78 results about "Resource integration" patented technology

The invention relates to the field of computer vision, in particular to an intelligent parking system based on a computer vision algorithm, which is provided with a data acquisition module, a resource integration module, an anomaly analysis module, a parking matching module and a parking guide module, determines a vehicle running value and an actual parking effective value, calculates a parking permission characterization value, and displays the parking permission characterization value. Determining whether a parking position for a target vehicle exists in the parking area; determining a target parking area; dividing the target parking area into a plurality of sub-areas; analyzing data information corresponding to the target parking area; and parking guidance is carried out according to the judgment result of the preset condition, and intelligent parking is completed. According to the invention, parking guidance is carried out by determining the target parking area, analyzing the corresponding abnormal data and comparing with the parking related area of the target vehicle, so that the smoothness of the parking path and the parking efficiency are improved.

The invention belongs to the field of load response and regulation, and particularly relates to an adjustable load aggregation and demand response control system of a virtual power plant, which is characterized in that dispersed adjustable load resources are aggregated into a load aggregation cluster containing shared resources through a clustering module; utilizing a screening module to construct an overlapping cluster hypergraph taking the shared resources as hyperedges, and screening a high-value candidate set; an iteration module is adopted to calculate a Shapley value revenue share of each load aggregation cluster through a cooperative game, a joint demand response strategy is generated by taking alliance total revenue maximization and Gini coefficient minimization as targets, and a system state is dynamically updated; and finally, integrating all strategies through a strategy generation module to generate an executable control instruction. According to the method, the problems of low resource integration efficiency, response delay and large execution deviation in the prior art are solved, optimal scheduling and cooperative control of load resources are realized, and the economical efficiency and the stability of the virtual power plant participating in the power grid demand response are remarkably improved.

The invention relates to the technical field of renewable energy utilization, and discloses a biomass energy circular economy system based on a multi-stage partner system and an operation method, and the system comprises a resource integration module which is used for obtaining a biomass raw material from an upstream partner; the energy and product conversion module is used for converting the biomass raw material into at least one energy product and at least one substance byproduct; the value circulation module is used for processing the substance byproducts into value-added products; and the multi-stage partner collaborative management module is used for carrying out whole-process resource collaboration, benefit distribution and cooperative relationship management on upstream partners, downstream partners and system operation related parties. According to the invention, a stock right binding mechanism based on a contribution value evaluation model is constructed, the cooperation value of the upstream raw material supplier can be accurately quantified, the long-term income right is given to the upstream raw material supplier, and the design realizes the relationship transformation from short-term buying and selling to long-term symbiosis with the raw material supplier.

The application provides a resource scheduling method and an electronic device, which can be applied to the technical field of computers. The resource scheduling method comprises the following steps: in response to a resource request for a target task, obtaining resource utilization scores of nodes and hardware accelerators in a cluster according to resource usage amounts of the hardware accelerators, resource allocation amounts of the nodes, and a resource demand amount carried by the resource request; determining a target node in the nodes and a target hardware accelerator of the target node according to the resource utilization scores and a scheduling strategy carried by the resource request, the scheduling strategy indicating a scheduling rule matched with resource integration requirements and / or load balancing requirements of the target task; virtually dividing the target hardware accelerator according to the resource demand amount to obtain a virtual hardware accelerator; and binding the virtual hardware accelerator to a container of the target node to execute the target task by using the container.

The invention relates to a red tourist route intelligent planning method based on multi-source data fusion, relates to the technical field of crossing of smart tourism and artificial intelligence, and realizes semantic unification and streaming incremental updating of multi-source heterogeneous red cultural resources by constructing a domain knowledge graph. Dynamic modeling is carried out on the regional road network, the environmental factors and the tourist portraits by utilizing a space-time digital twinning technology; a multi-target reinforcement learning algorithm is adopted, multi-dimensional constraints such as cultural value, safety risk and time satisfaction are comprehensively considered, and a personalized tourist route is generated online; and continuous self-optimization of the strategy is realized through a closed-loop feedback mechanism in the travel. According to the technical scheme, the problems of resource integration and real-time dynamic decision making in a large-scale desert area are effectively solved, and the intelligent level of route planning, the cultural experience depth and the travel safety guarantee are remarkably improved.

The invention discloses an AIGC-driven traditional cultural life education interaction system, which belongs to the field of cultural education and comprises a resource integration module, a situation creation module, a comprehensive evaluation module and a life criterion landing module. The resource integration module is used for collecting traditional cultural life education resources, performing intelligent processing on the resources through an AIGC technology, and constructing a structured digital resource library; the situation creation module generates immersive experience interaction content through AIGC based on the digital resource library, and realizes dynamic interaction between the learner and the traditional cultural life education content; by means of the AIGC technology, traditional cultural life education resources are converted into diversified forms such as 3D scenes, virtual interaction content and role playing games, a traditional single character and static teaching mode is replaced, the interestingness and immersion of learning are enhanced, cognitive lassitude is effectively relieved, and the intention of active participation of learners is stimulated.

The invention discloses a MinIO distributed storage optimization system and method based on an AI cloud desktop, belongs to the technical field of distributed storage, and aims to solve the technical problems of multi-cluster synchronization, enterprise-level security management and heterogeneous resource integration faced by MinIO in the AI desktop. Comprising a unified management platform which provides user authority management through an RBAC model and provides multi-level approval and audit logs through an operation approval process; the non-intrusive monitor is deployed in a source MinIO cluster and used for monitoring a data change event, and the non-intrusive monitor is matched with a synchronization engine in a target cluster to realize multi-cluster data synchronization; the storage abstraction layer is used for managing heterogeneous cloud storage resources, receiving a storage request initiated by a user through the API gateway, and routing the storage request to a corresponding storage service; and the metadata management library provides a data storage service.

The present application relates to the technical field of federal learning, in particular to a multi-agent enterprise asset collaborative management method and system based on federal learning, comprising the following steps: collecting multi-enterprise asset returns, risk volatility and asset liquidity, and performing normalization and feature dimension reduction to generate an asset feature set, calculating gradient differences based on the feature set and dynamically adjusting weights to generate a collaborative weight set, combining upload stability, return volatility ratio and participation frequency for comprehensive analysis to generate a credit factor, calculating the gradient angle to judge the direction deviation adjustment contribution ratio, and finally generating a collaborative return result set by joint weighting, in the present application, feature dimension reduction is optimized through data processing, local model training efficiency is improved, enterprise weight and collaborative direction are adjusted, enterprise contribution imbalance is avoided, collaboration stability is enhanced, gradient upload accuracy is improved, asset collaborative management is finally optimized, resource integration and utilization efficiency are improved, and data security and privacy protection are ensured.

The application relates to the technical field of computing power resource management, and discloses a computing power operation management method based on artificial intelligence, which comprises the following steps: S1, data acquisition and prediction; S2, intelligent scheduling and distribution of computing power resources; S3, comprehensive index optimization of computing power resources; S4, cross-regional multi-service resource integration; and S5, security management and monitoring of computing power resources. The application uniformly schedules and distributes multiple computing power resources, thereby greatly shortening the task execution time and improving the work efficiency; the optimal distribution strategy under different comprehensive indexes of computing power resources is analyzed, various comprehensive indexes are optimized and balanced, thereby realizing low-delay and high-response task scheduling; a unified computing power resource management platform is constructed, a sharing mechanism and cross-service integration are established, computing power resources in different regions, services and departments can be integrated, efficient utilization of the computing power resources and flexible deployment across regions are realized.

The invention provides a model parameter training data batch method and device based on a large model. Monitoring resource data of computing nodes in the cloud environment in real time, wherein the resource data comprises a CPU utilization rate, a GPU utilization rate, a memory occupancy rate, storage I / O performance and network bandwidth; processing the collected resource data to form a resource use snapshot; a scheduling strategy is initialized based on the resource snapshots, task requirements and node resource states are combined, and data batch tasks are dynamically distributed through an intelligent scheduling algorithm; the distributed tasks are received, an execution environment is prepared at a target node, data are preprocessed, the tasks are executed through parallelization and distributed calculation, and resources are released after the tasks are executed; training results of all the nodes are integrated and verified, and final model parameters are stored and published after verification. The scheme of the invention can adapt to the dynamic resource change of the cloud environment and meet the efficient processing requirement of large-scale data.

The invention discloses a grid code-driven power grid data resource multi-dimensional management method and system, and relates to the technical field related to power grid data management, and the method comprises the steps: carrying out the partition planning of grid division granularity for a preset power grid region, and generating a grid code coding result; obtaining multi-dimensional power grid data type generation features in a preset power grid region; performing hierarchical relationship analysis on a time dimension, a space dimension and an equipment dimension, and establishing a multi-dimensional data hierarchical relationship; constructing a large multi-dimensional hierarchical index model in combination with a grid code coding result and a multi-dimensional data hierarchical relationship; and executing storage and calling management of the power grid data resources of the preset power grid region by using the multi-dimensional hierarchical index large model. The technical problems that in the prior art, power grid data multi-dimensional characteristics are difficult to manage efficiently, time, space and equipment dimension data are processed dispersedly, and query management efficiency and accuracy are low are solved, and the technical effect of improving the accuracy and efficiency of power grid data resource integration management is achieved.

This invention provides a method for integrating and allocating computing resources for large-scale models based on power data, comprising the following steps: acquiring basic data of the large-scale model, determining the total amount of computing resources of the large-scale model from the basic data, and constructing a core computing pool and an unnecessary computing pool based on the total amount of computing resources; querying the specific locations of converter stations monitored by the large-scale model, mapping converter station nodes around the core computing pool, and connecting the core computing pool and converter station nodes through data channels; when a converter station experiences an anomaly or failure, collecting power data of the converter station, and evaluating the viscosity value between the converter station and the core computing pool based on the power data; adjusting the data channels according to the viscosity value, and allocating the computing resources of the core computing pool and the unnecessary computing pool to the abnormal or failed converter station through the adjusted data channels. By dividing the core computing power into core and unnecessary computing power, the problem of chaotic allocation caused by mixed computing power can be avoided, and the quantified viscosity value can be used to rationally allocate computing resources.

The invention discloses a cross-platform health science popularization resource integration and recommendation method and system, and relates to the technical field of data integration processing, and the method comprises the steps: collecting multi-source health science popularization resources, and carrying out the primary screening of the sources of the collected resources; performing standardization treatment on the health science popularization resources subjected to primary screening; collecting user data, and based on the collected user data, generating a user depth portrait from four dimensions of basic attributes, health states, behavior preferences and health demands; and matching a standardized processing result with the user depth portrait, and setting a recommendation priority according to the health state of the user. According to the method, standardized integration and medical precise recommendation of multi-platform health science popularization resources can be realized, and the problems of disordered resource formats, insufficient content authority, disjunction between recommendation and user health requirements and the like in the field of health science popularization are solved.

The invention discloses a road vehicle free flow identification system based on cross-system multi-source video fusion, and belongs to the technical field of Internet of Things. The system comprises a sensing layer, an edge computing layer, a cooperative computing layer and an application layer, the sensing layer is used for collecting video streams of the special identification equipment group of the toll portal and the traffic monitoring camera; the edge calculation layer is used for carrying out real-time analysis on the video stream of each identification node, generating a structured identification data packet and uploading the structured identification data packet; the cooperative calculation layer is used for carrying out environment adaptive fusion on the multi-source recognition results of the same node, carrying out real-time space-time cooperative verification on the cross-node recognition results, and constructing a vehicle track; the application layer is used for carrying out real-time path judgment and charging according to the vehicle track and detecting fake-licensed, shielding and abnormal speed behaviors; through cross-system resource integration, environment adaptive fusion, real-time multi-node cooperation and edge cloud distributed processing, a real-time and accurate technical solution is provided for free flow charging of the expressway.

The invention discloses a fund sales ecological platform based on four-party collaborative operation, belongs to the field of financial services, and aims to solve the problem that information of an existing fund sales ecological platform cannot be synchronized. Through the supervisor module, the institution module, the financial planner module, the customer module, the sales management module and the dynamic management module, single sign-on, full-process run-through and data seamless circulation are realized through one-stop resource integration aiming at the long-standing system splitting and low-efficiency operation pain points in the fund industry, and the system is convenient to use. A traditional mode that a user needs to repeatedly switch multiple systems and an operation path is broken is thoroughly changed, multiple fund product data of multiple trusteeship institutions are pulled at regular time through an FSP platform for unified cleaning and collection, and a standardized data asset management specification is established; structured and unstructured storage and processing are supported, the problem of data islands is solved, data are stored in different platform media according to the data value and the cold and hot degree, and the cost is optimized.

The invention discloses a green energy computing network system based on multi-modal energy collaborative scheduling, and particularly relates to the technical field of power grid scheduling, which comprises a multi-modal energy sensing module, a computing power task energy efficiency model building module, a computing network node layer, a two-dimensional prediction scheduling module, a computing power scheduling control module and a computing power flexible control module, according to the method, green energy data is collected in real time, expectation of the power consumption demand of a computing power task is calculated, a decision basis is provided for upper-layer scheduling through resource integration and cross-regional data interaction of a green power region and a computing power region, and an optimal collaborative scheduling strategy is output by adopting an improved particle swarm optimization algorithm based on the green energy data and a task energy efficiency portrait. The computing power task scheduling of the power shortage area is realized, the impact computing power scheduling instruction is converted into the power output by introducing the power ramp rate control of the S-shaped curve, the computing power is converted into the schedulable flexible load from the impact load of the power grid, and the stability in the power grid scheduling process is enhanced.

The embodiment of the invention relates to the field of data processing, and provides a cross-industry right and interest resource distribution method and device and a medium, and the method comprises the steps that a right and interest resource collection module obtains first right and interest resource data and second right and interest resource data; the user right and interest label extraction module performs user right and interest label extraction processing according to the consumption related data of the target user to obtain a user right and interest label; the user portrait construction module performs user right and interest portrait construction processing according to the user right and interest label and the consumption-related data to obtain a user right and interest portrait; the right and interest resource integration module performs right and interest label auxiliary integration processing according to the user right and interest label, the first right and interest resource data and the second right and interest resource data to obtain a right and interest resource database; a personalized right and interest resource screening module screens a personalized right and interest resource data set from a right and interest resource database; and the real-time dynamic right and interest distribution module is used for dynamically matching and distributing target right and interest resources from the personalized right and interest resource data set according to the real-time scene data.

The application relates to a script resource loading method, which uniformly coordinates and manages a script resource loading process by introducing a front-end loading coordinator. Specifically, after receiving a resource loading request sent by a front-end interface module, the front-end loading coordinator accesses a cache area, and finds matched script resources. When there are unmatched script resources, a special script resource request is generated and sent to a resource server, and corresponding target script resources are obtained from the resource server. The newly obtained script resources are written into the cache area for subsequent reuse, and the matched script resources and the newly obtained target script resources are integrated to generate request result data, and the request result data is returned to the front-end interface module. The application realizes reuse of inventory resources and directional pulling of incremental resources, and improves script resource loading efficiency.

The application discloses a kind of based on three-dimensional digital twinning's power grid infrastructure engineering intelligent management and control system and method, it is related to power grid infrastructure engineering management and control field, including: to power grid infrastructure is virtually modeled, builds power grid infrastructure numerical twin expected model;The progress of each link of power grid infrastructure engineering is carried out data acquisition, and is carried out digitization and standardization processing;The data of image acquisition are handled;The actual deviation degree of each link progress of power grid infrastructure is calculated;Comprehensive evaluation and forecast whether the progress of each link of existing power grid infrastructure engineering can complete project as expected;Establish three-dimensional digital twinning control platform of power grid infrastructure engineering, receive, store and display the numerical change of each link, and observe the progress change of each link of power grid infrastructure engineering by adjusting model parameter.Effectively improve the management efficiency of power grid infrastructure engineering, progress comprehensive evaluation ability and resource integration ability, reduce the island phenomenon of each link.

The invention discloses a learning resource intelligent management system and method based on data analysis, and belongs to the technical field of resource management. The method comprises the following steps: traversing multi-platform courses, extracting knowledge points, constructing a knowledge graph, and summarizing to form a multi-platform knowledge point database; repeated knowledge points are screened, and explanation emphasis directions of all the platforms are analyzed and quantified into specific numerical values. According to historical test data of students, answer expressions are disassembled to deduce knowledge point emphasis directions and quantify the knowledge point emphasis directions into specific numerical values, and courses with the most similar emphasis degrees are recommended after comparison. And if the matching degrees of the multiple courses are consistent, constructing a multivariate quantitative scoring system containing indexes such as teacher qualification and course favorable comments, carrying out weighted calculation on comprehensive scores, and carrying out sorting recommendation. Cross-platform resource integration and accurate personalized learning resource pushing are realized in the whole process, and the learning efficiency and the resource utilization efficiency are improved.

The invention discloses a universal evaluation system and method, computer equipment and a storage medium. The system comprises a new evaluation task establishment module, an evaluation model management module, a test execution module and an evaluation execution module. Wherein the new evaluation task module is used for receiving evaluation task information of an evaluation object input by a tester and generating an evaluation task card based on the evaluation task information; the test execution module is used for determining the type of the executed test task according to the content of the evaluation task card and executing the test task corresponding to the test task type to obtain a corresponding test result; and the evaluation execution module is used for acquiring a target evaluation model associated with the evaluation object from the evaluation model management module, and generating an evaluation result based on the test result and the target evaluation model. According to the technical scheme, multiple evaluation types can be compatible, resource integration and collaboration are achieved, the quality and efficiency of information security evaluation are improved, and the ever-increasing network security protection requirement is met.

This invention discloses an integrated application resource implementation scheme based on architecture diagrams, belonging to the field of computer technology. The system includes an architecture diagram design module, a resource association module, a work order generation module, and multiple collaboration modules. The architecture diagram design module provides a graphical interface for drawing architecture diagrams containing application nodes and connections; the resource association module associates resource information with application nodes; the work order generation module generates resource request work orders based on newly added application nodes and communication access control work orders based on the communication requirements corresponding to the connections; the multiple collaboration modules share the architecture diagram, resource information, resource request work orders, and communication access control work orders with multiple collaboration groups, and receive update feedback on work order status from multiple collaboration groups to dynamically adjust resource configuration. This invention achieves integrated management of architecture, applications, and resources, reduces cross-group collaboration costs, and improves resource configuration efficiency and system management efficiency.

A legacy resource is virtualized as a virtualized resource defined by features and capabilities set by an individual through a front-end user interface. Access rules are set on the virtualized resource based on the features and capabilities. When an access is requested to the virtualized resource, the corresponding access rules are enforced. Assuming there is no violation in the access rules, virtualized legacy resource services are overlaid on legacy resource services to cause the legacy resource services to perform any needed access operations on the corresponding legacy resource associated with the virtualized resource without changing any workflows processed by the legacy resource services.

The invention relates to the technical field of data resource integration, and discloses an integration method and device based on a localized data resource isomorphic processing technology and a medium. The integration method comprises the steps that a plurality of heterogeneous data sources are accessed through a localized data acquisition mechanism, original acquisition of data is completed, and attribute information of the data sources is marked; performing preprocessing through a preprocessing mechanism, standardizing and unifying the basic format of the data according to a preset basic format, and generating a standardized intermediate data set; metadata of an intermediate data set is analyzed to obtain field features of the data, a data model meeting a target standard is obtained through a localized data resource isomorphism processing algorithm step, then registration, classification and filing are performed through a resource management mechanism, a local resource directory is constructed, and the data model is stored in a database. And retrieval, calling and authority control based on metadata are supported. According to the method, the problems of poor adaptability, low resource utilization rate and insufficient data security in coping with a complex and changeable data environment in the prior art are solved.

Provided are a resource integration method, an electronic device and a storage medium. In the method, a resource list interface and a resource collection interface are displayed. In response to a dragging operation of dragging a target resource of at least one resource from the resource list interface to the resource collection interface, the target resource is displayed on the resource collection interface. An integrated resource is obtained based on the target resource included in the resource collection interface.

The invention provides a storage resource integration method, device and equipment and a readable storage medium, and relates to the technical field of containers, the method comprises the following steps: aggregating local storage spaces on a plurality of computing nodes of a container arrangement platform to form a cross-node storage resource pool, and establishing a data service environment on each computing node; constructing a storage service network, and deploying node management agents on a plurality of computing nodes; collecting information of a storage resource state and a storage resource pool through each node management agent, and generating a global resource view; receiving a storage resource application request, and generating a scheduling strategy in combination with the global resource view and a preset resource scheduling strategy; and according to the scheduling strategy, allocation and mounting operations of the storage resources are executed, so that the fragmented local storage resources are flexibly shared and allocated as required in the cluster range, the overall storage utilization rate is improved, and meanwhile, the technical effects of avoiding redundant overhead are achieved.

The application provides a classical music cross-modal high-reliability experimental data set construction method for full-scene teaching application, comprising the following steps: collecting multi-modal data such as audio, video and music score, constructing an original data set, standardizing each modal data by using a preprocessing technology, and obtaining a multi-modal data set in a unified format; constructing a knowledge graph according to a semantic feature vector, wherein a node represents a music element, and an edge represents a semantic relationship between elements; encoding the knowledge graph by using a graph convolution network to obtain a semantic representation of teaching content; integrating multi-modal teaching resources into an immersive teaching scene by using virtual reality rendering technology, presenting a content sequence in real time, and obtaining a dynamic teaching experience; updating the knowledge graph and the semantic feature vector by continuously collecting learner interaction data, optimizing the cross-modal fusion model by using an incremental learning algorithm, and obtaining an adaptive teaching data set.

A course resource development method. The method comprises: constructing a Chongqing regional culture key element recognition model, and extracting a cultural core having an educational value and an ideological and political orientation function; establishing a mapping logical framework between regional cultures and ideological and political theories, and performing structured correspondence on the cultural core and key knowledge points in course standards for ideological and political education in higher vocational education, so as to form a multi-dimensional mapping relationship matrix taking cultural carriers, value orientation and teaching targets as logical chains; on the basis of student cognitive features and professional backgrounds, dynamically generating contextualized teaching resource units; integrating multi-modal resources such as text, images and virtual scenes to form a reconfigurable multi-modal resource integration platform; and implementing continuous iterative optimization of the resources by means of teaching feedback data.

The invention relates to the technical field of information retrieval and data processing, and discloses a preschool education resource intelligent matching and pushing system based on a knowledge graph, and the system comprises a storage module which is used for storing a multi-layer dynamic knowledge graph comprising a basic knowledge layer, an individual development layer and a real-time situation layer; the processing module can acquire real-time situation data of physiology, environment and the like of the user, calculates development potential energy in combination with cognitive channel capacity to intelligently match resources, and identifies a learning path at the same time; and the pushing module is used for pushing the matched single resource or the combined sequence. According to the method, the real-time situation of the user and development potential energy calculation are integrated, fragmented preschool education resources are integrated into a coherent structured learning path, dynamic and prospective accurate recommendation is achieved, the problems that in the prior art, recommendation does not conform to the user state, and knowledge points are scattered are solved, and the user experience is improved. And the accuracy and suitability of education pushing are improved.