, and the method specifically comprises the following steps: receiving a system backup instruction; identifying protection object parameters in the system backup instruction to obtain a to-be-reconstructed disk list; in the target medium, creating a corresponding virtual disk device for each physical disk in the to-be-reconstructed disk list based on NBD mapping; based on the to-be-reconstructed disk list and the collected data of the to-be-backed-up host, performing partition table structure reconstruction on the virtual disk device to obtain a virtual disk partition device and a virtual volume device; determining a corresponding relationship between the volume on the host to be backed up and the virtual disk device, the virtual disk partition device and the virtual volume device to obtain a mapping relationship table; and determining a volume set to be backed up based on the mapping relation table. According to the method, the concurrent backup capability is enhanced, and compared with an existing system backup mode, the resource consumption can be reduced, the backup efficiency can be improved, and the data verification time can be shortened.

The invention provides a cross-database approximate nearest neighbor search method and system and a calculation framework, and the method comprises the following steps: constructing a graph index, storing the graph index in a relation table, and obtaining a graph index table; acquiring and storing a data set and a query set in a structured relation table form; the dismantling approximate nearest neighbor search process comprises a plurality of SQL operation stages including a candidate node screening stage, a neighbor expansion stage, a distance calculation stage, a result combination stage and a priority queue maintenance stage; and based on the graph index table, executing an iterative search process of the plurality of SQL operation stages on each query point in the query set, and finally outputting an approximate nearest neighbor search result of the query set. According to the method, the graph index is combined with the relational database, and the approximate nearest neighbor search is realized by adopting a plurality of SQL operation stages, so that the high-dimensional vector retrieval efficiency and the cross-database compatibility are remarkably improved, and the large-scale application of the vector data in a multi-element scene is promoted.

A sound pickup device includes a processor with hardware. The processor calculates a first relational expression between acoustic filter factors of acoustic filters applied to microphone acquisition signals acquired by two or more microphones, based on a multiplication factor at a sensitization control point with high sound pressure sensitivity by the two or more microphones and a transfer function between each of the two or more microphones and the sensitization control point. The processor calculates a second relational expression between the acoustic filter factors, based on information of a frequency of a sound source and an interval between the two or more microphones. The processor calculates each of the acoustic filter factors, based on the first relational expression and the second relational expression.

The invention relates to the technical field of text mining and data clustering, and discloses a state grid document collaborative clustering analysis method, system and device based on a graph model and a medium, comprising: constructing a joint graph model, the joint graph model comprising a document node subset and a word node subset, the edge weight between document nodes being determined based on the diversity between documents, and the word node subset being determined based on the difference between the document nodes; the edge weight between the word nodes is determined based on the diversity between the words, and the document nodes and the word nodes are not directly connected; on the basis of the joint graph model, constructing and solving a collaborative clustering target function to synchronously perform graph division on the document node subset and the word node subset so as to obtain a clustering result of the document and a clustering result of the word at the same time; wherein the collaborative clustering objective function is configured to maximize the sum of the cut value of the document sub-graph division and the cut value of the word sub-graph division. According to the method, the complex dissimilar relationship between the documents and between the words can be visually and effectively captured by utilizing the natural relationship representation capability of the graph model.

An illustrative system includes a processor configured to: determine that a first user login session and a second user login session have a parent-child relationship that indicates that a particular user is associated with both the first and second user login sessions; link first user login activity performed during the first user login session and second user login activity performed during the second user login session to the user; and identify, at least in part by using an ssh lineage table, an original login session associated with a subsequent chain of login sessions; and a memory coupled to the processor and configured to provide the processor with instructions.

The invention discloses a data preprocessing method and system for edge computing, and relates to the technical field of edge device data processing, and the method comprises the steps: determining the device state of an edge device and the data value of to-be-transmitted data, and outputting a processing capability score based on the device state and the data value through employing a pre-constructed capability perception model; outputting a processing strategy parameter through a pre-constructed strategy relation table according to the processing capability score, and associating the processing strategy parameter with the to-be-transmitted data to form a to-be-transmitted data packet; and setting an activity execution channel based on the edge device to transmit the to-be-transmitted data packet, and performing preprocessing control by using the processing parameter packet through the activity execution channel in the transmission process. According to the method, the occupation of redundant strategy parameters on transmission bandwidth and storage resources can be reduced, the data preprocessing efficiency and the resource utilization rate of edge equipment are remarkably improved, the local processing advantages of edge computing are fully played, and the requirements of accurate data processing and efficient resource utilization in an edge computing scene are better met.

The invention provides an index-based knowledge base RAG recall method and system and a medium, and the method comprises the steps: obtaining a query problem text input by a user, and vectorizing the query problem text to obtain a query vector; the similarity between the query vector and an index vector stored in an index vector library is calculated, and the index vector in the index vector library is obtained through index description vectorization generated by an intelligent index generation mechanism; selecting the index vector corresponding to the similarity meeting a preset condition as a target index vector; obtaining a mapping relation table corresponding to the index vector library, reading corresponding target document contents in a document database according to the target index vector and the mapping relation table, sorting the target document contents, constructing a context, and inputting the context into a corresponding large language model; the accuracy of the recall result of the large language model is effectively improved.

Embodiments of the present application provide a geographic position query method and device, electronic equipment and storage medium, and belong to the technical field of communication. The method comprises: obtaining a mapping relationship table; performing IP address completion and sorting on the endpoint IP address of each IP address interval to obtain a first IP address interval sequence; obtaining a to-be-queried IP address; obtaining a middle IP address in a target interval, the middle IP address divides the target interval into a sub-interval, updating the target interval with the sub-interval in which the to-be-queried IP address falls, and returning the step of obtaining the middle IP address in the target interval until the target interval does not contain the endpoint IP address of the IP address interval; in the first IP address interval sequence, determining an associated IP address interval of the target interval, and taking the geographic position corresponding to the associated IP address interval in the mapping relationship table as a queried geographic position. The embodiments of the present application can improve the efficiency and convenience of IP address searching for a corresponding geographic position, and reduce the query cost.

The invention relates to the technical field of dynamic instrumentation, in particular to a method and system for dynamically instrumenting a swan NEXT Native layer function. The method comprises the following steps: obtaining a process identifier of a target application process, and reading a corresponding memory mapping file to obtain a loading base address and a file path of a Native layer ELF shared object; an ELF file corresponding to the file path is read, and an index relation table of the target function symbol name of each item in the PLT section, the PLT item and the file offset of the PLT section is established; adding the loading base address and the file offset of the PLT section to calculate the initial address of the memory of the PLT section; and calculating the memory absolute address of the PLT entry of the target function according to the PLT entry of the to-be-intercepted function in the index relation table. According to the method, the index relationship between the symbol and the address is established by analyzing the memory mapping file and the ELF shared object file of the target process, and accurate function interception is realized at the PLT entry level.

This invention discloses a method and system for power equipment identification and information verification that integrates image semantic segmentation, relating to the fields of computer vision and data processing technology. The method includes: acquiring power equipment images and performing pre-standardization review; performing hierarchical identification on the power equipment images that have passed the pre-standardization review; matching measurement names from a measurement point-equipment-image relationship table based on image identifiers, calculating the similarity between the measurement point names and the measurement point names in the ledger records, and establishing an association between the power equipment images and the ledger records when the similarity is greater than or equal to a preset similarity threshold; comparing the hierarchical identification results with corresponding fields in the ledger records to obtain differences, and performing logical hierarchical consistency checks on the differences at the field level, cross-field level, and business level to obtain the credibility level and perform differentiated updates. This achieves high-precision automatic alignment between ledger data and on-site equipment status, reducing the cost of manual inspection and ledger verification.

This application provides an AI-based method for playing information on electronic class signs. Based on the course type, it adaptively searches for the corresponding anomaly detection distance threshold from a pre-set mapping table. It receives the pose features of multiple students wearing electronic school badges associated with the target class, transmitted within the previous first time period. The received pose features are clustered to obtain cluster center features. If the distance between any student's pose feature and the cluster center feature is greater than the anomaly detection distance threshold, a short video image containing the student is obtained. The course type and the student's short video image are input into a pre-trained model for determining abnormal classroom behavior. If abnormal behavior is detected, the electronic class sign in the classroom area displays the student's personal information and anomaly alerts.

The invention discloses a digital twinning-based steel smelting process management and control method, equipment and a medium, and relates to the technical field of industrial intelligent management and control, and the method comprises the steps: compiling a process card into an executable production path diagram, analyzing an equipment nameplate, a permission window and the process card to obtain a continuous casting grouped execution package, performing constraint embedding and decision variable setting in the executable production path diagram by using the constraint set and the optimization target parameter set, and establishing a mapping relation between the constraint set and decision variables to obtain a binding relation table; performing feasible region calculation on the executable production path diagram and the binding relation table based on the continuous casting group execution package to generate a feasible region space; constructing the optimization target parameter set and the feasible region space into a convex quadratic programming model and solving the convex quadratic programming model to obtain production configuration; according to the method, the optimal balance among the production efficiency, the energy efficiency and the carbon emission is realized by establishing a quick adjustment mechanism of feasible region calculation and production configuration.

The invention discloses a transaction detection method and device, electronic equipment, a storage medium and a program product, which are applied to the technical field of transaction detection, and the method comprises the following steps: obtaining transaction information of a current transaction; acquiring position information of a transaction subject and position information of a transaction opponent from the transaction information; under the condition that the position information of the transaction opponent cannot be obtained from the transaction information, the position information of the transaction opponent is determined based on at least one of the first mapping relation table and the second mapping relation table; based on the position information of the transaction subject and the position information of the transaction opponent, determining whether the transaction is a remote transaction; and through a real-time calculation engine, based on the transaction information and the target database, determining whether the transaction is a stranger transaction. The success rate of abnormal transaction identification is improved, and stranger transaction identification can be carried out in real time in the transaction process.

The invention provides a transaction entry method and device based on an EL expression engine and electronic equipment. Comprising the steps that a rule factor dictionary table is constructed, the rule factor dictionary table is a mapping relation table of rule conditions and transaction routing rules, and the rule conditions and the transaction routing rules are stored in the rule factor dictionary table in the form of EL expressions; obtaining transaction data of a user, determining transaction attributes of the transaction data, and determining a transaction routing rule corresponding to the transaction data by adopting an EL expression engine based on the rule factor dictionary table by taking the transaction attributes as rule factors; and based on the routing rule matching table, determining a quota management and control unit and a transaction-level account type of a transaction system corresponding to the user according to the transaction routing rule and the transaction attribute, and performing accounting processing on the transaction data according to the quota management and control unit and the transaction-level account type. The problems that business rules and codes of an existing bank transaction system are strongly coupled, new transaction types need to be developed and deployed again, and the response period is long are solved.