390 results about "Information resource" patented technology

The invention provides an industrial chain atlas modeling method and system based on deep learning, and relates to the technical field of industrial chain analysis and modeling, and the method comprises the steps: collecting multi-source heterogeneous data in an industrial chain, including demand information, resource states, process features and operation and maintenance data, and preprocessing the multi-source heterogeneous data to form a standardized data set; and performing semantic vectorization processing on the text type data in the standardized data set, and performing node embedding on the multi-relation graph to generate entity low-dimensional representation fusing text and structural features. According to the method, by integrating multi-source heterogeneous data, fusing text and structural features, constructing an industrial chain knowledge graph and performing dynamic optimization, accurate adjustment of production line configuration and task allocation strategies is realized, meanwhile, the industrial trend is effectively predicted, risk paths are analyzed and resource bottlenecks are identified in combination with a risk propagation model, a scientific basis is provided for industrial chain decision-making, and the risk propagation model has a wide application prospect. And the operation efficiency and stability of an industrial chain are improved.

The invention relates to the technical field of information resource fusion management, and particularly discloses a fusion and management system for multi-source heterogeneous science and technology information resources. Analyzing an equipment fault chain from an unstructured text of a historical operation and maintenance log, extracting a rated parameter constraint from a structured table of an equipment manual, and collecting an operation feature vector from a real-time sensing data stream to generate a knowledge graph containing N entity relationships; based on an entity attribute constraint rule of the knowledge graph, designing a bidirectional attention mapping network to calculate semantic similarity weights of multi-source data and knowledge nodes, and generating a graph embedding vector set with weight marks through Hadamard product operation; according to the method, the embedded vector set is input into the pre-trained graph neural network model, and the root cause equipment set causing feature offset is positioned, so that efficient fault diagnosis and positioning are realized, decision support is provided for a subsequent preventive maintenance strategy, and the reliability and the operation and maintenance efficiency of the system are improved.

The invention provides an information resource demand prediction method and system based on a user behavior pattern, and the method comprises the steps: firstly obtaining a user behavior data set of a target user in a preset time period, and enabling the user behavior data set to comprise a plurality of behavior event units composed of user operation types, operation timestamps and associated resource identifiers; performing behavior feature extraction on the user behavior data set to obtain an operation intensity feature, a time distribution feature and a context association feature, and inputting the operation intensity feature, the time distribution feature and the context association feature into a pre-trained demand prediction model to generate a resource demand prediction set; according to the method, priority ranking is carried out according to the feature weights of the resource demand items in the resource demand prediction set, a resource allocation optimization strategy is generated, and finally, the resource allocation optimization strategy is sent to a resource scheduling system to trigger a resource preloading operation, so that the accuracy and efficiency of information resource allocation can be improved.

The invention discloses an information resource efficient collaborative optimization method for a distributed computer system, which belongs to the technical field of information resource optimization control and comprises the following steps: executing a transaction according to a target lock element information set, monitoring popularity information of each resource segment, generating self-adaptive lock granularity decision information of each resource segment, and executing dynamic adjustment of lock granularity. And obtaining load sensing optimization parameters to complete lock competition optimization, and completing real-time iterative updating of lock element information and strategies. According to the method, the problems of resource competition and deadlock in the distributed system can be effectively solved, and the system performance and the resource utilization efficiency are improved. Transaction pre-allocation resources are reasonably allocated, the deadlock risk is reduced, lock granularity is dynamically adjusted according to resource segmentation popularity, lock competition optimization is completed based on load awareness optimization parameters, an adjustment result and the optimization parameters are synchronized to a distributed lock management library for real-time iteration updating, and it is ensured that a system always operates with an optimal strategy; and the distributed computer system efficiently and stably processes information resources in a cooperative manner.

The invention provides an information resource distribution method and system applied to a dynamic network environment, and the method comprises the steps: firstly obtaining a real-time state feature set of a target distribution network, determining a resource distribution constraint condition set in a current network environment based on the real-time state feature set, carrying out the priority analysis of a real-time resource request sequence of a target user group, and obtaining a real-time resource distribution constraint condition set; obtaining resource timeliness grade distribution and a request path optimization feature set, generating a dynamic distribution strategy parameter set matched with a resource distribution constraint condition, triggering a resource redirection operation, and enabling the resource request response rate of the target user group to be improved to a preset threshold interval; and the information resource distribution efficiency and stability in the dynamic network are improved.

The invention provides a local cache resource optimization method and system combined with a node state, and relates to the technical field of cloud storage optimizing.The method comprises the steps that firstly, a state index set, including indexes such as resource use, security levels, survivability and transmission cost, of multiple nodes in a distributed network is obtained; calculating a target cache value of the current node to the target information resource according to the target cache value, generating a local cache decision parameter after correction of a dynamic adjustment factor, if the local cache decision parameter exceeds a node cache trigger threshold value, storing the target information resource into a local cache of the current node and generating a cache resource distribution update instruction, and updating the cache resource distribution update instruction. And adjusting the adjacent node cache synchronization strategy according to the cache resource distribution updating instruction, thereby realizing the cooperative operation of the cache resources, and improving the resource utilization rate and access efficiency of the distributed network.

The invention provides an information resource matching recommendation method and system based on context awareness, and the method comprises the steps: firstly obtaining a context data set which is generated by real-time interaction of a target user and comprises user operation behavior data and scene awareness parameter data, and then carrying out the demand feature extraction of the context data set, the method comprises the following steps: acquiring a dynamic demand feature and a context association feature, matching the dynamic demand feature and the context association feature with a pre-stored information resource library to generate a real-time information resource matching result set, and optimizing a matching strategy of a target user matching model in real time according to a dynamic feedback parameter of the real-time information resource matching result set. According to the method, a resource matching strategy is optimized to obtain an optimized resource matching strategy, and finally, a target information resource set related to the dynamic demand characteristics is pushed to a target user terminal device based on the optimized resource matching strategy, so that more accurate and personalized information resource recommendation can be realized, and the recommendation quality and the efficiency of obtaining effective information by a user are improved.

The invention provides a potential information identification method and system in combination with a heterogeneous network environment, and the method comprises the steps: firstly obtaining a heterogeneous network environment data set of a target network environment, which comprises original information resources of various data formats, and carrying out the feature extraction of the heterogeneous network environment data set to obtain an associated feature set; performing hierarchical pattern matching processing on the associated feature set based on a pre-trained information pattern analysis model to generate a potential information identification result set containing significant value information resource attribute identifiers and distribution paths, and generating a dynamic resource integration strategy according to the potential information identification result set; and the resource management system is used for adjusting a resource scheduling rule and a storage path mapping relation, finally feeding back a dynamic resource integration strategy to the data management system, triggering a resource directory updating operation, and improving heterogeneous network resource utilization and management efficiency.

The invention relates to the technical field of information processing, and discloses a big data-based information matching management system, which comprises an acquisition module, an attribute analysis module, a multi-dimensional modeling module and a dynamic matching module. The acquisition module acquires a user behavior data set and extracts active information demand features; the attribute analysis module analyzes the real-time updating frequency, the semantic association degree, the historical matching success rate and the data topological structure characteristics of the target information resources; a multi-dimensional modeling module performs heterogeneous modeling on each feature to generate timeliness, semantic association, matching probability feature vectors and topological structure vectors; and the dynamic matching module generates an adaptation degree score and determines an optimal matching object through heterogeneous space projection and feature coupling operation. The system improves the accuracy, real-time performance and efficiency of information matching through multi-dimensional feature processing, topological structure analysis and a dynamic matching algorithm, and is suitable for an accurate information matching scene in a big data environment.

This application discloses a resource indication method, a terminal, and a network-side device, pertaining to the communications field. The resource indication method of embodiments of this application includes: sending, by a first terminal, sidelink control information according to a numbering rule of sub-channels and / or resource groups, where the numbering rule of sub-channels and / or resource groups includes a mapping rule between sub-channels and interlaces, the sidelink control information includes resource indication information, and the resource indication information is used to indicate resources occupied and / or reserved by the first terminal.

Embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of resource allocation for time-division or frequency-division duplexing communication. The method comprising: receiving, at a first device and from a second device, first configuration information indicating a set of resources for time-division or frequency-division duplexing communication between the first device and the second device, the set of resources comprising a first subset of the resources for uplink transmission; and receiving, from the second device, second configuration information indicating at least one second subset of the resources for the uplink transmission, the at least one second subset of the resources comprising at least one resource other than the first subset of the resources.

The invention relates to the technical field of artificial intelligence, in particular to an intelligent question answering method and device for knowledge in the power production field, equipment and a medium, and the method comprises the steps: carrying out semantic partitioning and vectorization embedding on a knowledge base document, forming a data set and a vector set in the power production field, and obtaining a knowledge problem about the power production field inquired by a user; respectively executing vector retrieval and keyword retrieval on the data set and the vector set according to a knowledge problem about the power production field inquired by a user to obtain a multi-path retrieval recall result; and fusing multi-path retrieval recall results to obtain similarity scores Top T vector document blocks to form a candidate set, inputting the vectorized knowledge questions and the vector document block candidate set into a large model, and generating question and answer results of the knowledge questions by the large model. Therefore, the problems that diversified information resources are difficult to fully utilize due to the adoption of a single retrieval path in related technologies, and processing limitation on timeliness and multi-modal data is caused are solved.

The invention provides an information resource multi-level data recovery method and system and a medium, and the method comprises the steps: generating a snapshot header for each snapshot, which comprises a snapshot ID, a previous snapshot hash value, a current snapshot hash value and an optional digital signature; meanwhile, hash calculation is carried out on all the blocks in the snapshot, and a Merkel tree is constructed to obtain a global hash value; when a new or updated block is detected, carrying out Hash calculation on the new or updated block, adding the new or updated block into a Merkel tree, generating a new snapshot Hash value, and writing the new snapshot Hash value into a snapshot head; and taking the hash value of the previous snapshot as a predecessor reference of the new snapshot to form chained association. In a multi-copy environment, when data recovery needs to be carried out, firstly, related snapshots are screened and determined through a snapshot index and a filter; then verifying the snapshot chain to ensure that the front and back references of each snapshot are correctly matched with the Merkel tree hash value; for block-level data, if copies are inconsistent, a correct version is discriminated through weighted consensus; and finally reconstructing the damaged block.

The invention relates to an intelligent city sweeper operation monitoring management method and system. The method comprises the following steps: carrying out multi-source data acquisition processing on vehicle operation data of a cleaning vehicle to obtain a state fusion data set for representing operation behavior characteristics of the cleaning vehicle; according to a matching relationship between a preset standard operation template and the state fusion data set, performing hierarchical analysis processing on the operation behavior characteristics of the sweeping vehicle to obtain an operation behavior evaluation result; according to the operation behavior evaluation result, a matched monitoring feedback strategy is executed on the sweeping vehicle, an operation monitoring feedback information set is generated, and the operation monitoring feedback information set comprises operation abnormity alarm information, track deviation labeling information, resource allocation suggestion information and state diagnosis result information; the method is used for providing operation scheduling management basis for the sweeping vehicle for the preset monitoring platform. By adopting the method, fine identification and efficient management of the operation state of the sweeping vehicle can be realized.

The invention provides a file auditing method, device and equipment based on a multi-modal large model, and the method comprises the steps: splitting data in a to-be-audited file, and obtaining text data in the to-be-audited file and image data in the to-be-audited file; segmenting the file to be audited to obtain a plurality of text paragraphs; based on a pre-constructed cue word template, guiding the multi-modal large model to identify texts in the image data, calling a knowledge base to verify text contents identified in the image data, guiding the multi-modal large model to determine themes of all text paragraphs, and indexing in the knowledge base according to the paragraph themes, and the plurality of text paragraphs are verified based on the index result, so that the automatic auditing process of the to-be-audited file is realized, and the file auditing efficiency and accuracy are improved. The powerful processing capability of the multi-modal large model and the rich information resources of the knowledge base are fully utilized, and powerful technical support is provided for file auditing.

An information transmission method and device, in the information transmission method, a first device determines resource demand information, the resource demand information is used for indicating a demand of the first device for a required BM resource, and the resource demand information comprises one or more of the following items: a real-time demand, a pooling demand, a sharing demand, a security demand, and a mobility demand. And the first device sends the resource demand information to the second device. And the second device allocates the BM resource satisfying the resource demand information to the BM resource instance. Therefore, the BM resource allocated by the second device for the BM resource instance meets the requirement of the first device for the BM resource. Wherein the demand indicated by the resource demand information can be the demand of the telecommunication cloud application for the BM resource, so that the method is beneficial for the second equipment to deploy the BM resource instance matched with the differentiated demand of the telecommunication cloud application for the BM resource.

The invention discloses a deep search method and device, equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: employing a planning agent to decompose a currently input preprocessing problem into a plurality of sub-problems; screening and analyzing from an external knowledge base by adopting a search agent according to the characteristics of each sub-problem, and gradually extracting corresponding effective information; and integrating the extracted effective information to generate an answer corresponding to the pre-processing question. In this way, preprocessing problems are decomposed through the planning agent and the searching agent, screening and analysis are carried out from an external knowledge base to gradually extract corresponding effective information, then the extracted effective information is integrated, and therefore the problems can be managed more easily; in addition, it can be ensured that each sub-question can be fully concerned and accurately answered, the information retrieval efficiency is improved, and scattered information resources are effectively integrated, so that accurate and timely replies can be generated, and the reply quality and accuracy are ensured.

The invention discloses a scene generation method and device based on multi-source GIS data fusion, and relates to the technical field of digital twinning and programmed generation. The method comprises the following steps: acquiring GIS data, preprocessing the GIS data, and storing the preprocessed GIS data in a geographic information resource library; a structured resource library is constructed, semantic parameters are added to the three-dimensional model in the structured resource library through the configuration file, and three-dimensional model resources with structured semantics are constructed; on the basis of the three-dimensional model resources with structured semantics and GIS data in a geographic information resource library, building and road generation and terrain processing are carried out in a programmed modeling engine through a configuration file, and scene data are generated; and importing the generated scene data into a real-time rendering engine, carrying out dynamic environment interaction and biocenosis simulation, and generating a city scene. The problems that in the prior art, an urban three-dimensional modeling method is low in efficiency and insufficient in environment interaction reality sense are solved.

The invention discloses an information system operation intelligent control system, and relates to the field of information operation management, and the system comprises an information operation intelligent management platform which is provided with an information collection module, an information monitoring and processing module, an information intelligent analysis module, an information intelligent scheduling module and an information intelligent management and control module; the information acquisition module is used for acquiring working data information and path operation state data; the information monitoring and processing module is used for acquiring real-time flow network state data and a corresponding real-time information flow network according to the acquired data; the information intelligent analysis module is used for judging whether the corresponding flow network nodes are abnormal or not, and performing abnormal marking according to a judgment result; the information intelligent scheduling module is used for processing abnormal flowing network nodes and generating information resource scheduling information; the information intelligent management and control module is used for managing and controlling the corresponding flow network nodes according to the information resource scheduling information; according to the invention, the accuracy of the information system in the control process is improved.

The invention provides a resource leakage point positioning method, electronic equipment and a storage medium, and relates to the technical field of terminals. In the method, in a service process, when a service thread calls a resource application interface to apply for resources, corresponding resource calling information is obtained, and the resource calling information comprises function stack memory information and register information corresponding to the resource application interface; the business process comprises one or more business threads; according to the technical scheme, the target thread is newly added in the business process, the stack return is carried out on the nat ive layer based on the function stack memory information and the register information, and the backtracking from the nat ive layer to the java layer is not needed during the stack return, so that the performance overhead and the resource consumption caused by the stack return are reduced, and the technical effect of improving the positioning efficiency of the resource leakage point is realized.

Systems and methods are provided for processing prompts to a large language model based on a corresponding intent of a received prompt. The systems and methods select, based on determined corresponding intents, from a plurality of information resource engines to process the received prompts.

The invention provides an LLM model resource allocation method and device under a GPU cluster based on mixed integer programming, and relates to the technical field of computers.The method comprises the steps that a computing resource allocation request of a user is received, and resource demand information and a budget upper limit of at least one LLM model are determined based on the computing resource allocation request; obtaining available resource information of the GPU cluster; wherein the GPU cluster comprises a plurality of heterogeneous GPUs; using the available resource information, the resource demand information and the budget upper limit as input of a pre-constructed resource allocation model, solving decision variables of the resource allocation model through a prepared optimization mode, and obtaining a target allocation scheme; a resource allocation model is constructed based on a mixed integer programming algorithm framework; and carrying out computing resource allocation on the at least one LLM model based on the target allocation scheme. According to the scheme, the globally optimal target allocation scheme can be obtained by utilizing the resource allocation model, and the resource utilization rate is improved by utilizing the target allocation scheme to perform computing resource allocation.

The present application relates to the technical field of communications, and discloses a PRACH resource determination method, a PRACH resource indication method, an apparatus, a terminal, and a network side device. The PRACH resource determination method in embodiments of the present application comprises: a terminal acquires first information; and the terminal determines a PRACH resource on the basis of the first information, wherein the first information indicates at least one of the following: configuration or reconfiguration information of the PRACH resource, update information of the PRACH resource, and time-frequency domain information of the PRACH resource.

According to the retrieval enhancement generation method and equipment provided by the embodiment of the invention, the plurality of preset dimensions for performing multi-view evaluation on the retrieved information resources are pre-configured, the dimension score of each information resource for each preset dimension is determined, and multi-dimensional comprehensive evaluation is performed on the information resources based on the dimension score of each preset dimension. Determining a target information resource; and based on the target information resource and the query input, generating a corresponding answer through the large model application. According to the technical scheme of the embodiment of the invention, the quality of the document retrieved in the retrieval enhancement generation can be improved, so that the quality of the answer generated by the large model can be improved.

The invention relates to the technical field of communication, and provides a communication method and a communication device.The method comprises the steps that first information is generated, the first information comprises second information and third information, the second information is used for waking up a first terminal and determining the third information, and the third information is used for waking up the first terminal; the third information is used for scheduling a first transmission resource of the first terminal; and sending the first information. According to the method, information resources can be flexibly and fully utilized according to the condition of the network load.

The present invention relates to the technical field of artificial intelligence, and in particular to a deep-learning-based method and system for root cause localization in cloud platform alert scenarios. The method comprises the following steps: acquiring cloud platform alert information, alert resource information, resource log information, and alert processing historical information. The beneficial effects are as follows: in the deep-learning-based method and system for root cause localization in cloud platform alert scenarios provided in the present invention, on the basis of collected cloud platform alert information, resource information, log information, etc., different alert scenarios are formed by means of alert clustering; for each alert scenario, the range for log analysis is determined, an association with resources and an association with logs are deeply analyzed, a final fault cause is identified; and for different alert scenarios, descriptions of the fault causes, key alert information, etc., are provided. In this way, scenario-based management is performed on alert, and more accurate problem localization is provided, thereby effectively shortening the period of time for operation and maintenance personnel to locate problems, improving the efficiency, and better ensuring the normal operation of a cloud platform.

The invention provides a node resource processing method and apparatus, a device, a medium and a program product, which are applied to a cloud computing platform architecture comprising N nodes, one node is deployed with an agent component, and one node comprises one or more resource nodes. The method comprises the following steps: when a resource scheduling request is received, acquiring a node resource topology information set; based on the resource scheduling request and the node resource topology information set, performing resource analysis processing on the N nodes, and determining a target node; resources in the target node are pre-allocated based on the resource scheduling request, resource annotation information is generated based on a resource allocation result of the target node, and the resource annotation information is used for indicating that the allocated resource node is bound with the resource object in the target node. According to the method, the node resources can be allocated and scheduled according to the node resource topological structure and the resource scheduling request, so that the node resources can be reasonably allocated, the scheduling result meets user requirements, and the resource scheduling effect is improved.

A method for a network data analytics function, NWDAF, configured to assist splitting of artificial intelligence / machine learning, AI / ML, operations between a user equipment, UE, and a processing network that are operably coupled via the communication network, the method comprising receiving, from a network function, NF, or an application function, AF, associated with the communication network, a request for a processing entity, PE, performance analytic associated with the processing network, wherein the processing network comprises a plurality of PEs; for each PE in the processing network, obtaining one or more of the following information: PE resource availability, and communication performance between the PE and each other PE in the processing network; computing the PE performance analytic based on the obtained information; and sending the computed PE performance analytic to the NF or AF, in accordance with the request.

The invention relates to the field of intelligent management systems, and particularly discloses a visual gas business management system and method, and the system comprises a supply chain relation management module which is used for building a business relation graph between enterprises according to a user instruction, collecting business mode information of the enterprises, and storing the business mode information of the enterprises; checking the rationality of the business relation graph in real time according to the business mode information, and generating an optimization suggestion based on a preset business rule; the settlement analysis module is used for carrying out detailed accounting information of fund arrival on each node in the service relation graph, dynamically adjusting the detailed accounting information according to prices and usage input by a user, and summarizing total fund detailed information at the tail end of a service link; a resource optimization module; a label management module and a report analysis module. By the adoption of the technical scheme, the multi-level gas supply chain structure can be conveniently constructed, accounting can be carried out in time, and verification can be carried out.

The invention belongs to the technical field of vehicle chassis coordination control, and particularly relates to an automobile chassis domain unified yaw motion control method and device based on a three-step method. Comprising the following steps: calculating a required yaw target; sensor, vehicle state and road surface information are acquired, and internal information resource sharing is realized; fault failure recognition of software and hardware is achieved, and corresponding driving safety is guaranteed. Aiming at an automobile of a four-wheel steering distributed driving electric automobile, a yaw stability integrated control system of a chassis domain based on a three-step method is designed; distributing the additional yawing moment, and distributing the additional yawing moment to four rounds for execution; and executing the distributed yawing moment control instruction and executing a front and rear wheel turning angle command to realize expected vehicle yawing dynamic control. Based on intelligent driving requirements of L2 + and above levels, the dynamic performance and the handling stability of the vehicle are improved, and the problem that yaw control in a traditional drive-by-wire chassis system is insufficient is solved.