373 results about "Computer appliance" patented technology

The invention relates to the technical field of artificial intelligence chips, and discloses a model performance estimation method and device and computer equipment, and the method comprises the steps: determining model configuration data and candidate distributed strategies of a target model; converting the original calculation graph corresponding to the single-card deployment state based on the model configuration data and the strategy configuration data of the candidate distributed strategies to obtain a distributed overhead calculation graph corresponding to the multi-card deployment state; and performing performance estimation on the candidate distributed strategy according to the basic overhead and the additional overhead in the distributed overhead calculation graph to obtain strategy performance data of the target model under the candidate distributed strategy, thereby realizing conversion of a single-card model into a multi-card model. And based on the multi-card model, simulation calculation of the multi-card interconnection mode is realized on the premise of limited hardware resources, so that the influence of a communication operator and a topological structure corresponding to the multi-card interconnection mode in the overall operation of the model is reflected, and the upper limit of the model performance can be accurately evaluated in a simulator verification stage before silicon is applied.

An autonomous driving system test method, comprising: sampling scenario data of a plurality of scenarios (S10), and sending the scenario data of the plurality of scenarios to a plurality of simulation emulators (200) for distributed testing, so as to obtain test result data of the plurality of scenarios, the plurality of simulation emulators (200) being each integrated with an autonomous driving domain controller; and determining a dangerous scenario boundary for an autonomous driving system on the basis of the test result data of the plurality of scenarios (S20). The method is an improvement on the a scenario-based simulation test technology for autonomous driving systems, and using a server and a plurality of simulation emulators integrated with autonomous driving system domain controllers to perform joint testing can greatly improve the simulation test efficiency and the test effect for autonomous driving systems.

The invention provides a robust optimization method and system for a flexible power distribution network, computer equipment and a storage medium, and belongs to the field of power grid planning, and the method comprises the steps: obtaining a network topology structure and line electrical parameters of a to-be-optimized flexible power distribution network, and constructing a line model corresponding to the to-be-optimized flexible power distribution network according to the network topology structure and the line electrical parameters; acquiring historical operation data of each node in the line model; performing clustering analysis on the historical operation data of each node based on a fuzzy C-means clustering algorithm to obtain a typical scene of the to-be-optimized flexible power distribution network; constructing a polyhedral uncertainty set according to the typical model; taking the limited extreme scene as input, and minimizing the operation cost as an optimization target to construct a main problem; and taking a decision scheme for solving the main problem and the polyhedral uncertainty set as input, taking a scene with the maximum search operation cost as a target to construct a sub-problem, and iterating to obtain a robust optimization result of the to-be-optimized flexible power distribution network. According to the method, reliable optimization of the flexible power distribution network in a real uncertain environment is realized.

The invention discloses a GPU resource scheduling method based on data awareness and computer equipment, and the method comprises the steps: carrying out the real-time monitoring of a cluster node, obtaining a current cluster load state, and predicting the cluster load state in a future time period; creating services according to an input service definition description file, adding the services into a to-be-scheduled service queue, periodically selecting the services from the to-be-scheduled queue, and allocating computing nodes for the services; distributing a target service for the user request according to the current cluster load state, establishing a session, and analyzing the intention of the user; dynamically adjusting and allocating static resources through deep reinforcement learning based on a hybrid expert model according to a user intention analysis result and a cluster load state; required resources are loaded to a GPU through a multi-level cache architecture, and after calculation is completed, a calculation result is returned to a user through a session. According to the method, the utilization rate and the performance of GPU resources in an interactive GPU acceleration service scene can be improved, and the energy consumption and the cost are reduced.

The present application relates to a method and apparatus for controlling a wireless electrical energy transmission system, and a computer device. The method comprises: determining a real-time load resistance of a wireless electrical energy transmission system, and obtaining a trained value table, the trained value table comprising a sample load resistor, a sample primary resonant capacitor, and a sample value of correspondence between each sample load resistor and each sample primary resonant capacitor; in the trained value table, determining a real-time primary resonant capacitor of the wireless electrical energy transmission system on the basis of the real-time load resistance and the sample value; and controlling the wireless electrical energy transmission system on the basis of the real-time primary resonant capacitor. By adopting the present method, the convenience of control can be improved.

Telecommunications systems, computer devices and systems, and methods are provided. One example method, performed by a data abstraction layer of a telecommunications system for a network, includes accessing data elements associated with a network function of the network, performing abstraction on the data elements to generate one or more data products, receiving a customer request for a service on the network, identifying the data product related the service, and provisioning the identified data product to the customer. The method may further include identifying proprietary data and private data of the data elements based on a predefined policy and removing proprietary data and private data before performing abstraction.

A computer device and method are provided for detecting anomalies in a monitored computer system by classifying detected events using a machine learning model trained based on an activity log of events detected during an initial activity period. The machine learning model embeds logged events by generating a vector based on a tokenization of the logged event and a categorization of the logged event by a large language model. Events detected during the initial activity period are used to generate a profile of the monitored computer system. Events detected after the initial activity period are compared to the generated profile by a classifier of the machine learning model to classify each detected event as anomalous or normal.

The invention relates to a view-driven subgraph matching load balancing method and system, computer equipment, a storage medium and a computer program product. Candidate points of part of subgraphs are acquired and screened by starting a kernel function; collecting calculation data; calculating a prefix sum and a total candidate vertex number; dividing a calculation range according to the total number of candidate vertexes; screening candidate points, and recording the number of the candidate points; and counting results and generating a matching result array. The problems of waste of computing resources and low efficiency in the prior art are solved; through the load balancing method, the computing resources of the GPU are fully utilized, and the overall computing performance is remarkably improved.

The application relates to the technical field of communication, and provides an Activity component calling processing method and system, a computer device and a storage medium, which comprise the following steps: establishing a communication connection with a calling party and constructing a cross-process connection with a preset proxy Activity component; receiving intention information input by the calling party, sending the intention information to the proxy Activity component through the cross-process connection, and enabling the proxy Activity component to call a target Activity component corresponding to the intention information to process the intention information and obtain a return result; receiving the return result sent by the proxy Activity component, and returning the return result to the calling party. The application realizes cross-process calling of the Activity component, expands the range of target Activity components that can be called by the calling party, reduces the complexity of the calling party code, improves the logic of the calling party, ensures that the calling party can efficiently obtain data from the target component, and is beneficial to maintenance and function testing of the calling party.

The embodiment of the utility model provides a multi-path interconnection system and computer equipment, the multi-path interconnection system comprises a plurality of computing acceleration entities, the computing acceleration entities are standardized entity units at least used for integrating computing units, the computing acceleration entities comprise the computing units, and the computing units are connected with the computing acceleration entities. The computing unit comprises a plurality of first ports supporting a memory interconnection bus; a plurality of interface switching chips, each interface switching chip comprises a plurality of second ports, and the second ports are matched with the first ports; the connection channel is connected with the first port of the calculation acceleration entity and the second port of the interface switching chip; wherein any computing acceleration entity is provided with a plurality of connecting channels which are respectively connected with the plurality of interface switching chips. According to the multi-path interconnection system provided by the embodiment of the invention, the interconnection requirement among a plurality of computing units can be met.

This application relates to a domain name resolution method, apparatus, computer device, storage medium, and computer program product. The method includes: in response to a domain name resolution request for a target domain name, determining the target load type corresponding to the target domain name; determining a target node identifier array corresponding to the target load type from a node identifier array corresponding to each load type; wherein, in the target node identifier array, the number of node identifiers corresponding to each service node is positively correlated with the weight of each service node for the target load type; the weight of each service node for the target load type is obtained based on the load information of the service node for the target load type; determining the target node identifier in the target node identifier array according to a pre-stored node identifier determination strategy, and generating a response message corresponding to the domain name resolution request based on the Internet Protocol address corresponding to the target node identifier. This method can achieve a relatively balanced load pressure on each service node.

The invention provides a control method of a panel satellite large-size flexible solar wing driving device. The driving device comprises a satellite body, a double-shaft SADA, a swing rod, a hinge, a pressing and releasing mechanism and an ROSA solar wing. The control method comprises the steps that a release signal is sent to the pressing and releasing mechanism, the pressing and releasing mechanism releases the pressed solar wing after receiving the release signal, and the solar wing is driven by a hinge at one end of a swing rod to be passively unfolded by a first angle; according to the target angle and the first angle, calculating a second angle that the double-shaft SADA needs to rotate; a rotation signal is sent to the double-shaft SADA, the double-shaft SADA drives the solar wing to continue to rotate by a second angle after receiving the rotation signal, and a rotation in-place signal is sent out; and an unfolding signal is sent to the solar wing, and the solar wing starts to unfold the cell array plane until the cell array plane is completely unfolded. The control method improves the energy utilization efficiency of the whole satellite platform.

A method for supervised training of a machine learning model is described. Furthermore, a method for determining the armature position of an electrical actuator is described. A method for controlling an electrical actuator is also described. A computer device (2) configured to execute such a training method is described. A control device (4) configured to execute such a method for determining the armature position and such a method for controlling the actuator is also described. Finally, a vehicle (6) equipped with such a control device (4) is described.

The application relates to a reference value determination method and device of electrocardio data, a computer device, a storage medium and a computer program product. The method comprises the following steps: obtaining target electrocardio data collected in a collection time period, the target electrocardio data containing a plurality of heartbeat data units, each heartbeat data unit being composed of a plurality of heartbeat data segments. A heartbeat data segment to be detected is determined from the plurality of heartbeat data segments, and a target parameter matched with the heartbeat data segment to be detected is determined. A calculation mode of a reference value is determined, and a target test mode corresponding to the calculation mode is determined from a plurality of preset test modes; wherein the calculation mode comprises at least one of an automatic calculation mode and a manual calculation mode. The reference value of the target electrocardio data under the target parameter is calculated based on the target test mode. In this way, the accuracy of the reference value of the electrocardio data is greatly improved.

Renewable Energy Forecasting Computer Device

This application relates to the field of computer technology, specifically to a method, apparatus, computer device, and storage medium for running an open-source engine. The method for running the open-source engine is applied to a hardware extension plugin system for an inference engine. The hardware extension system includes at least an inference engine module and a hardware extension plugin module. The method includes: determining whether the current hardware is configured with all target operators required for inference computation of the model to be computed; if missing, determining whether the inference engine interfaced with the current hardware is configured with missing hardware operators; if the inference engine interfaced with the current hardware is not configured with missing hardware operators, calling the missing hardware operators from a pre-configured CPU operator library in the CPU through the hardware extension plugin system; and registering all target operators to the inference engine and / or the current hardware. This provides a secure, reliable method for third-party hardware to access an open-source engine with complete evolvability.

Embodiments of the present disclosure provide an interrupt controller, a chip, a computer device, an interrupt control method and a medium. The interrupt controller comprises a configuration unit, a first selection unit and a normalization processing unit. The normalization processing unit comprises a plurality of normalization sub-units. Each normalization sub-unit is connected to the first selection unit. Different normalization sub-units adopt different normalization processing modes. The configuration unit is configured to obtain first configuration information. The first configuration information is generated in advance based on the type of an interrupt request. Each type of interrupt request corresponds to a normalization processing mode. The first selection unit is configured to send the interrupt request to one of the plurality of normalization sub-units based on the first configuration information. Each normalization sub-unit of the plurality of normalization sub-units is configured to normalize the received interrupt request by using the normalization processing mode corresponding to the sub-unit.

The invention discloses a negative electrode lithium supplement utilization rate determination method, a determination system and computer equipment. The method comprises the following steps: S1, obtaining a theoretical lithium supplement thickness H theory required for realizing a battery target; s2, obtaining the effective lithium supplement thickness H < effective > of the lithium supplement negative pole piece and the corresponding lithium supplement utilization rate eta; s3, the experience lithium supplement utilization rate eta'is obtained; s4, calculating target lithium supplement thickness H production according to the theoretical lithium supplement thickness H theory and the experience lithium supplement utilization rate eta '; s5, in the production process according to the actual H, sampling is conducted regularly, the step S2 is executed, the current utilization rate eta < current > is obtained, and the current utilization rate eta < current > is compared with eta 'to obtain a correction coefficient K; and when the K value continuously deviates from the preset range, triggering process adjustment, and selectively feeding the eta back to the step S3 to update the lithium supplementing process. According to the method, a complex electrochemical design problem is converted into executable engineering parameters, the actual lithium supplementing amount can be dynamically adjusted, and a closed-loop control system of'calculation-implementation-evaluation-feedback 'is formed, so that the lithium supplementing precision is continuously improved, battery performance degradation caused by lithium supplementing deviation is fundamentally avoided, and the lithium supplementing efficiency is improved. And the reliability and the service life of a battery product are enhanced.

The invention relates to a graph data processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: identifying a target node with a neighbor node from graph data; performing sub-block division according to the identification number of each neighbor node, and determining a sub-block to which each neighbor node belongs; wherein the identification numbers in the same sub-block are arranged disorderly, and the maximum identification number in the previous sub-block is smaller than or equal to the minimum identification number in the next sub-block; storing the sampling weight of each neighbor node belonging to the same sub-block to the sub-block in the form of a tree array; and on the basis of each sub-block, an index structure for the target node is constructed, and the index structure is used for carrying out weighted sampling on neighbor nodes of the target node. By adopting the method, the memory overhead of graph data processing can be reduced.

A request processing method, executed by a load balancing node in a request processing system, wherein the request processing system comprises a reverse proxy node, a virtual proxy node, and the load balancing node, and request forwarding is performed between the reverse proxy node and the virtual proxy node by means of a plurality of socket nodes. The method comprises: upon receipt of a plurality of traffic requests by the reverse proxy node, determining, from among the plurality of socket nodes, socket nodes available for processing (302); for each socket node available for processing, determining, from the virtual proxy node, a processing instance having a binding relationship with the socket node available for processing, so as to obtain a plurality of processing instances (304); determining, from among the plurality of processing instances, selected processing instances matching socket nodes available for processing (306); and on the basis of multiple pieces of instance running information respectively corresponding to the selected processing instances, respectively distributing the plurality of traffic requests to the selected processing instances, so that the selected processing instances process the distributed traffic requests (308).

The application provides a fault information sending method, device and vehicle, and belongs to the technical field of electronics. The method comprises the following steps: in the case that a diagnosis function is started, the instrument device determines fault information of at least one component in the vehicle based on a first data protocol, determines to-be-encapsulated information according to a second data protocol and the fault information, encapsulates the to-be-encapsulated information based on the first data protocol and the second data protocol, and sends the encapsulated information to the wireless device, wherein the fault information is used for indicating a fault type of the component; the wireless device analyzes the encapsulated information based on the first data protocol, and sends to-be-sent information obtained by analysis to a target computer device based on the second data protocol, and the target computer device is used for analyzing, storing and displaying the to-be-sent information. The application can provide effective display assistance for users and output fault information of an electric vehicle in a wireless mode.

The application relates to the technical field of molecular property prediction and digital medical treatment, and discloses a molecular property prediction model training method, a storage medium, a computer device and a molecular property prediction device. The method comprises the following steps: acquiring molecular graphs of a plurality of sample molecules, splitting the molecular graphs to obtain candidate graph prompts, extracting a preset number of candidate graph prompts as target graph prompts according to a preset candidate graph prompt extraction rule; encoding the target graph prompts into target graph prompt vectors, calculating the importance weights of the target graph prompt vectors on the molecular graphs, calculating a global graph prompt vector according to the target graph prompt vectors and the importance weights; splicing the global graph prompt vector with feature vectors of the sample molecules respectively to obtain molecular vectors of the sample molecules; and training a molecular property prediction model according to preset molecular property labels corresponding to the sample molecules and the molecular vectors. The trained model can simultaneously predict a plurality of molecular properties, and the drug research and development efficiency is improved.

This application relates to a cloud-native resource description framework (RPF) data storage system, method, and computer device. The system includes: a storage layer for storing triples sharing the same attribute in RPF graph data as a subgraph and storing them in cloud object storage, constructing a range-aware offset index for each subgraph; and a computation layer for receiving RPF queries, decomposing the RPF queries into multiple subqueries according to attributes, querying the range-aware offset index, obtaining the byte offset of the target data value in each subquery in the corresponding subgraph, and, based on a query processing efficiency model, determining a target access method for each subquery from multiple preset data access methods according to the byte offset, executing the target access method to output the subquery result, and concatenating the results of each subquery to generate the query answer. Using this system can significantly reduce storage and query operating costs while maintaining competitive query performance.

Embodiments of the present disclosure provide a positioning method and device of a backscattering device, computer device, readable storage medium and program, and relate to the technical field of computer communication. The method comprises: receiving a mixed signal, wherein the mixed signal comprises a direct signal and a reflected signal; obtaining a first incident estimation angle of the direct signal and a second incident estimation angle of the reflected signal; obtaining a direct estimation signal and a reflected estimation signal according to the first incident estimation angle and the second incident estimation angle; obtaining a reflected link delay according to the direct estimation signal and the reflected estimation signal; obtaining a reflected link length according to the reflected link delay; and obtaining coordinates of the backscattering device by an elliptic formula algorithm according to a radio frequency source coordinate, a receiver coordinate, the reflected link length, the first incident estimation angle and the second incident estimation angle. The method provided by the embodiments of the present disclosure can realize positioning of the backscattering device.

The invention relates to a tensor memory accelerator instruction synchronization system and method, computer equipment, a readable storage medium and a program product. The system comprises an execution unit and a tensor core, a synchronous control module and a tensor memory accelerator are integrated in the tensor core, the execution unit is used for sending a tensor memory accelerator instruction to the tensor core, and the tensor memory accelerator instruction carries synchronous information. The synchronization information comprises a to-be-monitored state of the first target signal and a to-be-updated state of the second target signal after the tensor memory accelerator instruction is completed; and the synchronization control module is used for controlling the state synchronization of the first target signal and the state updating of the second target signal before and after the tensor memory accelerator executes the tensor memory accelerator instruction based on the to-be-monitored state of the first target signal and the to-be-updated state of the second target signal in the synchronization information. By adopting the system, the efficiency of tensor operation can be effectively improved.

This application relates to a vehicle centering control method, apparatus, computer device, storage medium, and computer program product. The method includes: first, acquiring initial influence parameters; then, conducting orthogonal experiments based on the initial influence parameters; determining a target evaluation index based on the experimental results of the orthogonal experiments; the target evaluation index characterizing the degree of influence of the initial influence parameters on vehicle centering; next, determining a first target influence parameter from the initial influence parameters based on the target evaluation index; and finally, controlling vehicle centering based on the first target influence parameter. The method provided in this application determines the degree of influence of different initial influence parameters on vehicle centering based on the results of orthogonal experiments, thereby selecting a first target influence parameter that significantly affects vehicle centering, thus improving the accuracy of vehicle centering control.

This application discloses a service device invocation method, apparatus, computer device, and storage medium. Belonging to the field of communication technology, the method specifically includes: responding to a first service request sent by a calling terminal; obtaining device information of a target service device based on the terminal location information of the calling terminal in the first service request; wherein the device information includes at least the number of terminals currently invoking the target service device; determining the associated media gateway of the target service device based on the number of terminals; and invoking the target service device to provide the media stream corresponding to the first service request based on the associated media gateway. Because this application only requires the number of terminals to meet a preset requirement to invoke the target service device, it effectively solves the problem that traditional target service devices can only be invoked by one user. The method based on this application enables multiple users to simultaneously invoke the same service device, effectively improving resource utilization and facilitating the promotion of multimedia services.

The application relates to the technical field of artificial intelligence, and discloses a data processing method, device, equipment and storage medium to improve blacklist processing capability. The method part comprises the following steps: receiving a loan approval request sent by a target business system, the loan approval request carrying loan approval data, the loan approval data comprising a system type of the target business system and attribute information of an applicant; calling a blacklist interface corresponding to the system type to obtain a system blacklist; judging whether the applicant is a user in the system blacklist according to the attribute information of the applicant; when the applicant is not a user in the system blacklist, a platform blacklist of an automatic approval platform is called; judging whether the applicant is a user in the platform blacklist according to the attribute information of the applicant; when the applicant is a user in the platform blacklist, a loan service corresponding to the loan approval request is rejected, and rejection result information is generated and fed back to the target business system.

The invention relates to the technical field of communication, and provides a data transmission method, computer equipment and a computer readable storage medium. The method comprises the following steps: after a Bluetooth connection completion event with upper control equipment is detected, sending a maximum transmission unit negotiation request to the upper control equipment; determining a first negotiation result according to the maximum transmission unit response returned by the upper control equipment, and determining a target maximum transmission unit of the Bluetooth connection according to the first negotiation result; then, a link layer data length negotiation request is sent to the upper control equipment; determining a second negotiation result according to a link layer data length response returned by the upper control equipment, and determining a target link layer data length of the Bluetooth connection according to the second negotiation result; and according to the target maximum transmission unit and the target link layer data length, performing operation data transmission with the upper control equipment based on Bluetooth connection. According to the invention, the operation data can be normally transmitted between the self-operation equipment and the upper control equipment based on the Bluetooth connection.

This application relates to the field of household appliance technology, specifically to a washing control method, system, computer device, and storage medium based on multi-source fusion sensing. The method includes: during the washing stage, determining washing state parameters of the clothes in the tub and water quality change parameters of the washing water based on acquired spatial detection signals and water quality detection signals, respectively; dynamically adjusting the washing control parameters of the washing equipment based on the washing state parameters and the water quality change parameters until washing is complete; during the rinsing or spin-drying stage, acquiring real-time operating parameters of the washing equipment's drive motor; if the real-time operating parameters meet preset operating conditions, switching to a first sensing mode and performing foam state evaluation based on drive load parameters; if the real-time operating parameters do not meet the preset operating conditions, switching to a second sensing mode to perform foam state evaluation based on the spatial detection signals; and controlling the washing equipment to perform rinsing actions based on the foam state evaluation results.