165 results about "System requirements" patented technology

The invention discloses a power grid dispatching method and system adapting to power system requirements, and relates to the field of industrial big data, and the method comprises the following operation steps: S1, multi-source heterogeneous data collection and edge preprocessing; s2, knowledge graph construction and data fusion; s3, load prediction and renewable energy output prediction based on deep learning; s4, generating a dynamic optimization scheduling strategy; s5, carrying out security and credible execution on the data endowed by the block chain; and S6, real-time monitoring and closed-loop feedback optimization are carried out. According to the power grid scheduling method and system adapting to the power system demand, the scheduling method integrates edge calculation, block chain, deep learning and reinforcement learning, can realize multi-source data real-time processing, dynamic optimization strategy generation and data security and credibility, improves the power grid operation efficiency, stability and renewable energy consumption capability, and improves the power grid scheduling efficiency. And the dynamically optimized scheduling strategy can reduce the operation cost of the power grid, and can reduce carbon emission at the same time.

An online system automatically generates a personalized collection of items around a theme. The online system generates a prompt for input into a language model, the prompt including information about a plurality of items and a text describing the theme around which the collection of items will be built. The online system requests the language model to generate, based on the prompt, a list of products eligible for building the collection of items. The online system accesses a computer model trained to identify a set of items personalized for a user of the online system. The computer model identifies, based on the list of eligible products and information about the user, the set of items for populating the collection of items. The online system causes a device of the user to display a user interface with the collection of items for inclusion into a cart of the user.

The invention discloses a virtual power plant optimization system and method, and the system comprises a virtualization platform module which is used for integrating distributed energy, energy storage equipment, an electric vehicle, a flexible load and other resources, and achieves the virtualization and centralized management of the resources; the dynamic resource aggregation module is used for dynamically matching resource characteristics with power system requirements; the market transaction module is used for optimizing the earnings of the virtual power plant; and the core algorithm module is used for optimizing the load prediction precision. The market transaction module implements two-stage market bidding based on a multi-agent game model, analyzes the uncertainty of quotation of competitors through a multi-scene simulation technology, optimizes a dynamic transaction strategy, and achieves the maximization of spot market benefits and the controllability of risks. Through cooperative work of a virtualization platform module, a dynamic resource aggregation module, a market transaction module, a core algorithm module, a security management module and the like, efficient management of resources and maximization of market benefits are realized.

The technology described herein is directed towards an artificial intelligence scheduler for real-time task execution systems, including an implementation based on a recurrent learning model. In one implementation, the model incorporates a deep Q-network and proximal policy optimization to learn efficient scheduling policies for real-time systems. The scheduler can optimize for various real-time system aspects, including avoiding deadlocks, minimizing blocking, avoiding priority inversion, and reducing starvation. The artificial intelligence scheduler learns from actual system experience data to regularly improve scheduling policies and / or adapt to changing system requirements.

Systems, methods, and computer-readable storage media of configuring digital currency nodes utilizing a one-tier model or two-tier model. One method includes transmitting, via an application provider system, an installation request including authentication information, downloading, by the user device, a digital wallet application, and installing, by the user device, the digital wallet application based on one or more system requirements, wherein installing includes verifying the user device meets the one or more system requirements, generating a public and private key pair, hardening the user device, storing and configuring the digital wallet application, and authenticating the digital wallet application. The method further includes establishing, via a private network, a private network connection associated with digital currency issuance. Another method includes transmitting a registration request, receiving a software package including a software appliance and executable code, installing the software appliance and establishing a private network connection associated with digital currency issuance.

Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to comply with system requirements frameworks that indicate specific requirements on how the computing systems should handle certain data types. In response to detecting a change to one or more digital data requirements of a system requirements framework, the disclosed systems access a configuration profile of an entity and utilize a large language model to determine if data assets or data processing operations comply with the changes to the digital data requirements. In response to determining a configuration gap of the configuration profile based on detected changes to the digital data requirements, the disclosed systems utilize a large language model to generate tasks for correcting the configuration gap. The disclosed systems generate one or more tasks by modifying data assets, data processing operations, or other digital data associated with the entity.

The present disclosure provides computer-implemented methods, systems, and devices for automatically evaluating metadata associated with an application. A computing system accesses metadata for a respective application; wherein the respective application is associated with an operating system. The computing system accesses data describing requirements for the operating system. The computing system automatically generates one or more configuration rules for the metadata based on the documentation for the operating system. The computing system determines that the metadata violates one or more configuration rules based on the one or more configuration rules. The computing system transmits data describing one or more violations of the configuration rules for display.

Methods, systems, and non-transitory computer readable storage media are disclosed for facilitating modification of components of artificial intelligence computing applications via aggregated risk scores of individual artificial intelligence computing application components. The disclosed system generates data objects representing the artificial intelligence computing application components. The disclosed system determines mappings between the data objects based on relationships of the artificial intelligence computing application components. Furthermore, the disclosed system generates risk scores for the data objects representing the components of the artificial intelligence computing application by administering risk assessments that correspond to a system requirements framework. The disclosed system also generates an interactive aggregated risk indicator indicating contributions of the components to the artificial intelligence computing application in relation to the system requirements framework by combining the risk scores of the data objects according to the mappings between the data objects.

The invention provides an end-to-end intelligent system development method and system based on an AI large model. The method comprises the following steps: S1, receiving a system demand described by a user through a natural language; s2, analyzing the requirements through an AI large model and converting the requirements into formalized specifications; s3, automatically generating a system architecture and dividing components; s4, generating each component code in a recursive manner; s5, dynamically detecting and repairing the generated code problem; s6, automatically integrating all components to form a complete system; and S7, continuously optimizing the system based on system feedback or user feedback. According to the method, work of multiple stages such as demand analysis, architecture design, module division, code writing and testing is automatically completed, distributed integration and smart contract are performed, distributed integration verification is performed through a block chain smart contract and a graph database, data consistency, interface matching and security among components are ensured, the integration process is optimized, and the integration efficiency is improved. Cross-domain cooperation is achieved, and the development efficiency is high.

To provide systems and methods capable of ensuring correct execution of computer programs in a distributed computing environment.SOLUTION: In a distributed system, a first computer system is configured to: require computationally verifiable assurances of the authenticity and integrity of computations performed by a second computer system; and delegate execution of a program to the second computer system, where a protocol to make the execution of the program safer is employed to constrain the second computer system to perform correct execution of the program. The protocol may include mitigation and correction routines that mitigate and / or correct incorrect execution of the program, and the protocol may utilize a blockchain network such as a Bitcoin-based blockchain network.SELECTED DRAWING: Figure 4

The invention discloses a decision planning system-oriented simulation test scene automatic generation method. The method comprises the steps of scene modeling: constructing a scene model by using a deep learning model; constraint generation: based on an output result of the scene model, utilizing a reinforcement learning model to generate a constraint condition; performing optimization search: based on the scene model and the constraint conditions, generating scene parameters meeting constraints by adopting a Bayesian optimization algorithm; and scene evaluation: evaluating the system performance by using the deep reinforcement learning model. According to the simulation test scene automatic generation method facing the decision planning system, manual intervention is reduced through an automatic method, and the scene generation efficiency is improved; diversified and high-coverage test scenes are generated, the scene diversity is enhanced, and the robustness of the system is comprehensively tested; constraint processing is optimized by efficiently processing complex constraint conditions, and it is ensured that a generated scene meets system requirements; and comprehensive system performance evaluation is provided, multi-dimensional evaluation is realized, and the performance of the system in different scenes is reflected.

The invention discloses a configuration processing method and device of a hyper-converged system, a storage medium and electronic equipment, and relates to the technical field of computer hardware, and the method comprises the steps that specified configuration information of a server is acquired, and the specified configuration information is configuration information of a basic input and output system of the server; the specified configuration information is analyzed, actual configuration values of a set of specified configuration items are obtained, and one specified configuration item in the set of specified configuration items corresponds to one function provided by the hyper-converged system; in a set of specified configuration items, under the condition that at least one configuration item with the actual configuration value inconsistent with the expected configuration value exists, the actual configuration value of the at least one configuration item is modified, and therefore the difference between BIOS configuration and the hyper-converged system requirement can be automatically detected and corrected; the configuration processing method of the hyper-converged system in the related technology has the problems of low deployment efficiency and poor reliability caused by high deployment complexity.

Systems, methods, and computer-readable storage media of configuring digital currency nodes utilizing a one-tier model or two-tier model. One method includes transmitting, via an application provider system, an installation request including authentication information, downloading, by the user device, a digital wallet application, and installing, by the user device, the digital wallet application based on one or more system requirements, wherein installing includes verifying the user device meets the one or more system requirements, generating a public and private key pair, hardening the user device, storing and configuring the digital wallet application, and authenticating the digital wallet application. The method further includes establishing, via a private network, a private network connection associated with digital currency issuance. Another method includes transmitting a registration request, receiving a software package including a software appliance and executable code, installing the software appliance and establishing a private network connection associated with digital currency issuance.

The invention provides an engine software FADEC demand-oriented modeling analysis and test case automatic generation method, and belongs to the field of aero-engine control. According to the method, DeepSeek is used for assisting preprocessing at the system demand level, and modeling work based on a formalized table is completed; through multi-level demand model analysis, vulnerabilities existing in the demand are automatically detected; and finally, automatically generating a test case set meeting DO-178C airworthiness requirements by establishing a grammar logic architecture. The method focuses on formalized verification work of an engine software FADEC demand level, by using an executable model, defects appearing in the demand or design process can be effectively found, errors can be eliminated in time, test cases are automatically generated, and therefore rework and iteration cost in the later period of development is greatly reduced.

The invention discloses an equipment control device and method, a storage medium and electronic equipment, and relates to the technical field of computers, the device comprises a plurality of switch boards, and each switch board comprises a first controller, a first logic device and a plurality of switch chips; the first controller is connected with a first port of the first logic device; a second port of the first logic device is connected with a first port of the switching chip; a third port of the first logic device is connected with the first circuit board; a second port of the switch chip is connected with a plurality of heterogeneous acceleration cards; the first controller is used for controlling a target acceleration card in the heterogeneous acceleration cards, and the target acceleration card and the first controller are connected with the same switching board. Compared with the prior art, the system requirements of a plurality of heterogeneous acceleration cards can be met, the heterogeneous acceleration cards are controlled by utilizing the controllers on the switching boards, a controller on a host does not need to be called for control, the control efficiency of the heterogeneous acceleration cards is improved, and then the performance of the whole machine is improved.

The invention relates to a knowledge graph and thinking chain reasoning-based complex system demand identification and management method. The method comprises the following steps of S1, constructing a system demand classification network model; s2, constructing a demand structured extraction model based on a thinking chain; and S3, constructing a general demand knowledge graph and a target graph, and complementing the target graph. Through fusion of the knowledge graph and the thinking chain reasoning technology, the problems that in the prior art, classification model precision is low, extraction model leak detection is high, and graph model universality is poor are solved, and the method is suitable for demand modeling in the fields of subways and high-end equipment.

The invention discloses a meteorological data source credibility proving method based on a block chain, and provides a new data source credibility proving mechanism by utilizing the characteristics of tamper resistance, forgery resistance and loss resistance of the block chain and combining signature verification and hash operation algorithms in cryptography. According to the mechanism, credibility and data delivery validity verification can be accurately carried out on delivery data recorded by a data provider; according to the patent, transaction / shared data is converted into a pre-agreed intermediate format (a character set, a coding mode and an XML / JSON data structure expression mode) and is stored in a file form. And after receiving the data, the data user converts the data into a self system format according to self system requirements, so that the correctness of data information expression is ensured. Through the overall transmission of the data packet, the accidental missing and tampering of the data in the transmission process between the two handover parties are effectively avoided.

The invention discloses a stability regulation and control method and system for energy storage of a power distribution network of a power system. The system comprises an energy storage module, a load regulation and control module, an active power distribution module and a data interaction module, the energy storage module collects and analyzes parameter data based on power system requirements and resources, and reasonably stores the parameter data in a database; the load regulation and control module monitors the energy storage condition in real time and predicts and preferentially controls the load; the active power distribution module monitors power flow distribution and optimizes a power distribution scheme; the data interaction module is responsible for issuing a power distribution scheme to related equipment and adjusting and optimizing the scheme according to feedback; an energy storage objective function is established by comprehensively considering various factors, a dynamic optimization algorithm is used for load prediction, real-time monitoring and optimization of a power distribution scheme, a regulation and control scheme is continuously adjusted and optimized through a data interaction and closed-loop feedback mechanism, and meanwhile, an abnormal trigger limit value is set to guarantee stable operation of the system. Therefore, the expandability and maintainability of the system are improved.

Disclosed in the present invention are a network traffic collection method and system based on a cloud-based environment. The present invention solves the problems of existing traffic collection being invasive to a monitored system, and having system and software dependency requirements, poor adaptability, and high consumption of computing and network transmission resources. A mirror virtual switch and a virtualized instance agent node are created at a computing node. By mirroring traffic by means of a patch port of a virtual switch, monitoring node data is diverted to the mirror virtual switch, and then is forwarded to the virtualized instance agent node by means of the mirror virtual switch; network traffic data is stored as in a file format, and is forwarded to a data security monitoring platform for monitoring a virtualized instance event in real time, and when the event changes, a flow table of the virtual switch is adjusted on the basis of a monitoring policy. According to the present invention, traffic monitoring is implemented in a software manner, and virtualized instance traffic is collected before packet modification, facilitating the accuracy of security event judgment, involving no intrusive modification to an instance, and no system requirement, and occupying few resources.

The invention discloses a photoelectric system digital prototype function model generation method and device based on artificial intelligence, and belongs to the technical field of artificial intelligence and photoelectric system digital prototypes, and the method comprises the steps: inputting training data of an artificial intelligence model, carrying out semantic analysis, marking and key parameter extraction operation, and forming a knowledge graph; establishing a logic association and constraint relationship among the parameters; training an artificial intelligence model by using the analyzed training data, optimizing a preset general rule base of the artificial intelligence model, and constructing a photoelectric system modeling rule base and a photoelectric system artificial intelligence model; calling the trained artificial intelligence model of the photoelectric system, extracting a model demand, calling the modeling rule base of the photoelectric system, and generating a function model of the photoelectric system; and visually displaying the photoelectric system function model, modifying and updating the photoelectric system function model, and dynamically updating the optimization strategy. Different function model modeling languages can be selected according to actual system requirements, and an artificial intelligence algorithm is adjusted.

Methods and systems are described that use artificial intelligence (AI)-based natural language processing (NLP) techniques to rapidly analyze, merge, and / or identify relationships between systems engineering artifacts (e.g., system requirements, system architecture descriptions, research requirements, risk assessments, etc.) to accelerate systems engineering program management, technical capability development, and acquisition initiatives associated with systems engineering projects.

The invention discloses a model-based civil aircraft integrated modular avionics resident system design method. The method comprises the steps of S1, resident system demand modeling and demand confirmation based on a customized MBSE method; s2, performing resident application software function logic modeling based on a Simulink model; s3, performing qualitative security analysis on the resident system based on the function scene and the fault combination; the input of the step S1 comes from a technical protocol of a resident system issued by a host, and through modeling iteration, the demand of the resident system is captured and issued to the step S2; s2, feeding back a system design problem identified in the modeling process; the step S1 synchronously sends the demand of the resident system to the step S3, and at the same time, the step S3 feeds back the identified security demand and constraint to the step S1 to support system demand iteration. According to the invention, an efficient, replicable and landing design thought is provided for the integrated modular avionics residence system, the system design efficiency is improved, and the verification cost is reduced.

The invention relates to a dynamic resource aggregation scheduling method and system for a virtual power plant and a medium, and the method comprises the following steps: S1, building a virtual power plant (VPP) system model; s2, power system requirements and technical constraints are determined; s3, performing preliminary scheduling on various energy sources in the virtual power plant by using a random mixed integer linear programming model; s4, quantifying the system contribution of the distributed resources by using a VCG (Vickrey-Clarke-Grove) mechanism in a cooperative game theory; and S5, according to the quantitative result and the real-time data, dynamically adjusting scheduling schemes of various energy sources in the virtual power plant with economic benefit maximization. According to the method, the aggregation efficiency of virtual power plant resources can be effectively improved, and the overall energy utilization efficiency and the operation stability of a power grid are improved.

The invention discloses a plug-in function and online test method for a pre-training model of a power system, and designs a pre-training model oriented to the power industry by combining NLP, BERT and reinforcement learning technologies, and realizes a data-driven intelligent control strategy. Through semi-supervised learning, labeled data and unlabeled data are integrated, the generalization ability of the model is improved, and a high-quality initialization model is provided for reinforcement learning agents. The pre-training model is disassembled into independent plug-in modules, and the plug-in modules are integrated with a simulation platform through an API, so that on-demand loading and scene switching of the modules are realized, and the flexibility of the system is ensured. A dynamic event and a system fault are simulated on an HIL platform, and a reinforcement learning agent is pre-trained in combination with an MPC controller, so that the strategy optimization process can continuously adapt to a system state. In addition, model parameters and control strategies are continuously updated through a particle swarm optimization algorithm, and it is ensured that the RL agent and the plug-in module are always kept synchronous with system requirements.

Techniques are provided for customizing authentication and for handling pre-authentication and post-authentication plug-ins in an access management system. Users may want to access a protected resource, such as an application, and apply customizations to the protected resource. The customizations can be applied through the use of plug-ins, such as pre-authentication and post-authentication plug-ins. After it is determined that the user has permissions to apply a specified plug-in, analysis is performed to ensure that the plug-in complies with system requirements and that the criteria for implementing the plug-in has been satisfied. A browser session and control of the application can then be forwarded to the user.

A system for optimizing slide pick basket operations, wherein the system includes at least a robotic arm, at least a processor, and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to perform an orientation check on a plurality of slides in a pick basket, wherein performing an orientation check includes receiving visual data, identifying an orientation of a first slide of the plurality of slides as a function of the visual data, and verifying that the orientation of the first slide aligns with a system requirement, pick the first slide of the plurality of slides as a function of verifying that the orientation of the first slide aligns with the system requirement, and place the first slide at a scanner.

A system includes a host and a memory system, which includes a controller and a memory device including one or more superblocks for storing data. The host sets multiple system performance regions according to data type, on a plane which are formed by two or more system metrics. Each system performance region corresponds to at least one tier among multiple tiers of system requirements. The controller tracks the system metrics for each superblock associated with one or more read operations on the data; determines whether a condition of the system metrics is close to a boundary of a system performance region selected from among the multiple system performance regions, the selected system performance region corresponding to the data; and recycles the superblock when it is determined that the condition of the system metrics is getting close to the boundary of the selected system performance region.

Embodiments of the invention are directed to systems, methods, and computer program products for automatically enabling features in a software production environment. In some embodiments, the method includes defining, using a configuration scanning function, a plurality of features in a production environment, where each feature of the plurality of features includes a feature activation status, and activating, during a code delivery process, at least one feature of the plurality of features based on an output of a machine learning algorithm. The method may also include defining, using a code scanning function, a set of system requirements associated with a source code. The configuration scanning function and the code scanning functions may each be configured to provide at least one input of the machine learning algorithm.

The present invention relates to a method, system, terminal and storage medium for setting a GRUB startup sequence, comprising the following steps: enumerating PCI devices and creating PCI device paths in a BIOS startup phase; enumerating the mounted storage devices of the PCI devices in the BIOS, creating storage device paths, and installing the storage device paths to storage device handles; installing a BLOCK IO protocol to the storage device handles in the BIOS; obtaining all BLOCK IO protocol handles installed in the BIOS startup phase in a GRUB kernel boot disk sequence, finding storage device paths through the handles, and dividing storage devices into multiple storage device classes; reading a kernel program through the BLOCK IO protocol, and running the kernel program; a user can adjust the GRUB kernel boot disk sequence in the BIOS phase without modifying a GRUB configuration file or program, can adapt to various system requirements for mounting different storage devices, and smoothly load the kernel program.

The present invention discloses a high-speed real-time transmission implementation system and method based on the RapidIO protocol, comprising a data exchange module that is simultaneously connected to a source device and a destination device, the data exchange module comprising an FPGA chip, the source device and the data exchange module exchanging data via a serial transceiver, the data exchange module and the destination device exchanging data via a RapidIO interface, and the serial transceiver and the RapidIO interface both being connected to the FPGA chip via a cache module. The system of the present invention is highly flexible, highly scalable, and easy to transplant. The present invention can increase or decrease the interface between the source device and the data exchange module FPGA, and the interface between the data exchange module FPGA and the destination device according to system requirements, and adjust the data transmission bandwidth by increasing or decreasing the interface. The present invention takes into account both high bandwidth and real-time performance, adopts multi-channel transmission, increases the transmission speed, and improves the transmission efficiency.