696 results about "Operating environment" patented technology

The invention discloses a reinforcement learning-based virtual power plant response optimization scheduling system and method, and relates to the technical field of virtual power plant intelligent scheduling. The system comprises an environment modeling module, an intelligent agent module, a multi-agent coordination module and a self-adaptive optimization module which are respectively used for constructing a multi-dimensional state space and a layered action space, generating and optimizing an action strategy based on an Actor-Critic network, executing a scheduling instruction through a layered multi-agent structure and realizing conflict consensus, and dynamically adapting to state space change in combination with incremental learning and meta-learning mechanisms. The system and the method have the advantages of fine state modeling, efficient action response, adaptive strategy updating, stable agent coordination and the like, and can keep the continuity, the stability and the optimality of a scheduling strategy in an operation environment in which multi-source heterogeneous power resources participate in scheduling cooperatively, market rules change frequently and load fluctuation is violent.

The invention discloses an edge computing node dynamic load balancing method based on a multi-agent system, and relates to the technical field of node load balancing. According to the edge computing node dynamic load balancing method based on the multi-agent system, the current computing power communication data and the operation environment data of each edge computing node are collected, the operation load index of each node is analyzed, and whether an overload node exists or not is judged; if an overload node exists, a plurality of nodes adjacent to the overload node are obtained, a task migration candidate set is screened out, finally, a target node is determined from the candidate set, and task migration operation is executed; the operation load index of the edge computing node is dynamically quantified by collecting and comprehensively analyzing multiple parameters such as the CPU utilization rate, the memory occupancy rate, the communication delay, the temperature rise rate, the I / O blocking rate, the power consumption fluctuation rate, the cache write-in waiting time and the vibration disturbance amplitude in real time. Compared with a traditional single index or fixed threshold mode, the method can identify the node overload state more accurately and timely.

Disclosed in the present invention is a fully automated log analysis and fault handling system and method based on an NLP large model. The method comprises: collecting a service state, an operating environment, and log files; extracting and generating log summaries from the log files, extracting key information from the log summaries to obtain state information of a service process; if an error is fed back, the NLP large model performing fault analysis on the error by using the service state and the operating environment as prior knowledge, and recording upstream and downstream key information involved in the error; on the basis of the upstream and downstream key information involved in the error, finding a fault cause and providing a fault handling action; and then executing a plan on the basis of the fault handling action. Log collection of the present invention is not limited to a prescribed format, and an NLP large model using a service state and an operating environment as prior knowledge is introduced for fault analysis.

Systems and methods for mathematical modeling of the hardware and software stack of commodity computer platforms are provided, enabling provable guarantees on memory, device, and program execution. This approach addresses the technical problem of reliance on system agents that rely on implicit trust in the operating environment, which can be exploited by sophisticated attackers using complex threats such as memory access exploits and code / data integrity exploits. The solution provides a proactive, mathematically-backed security solution that eliminates entire classes of cyberattacks by design, ensuring realizable guarantees on commodity computer platforms running hardware and software stack elements at the lowest operating level. This approach has significant advantages over current reactive cybersecurity methods, including reduced complexity and overhead, and increased confidence in the integrity of the system. The solution's main uses include providing mathematically-backed security and availability guarantees for critical infrastructure, financial institutions, and other organizations vulnerable to cyberattacks.

The invention discloses an operating system health assessment method and system based on multi-dimensional index dynamic weighting, and the method comprises the steps: collecting the state of each hardware module, calculating the index, carrying out the weighted summation to obtain the score of the hardware module, adjusting the weight parameter of each hardware module through combining with the real-time load characteristic or business priority, and carrying out the real-time evaluation of the health of each hardware module. Performing weighted summation on the scores of the hardware modules to obtain a hardware health score; software state information in the operating system is collected, scores of all software modules are calculated, the software modules comprise key components, key services and key processes, and the scores of all the software modules are weighted and summed to obtain software health scores; and performing weighted summation on the hardware health score and the software health score to obtain a health score of the operating system so as to determine the health state of the operating system. The invention aims to solve the systematic defect in the existing health monitoring technology system, improve the comprehensive evaluation capability of the health evaluation of the operating system, and dynamically adapt to the change rule of the actual operating environment.

The invention provides a security verification method for a large model service operation environment, a medium, equipment and a product, and relates to the technical field of computers, large model services are deployed in a container group created in a virtual machine, and the virtual machine is deployed in a hardware-based trusted execution environment, so that the security verification of the large model service operation environment is realized. The method comprises the following steps: acquiring environment measurement corresponding to a running environment of a large model service through a remote attestation service deployed in a hardware-based trusted execution environment, the environment measurement at least comprising a first measurement corresponding to the trusted execution environment in which a virtual machine is located and a container measurement under a container stack dimension corresponding to a container group; the remote attestation service generates a remote attestation report according to the environmental metrics to enable a user to validate the security of the operating environment through the remote attestation report. According to the invention, not only can the attack from the IaaS layer be shielded, but also the credibility verification under the dimension of the virtual machine and the credibility verification under the dimension of the container stack can be provided, so that the credibility of the user to the service provided by the service provider is improved.

The invention provides a visualization system capable of synchronously displaying multiple types of data according to time. Comprising a distributed service cluster composed of a micro-service, a user management micro-service, a data transmission micro-service, a data storage management micro-service, a data extraction micro-service, a data visualization display micro-service, a data visualization template management micro-service and a resource monitoring micro-service; the micro-services are packaged in a containerized manner and interact by adopting a lightweight communication protocol, and automatic deployment and dynamic expansion are realized through a container arrangement tool; the system is provided with a basic parameter set with customizable micro-service configuration and a graphical configuration interface which are used for cooperatively generating a system operation environment configuration strategy. The user management micro-service establishes a multi-dimensional authority system based on a role access control model, and records an operation log to realize audit tracking; the data transmission micro-service integrates a plurality of heterogeneous data access modes, carries out transmission process verification and carries out secure channel transmission through the service gateway.

System and methods are disclosed for providing unforgeable telemetry on computer platforms. Mathematical modeling and theorem proving are utilized to guarantee the integrity of telemetry probe execution flow and trigger, thereby preventing circumvention and tampering of logged probe data. In contrast to current state-of-the-art solutions that rely implicitly on the operating environment, this approach provides a sound and complete assurance of telemetry output. The system enables organizations to map unforgeable telemetry probe data to industry and government cybersecurity regulatory controls, ensuring compliance therewith. This invention addresses the shortcomings of existing solutions, including their vulnerability to sophisticated attacks, operational complexity, and inability to provide unforgeable telemetry data, thereby providing a reliable and accurate monitoring output in the presence of cyberattacks on computer platforms.

The invention discloses a service node deployment method, system and device, equipment and a storage medium, and can improve the deployment and debugging efficiency of service nodes. The method comprises the following steps: acquiring MCP Server configuration information and resource configuration information of service resources; generating deployment parameters used for operating the MCP Server and the service resources; sending the deployment parameters to a target server, so that the target server deploys an operation environment corresponding to the MCP Server based on the deployment parameters; in response to a debugging instruction for the service resources, performing debugging operation based on the running environment to obtain a debugging result; under the condition that the debugging result indicates that the service resource meets the preset operation condition, a service node construction request is sent to a target server, so that the target server constructs an MCP Server node in a to-be-called state, and node metadata of the MCP Server node is generated; and receiving the node metadata sent by the target server, and registering the node metadata in the MCP Server management platform.

The invention relates to an ultra-high-speed large-flow Ethernet data generation system and method. The system comprises a software unit and an FPGA unit. The software unit is used for generating stream template data and issuing the stream template data to the FPGA unit; the stream template data comprises stream template configuration items and dynamic configuration parameters; the flow template configuration item comprises protocol header information, scheduling configuration information, frame length configuration information and load configuration information; the dynamic configuration parameters comprise dynamic jump configuration information, routing table configuration information and the like; and the FPGA unit is used for storing, reading and calculating the issued stream template data, realizing intra-frame jump value calculation, message and IP head checksum generation, Ethernet frame construction and transmission. Through combination of software and hardware methods, the demand quantity of hardware resources can be reduced, the consumption of logic resources of the FPGA unit can be reduced, the phenomena of high and low speed operation environments, network congestion and the like in the existing network can be simulated, and diversified simulation environments can be provided.

The invention discloses a performance testing method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of performance testing, and the method comprises the steps: generating a target load of a current cycle according to the cycle sequence of the current cycle through a constructed load generation model; or, the target load of the current period is obtained through the PID controller according to the target load and the actual load of each historical period, the target load of each period can be dynamically generated, and the dynamic target load better fits the load of the real operation environment, so that the load of the current period can be dynamically generated. The problem that the stability of the server for deploying the AI accelerator cannot be effectively evaluated when the load with the highest power consumption is used for testing can be solved, and the technical effect that the stability of each performance index can be truly, effectively and accurately evaluated is achieved. In addition, the target test task is generated through the load of the period, the execution process of accelerated calculation of the target test task is relatively close to the real operation condition, and the obtained multiple performance indexes are relatively close to the real operation result.

The invention discloses a prospective preprocessing method and system in six-axis mechanical motion automatic control, particularly relates to the field of six-axis mechanical motion automatic control, and is used for solving the problem of insufficient track prediction and control precision in a load sudden change scene. The inertia tensor is updated in real time in combination with dual-channel Kalman filtering, dynamic inertia data are accessed, and the sensitivity of trajectory prediction to load change is improved; double-domain feature extraction of time-domain thermal stress density and frequency-domain energy dispersion is adopted, acceleration pulse layout is dynamically optimized by using a complementary integral mechanism, and the overload risk of a driver is reduced; meanwhile, the instruction dispatcher avoids cache overflow through advanced rhythm regulation and control, and continuity of instruction streams is guaranteed; the inertia model is continuously refreshed through closed-loop feedback, and synchronous evolution of inertia change and trajectory prediction is achieved; the overload shutdown risk caused by inertia lag of six-axis mechanical motion is reduced, and the adaptive capacity of the prospective preprocessing method in a dynamic complex operation environment is enhanced.

The invention relates to an intelligent equipment function reliability verification method and device, equipment and a storage medium, and the method comprises the steps: obtaining operation environment parameters and equipment state data of intelligent equipment, and carrying out the construction evaluation of a redundancy verification architecture, and obtaining an initial verification reference; acquiring real-time operation data of the intelligent equipment, and performing function association analysis on the real-time operation data and the initial verification reference to obtain function abnormality features; acquiring state information of associated equipment of the intelligent equipment, performing cross validation on the state information of the associated equipment according to the function abnormality characteristics, and performing fault analysis on the state information of the associated equipment and the function abnormality characteristics to obtain an evolution fault injection scheme; and carrying out abnormal behavior identification on the real-time operation data to obtain an equipment repair requirement, and carrying out feasibility evaluation on the equipment repair requirement based on the function abnormal characteristics to obtain a dynamic repair strategy. According to the invention, a comprehensive guarantee mechanism can be provided for reliable operation of the intelligent equipment.

Described herein is an apparatus and method for evaluating software performance. An apparatus may include at least a processor; and a memory communicatively connected to the at least processor, wherein the memory contains instructions configuring the at least processor to receive a software package; identify a safety standard; select an operating environment as a function of the safety standard; deploy the software package on the operating environment; operate a communication channel between a user device and the operating environment, wherein operating the communication channel comprises determining a performance metric for the software package; and displaying, at a display device having a user interface, the performance metric to a user through the user interface.

The invention discloses a flight training digital twin system, which comprises a data acquisition module (for collecting real-time data of an aircraft and an environment to enable virtual and actual conditions to be consistent), a model and simulation module (for creating an aircraft, an operating environment and an airborne equipment simulation model), and an intelligent analysis and control module (for analyzing operation and equipment states through big data, and analyzing and analyzing the real-time data of the aircraft and the environment to enable virtual and actual conditions to be consistent). Feedback and optimization suggestions are generated), and an interaction and training module (based on real-time data scoring feedback and immersive interaction-aid operation). According to the system, states and behaviors of physical entities such as an aircraft, a pilot and an environment are mapped to a virtual space through a high-precision virtual simulation technology, and a real-time interaction and dynamic feedback simulation training platform is constructed. The system integrates multi-dimensional data, can be linked with physical equipment, and assists a pilot in improving skills and enhancing the coping ability of complex conditions in a safe and controllable virtual environment by simulating a real scene and providing a personalized scheme, intelligent decision and risk prediction.

The invention provides a PI coating equipment motion control method and system based on reinforcement learning, and relates to the technical field of coating equipment control. Firstly, a virtual simulation platform for simulating the actual operation environment of PI coating equipment is built, and a training environment is provided for reinforcement learning. And creating and initializing a Q matrix, and designing a comprehensive reward function considering the process performance parameter weight of the PI coating equipment. Then, obtaining operation data through interaction with the virtual simulation platform, and training a Q matrix based on reinforcement learning by using the data; and in the training process, dynamically adjusting the weight of the reward function by using a feedback mechanism so as to optimize the learning process until the training is completed. And finally, inputting the current state of the PI coating equipment into the trained Q matrix to obtain an optimal action, and guiding the PI coating equipment to operate. Motion control over the PI coating equipment is achieved, and the coating quality and efficiency are improved.

The invention discloses a building equipment maintenance demand linkage detection and evaluation system and method, and relates to the technical field of intelligent operation and maintenance of building equipment, and the system comprises an isomorphic equipment cluster division module, a group data flow collection module, a group behavior baseline learning module, an individual deviation degree calculation module, and a maintenance decision generation module. Equipment with consistent function attributes and operation environments is classified into the same cluster, data are classified according to different working conditions on the basis of historical operation data provided by a group data flow acquisition module, group average operation parameters, parameter fluctuation ranges and probability distribution characteristics under each working condition are calculated, a dynamic group behavior baseline model is generated, and the dynamic group behavior baseline model is established. With the continuous updating of new data, the normal behavior mode change of the equipment under different working conditions can be reflected in real time, and when the individual deviation degree calculation module calculates the individual equipment deviation degree according to the model, the accuracy and timeliness of the calculation result can be ensured.

The invention relates to an operation guiding method based on user behavior analysis. The method comprises the following steps: analyzing to obtain a user operation purpose, and classifying and recording the user operation purpose as an operation guiding template; obtaining an interface coordinate of the interaction element in the current presentation interface based on the identification number; obtaining an operation purpose of a currently logged-in user, and searching and presenting personalized operation guidance; carrying out user behavior and related data collection on the currently logged-in user; key indexes of the user completing the operation are counted, and evaluation and suggestions of the user on operation guidance are recorded. According to the method, the user operation purpose is determined through multi-dimensional analysis, the operation guide template is constructed, and highly personalized operation guide is provided for the current login user; establishing a dynamic updating mechanism of unique identification numbers and interface coordinates of the key interaction elements, and ensuring the accuracy and stability of guiding; the adaptive templates are screened according to user roles, permissions and operation environments, proper guidance and prompts are provided for users with different proficiency degrees, and the operation efficiency of the users is improved.

The invention discloses a scheduling and approval process control method and device for digital product online leasing, and the method specifically comprises the steps: carrying out the cloud native operation environment preparation, building a process control system based on a workflow engine capable of being arranged, carrying out the system initialization, and carrying out the operation of a cloud server; comprising the steps of initializing a lease process engine, an equipment resource scheduling module, an approval strategy and credit engine and a performance monitoring and state management system; and then a lease application and process control method, an equipment scheduling and conflict detection method, an examination and approval execution and process driving method and a performance monitoring and state write-back method are designed in sequence. After a user submits a leasing request, generating an approval process and distributing the approval process to an approval node; executing resource allocation and locking after the approval is passed; an event-driven mechanism is adopted to manage state circulation of all stages of leasing, and reverse-driven scheduling adjustment of approval results is supported. According to the invention, the approval efficiency of online renting of digital products is improved, the manual intervention cost is reduced, and the rationality and traceability of equipment resource configuration are guaranteed.

The invention provides an engineering machinery working environment layered modeling and planning method and system, and the method comprises the steps: carrying out the modeling based on the scanning point cloud data of an engineering machinery working region, the geometric point cloud of an object in the working region, and the aerial photographing image and aerial photographing point cloud data of the working region; a bottom geometric perception layer, a middle semantic planning layer and an upper topological navigation layer are obtained, and a corresponding model is reconstructed when an object moves, so that the contradiction between high-precision calculation power waste and low-precision modeling insufficiency caused by a current single-precision map is solved, the modeling calculation efficiency is improved, and the method can be expanded to different complex scenes.

Provided are systems and methods that facilitates cross-correlation among alerts within different systems in a complex operating environment. In one example, a method may include receiving a plurality of alert messages generated by a plurality of systems within a distributed and shared operating environment and storing the plurality of alert messages, identifying a subset of alert messages among the plurality of alert messages that are correlated based on relationships identified from the subset of alert messages, generating a description of a root cause of the subset of alert messages based on execution of an artificial intelligence (AI) model on the identified subset of alert messages, and displaying the description of the root cause via a user interface.

The invention provides an industrial equipment state real-time monitoring method and system based on edge computing. The method comprises the following steps: acquiring a time sequence sampling tensor and a window oscillation factor of target industrial equipment with limited edge computing resources; extracting a change intensity value of each channel from the time sequence sampling tensor; calculating the state offset degree of the target industrial equipment between two continuous sampling periods, and constructing a state space representation structure; determining a sampling decision probability according to the state space representation structure, judging a state sampling frequency of the edge industrial equipment based on the sampling decision probability, and recording a sampling action corresponding to the state space representation structure; and acquiring the high-frequency state fingerprint vector, matching the high-frequency state fingerprint vector with the state fingerprint database of the current state fingerprint vector, identifying the state of the target industrial equipment in the current edge node, and performing updating for continuous adaptation of the adaptive ability of the edge node and the operating environment.

A system for providing a safety critical operating environment container architecture, the system including a computing device having a memory communicatively connected to at least one multi-core processor, the memory containing instructions configuring the processer to receive at least a software module to be executed on the at least one multi-core processor, create a separate virtual environment for the at least a software module, wherein creating the virtual environment further includes generating a virtualization layer and allocating a dedicated private static memory space through the virtualization layer, wherein the separate virtual environment includes a dedicated operating system, integrate the at least a software module into the virtual environment by instantiating, the software module into at least one software container, wherein the at least one software container includes a plurality of dedicated software packages and execute the software module on each software container for each virtual environment.

The invention discloses a micro-front-end-oriented universal basic capability adaptation method and device and a storage medium, and the method comprises the steps: determining a sub-application which needs to be loaded at present, and obtaining the feature parameters of the sub-application; calculating the characteristic parameters through a preset adapter matching algorithm, and determining an adapter matched with the sub-application according to a calculation result; setting configuration items of the adapter according to the characteristic parameters of the sub-applications; and when the sub-application is activated, mounting the page content of the sub-application to a micro-front-end framework for display through the adapter. The universal micro-front-end adapter provided by the invention can automatically carry out front-end framework adaptation according to the sub-application framework and judge the adopted micro-front-end technology and base implementation according to the operating environment, the adaptation problem of different micro-front-end technology frameworks and bases is solved, the difference of gateway authentication, request headers and the like is processed through the adaptive requester, and the adaptability of the micro-front-end technology frameworks and bases is improved. The flexibility and expansibility of integration of the micro-front-end frame are improved.

A second apparatus having a second operating environment that is on a second OS operating as a host OS and that is on a guest OS, the second apparatus obtain a second IP address of the second apparatus through a second API different from a first API on the basis of an operating environment of a predetermined program being the second operating environment; execute second determination processing of determining whether the second apparatus belongs to a first network, using the second IP address obtained through the second API; and execute first processing on the basis of the second apparatus being determined to belong to the first network in the second determination processing, and execute second processing on the basis of the second apparatus being determined not to belong to the first network in the second determination processing.

The invention discloses a project management system based on a SpringBoot micro-service architecture. The project management system comprises an application layer, a support layer and a basic platform, the application layer comprises a user portal function module, and the user portal function module comprises a user login module used for providing a login interface; the achievement consulting module is used for supporting a user to retrieve project achievements in the system through keywords, displaying a related achievement list and providing excellent achievement displaying and downloading functions; the project filling and reporting module is used for supporting a user to fill basic information of a project or upload an attachment to form a project manuscript on line based on a template; the project review module is used for supporting initial review, expert review, summarized review, file uploading and batch export of project manuscripts; the support layer is used for providing a project filling and project review circulation process and a data management function, and the basic platform is used for providing an operation environment and hardware support. According to the invention, a project management solution which is easy to operate and efficient and stable to operate can be provided for a user.

The invention discloses a browser front-end component intelligent classification method and system based on element perception, and relates to the technical field of front-end component intelligent classification, and the method comprises the following steps: executing dynamic structure completion on an incompletely rendered DOM region through a preset structure prediction model based on a trajectory data stream, and generating an enhanced DOM structure chart; extracting first data of each candidate component area in the enhanced DOM structure chart, the first data including structural features, behavior features and visual features, and generating a component semantic embedding vector; constructing a context semantic map based on the component semantic embedding vector, outputting an initial classification result, and performing context correction on the initial classification result; and mapping the corrected initial classification result to a front-end interface, and outputting a real-time classification result. According to the method, a loading track data flow modeling and structure dynamic complementing mechanism based on a browser operation environment is introduced, so that the structure restoration accuracy and modeling robustness of a complex component area in a front-end page are remarkably enhanced.

The embodiment of the invention discloses a compliance detection method, device and equipment. In the embodiment of the invention, a compliance detection task of an application program is obtained; static task initialization and dynamic task initialization are respectively performed according to the compliance detection task, dynamic analysis and static analysis are respectively performed on an installation package of the application program, the static initialization is used for configuring a running environment of a static analysis engine, and the dynamic initialization is used for configuring the running environment of the static analysis engine; performing dynamic analysis on the installation package to generate structured privacy policy content; meanwhile, performing static analysis on the installation package to generate static analysis data; and inputting the structured privacy policy content and the static analysis data into a large language model, performing privacy policy consistency judgment, and generating a consistency judgment result. By means of the method, efficient and accurate compliance detection can be conducted on the application program.

The invention discloses a localized cloud platform security optimization method based on a trusted execution environment, which is suitable for a multi-tenant computing and key business data security protection scene of a localized cloud platform. Comprising the following steps of executing security startup and measurement verification on a domestic chip, constructing a hardware root trust chain, loading a trusted execution environment, performing sensitivity evaluation and grading on tenant tasks, and dynamically scheduling the tasks related to privacy or key data to a TEE (Trusted Execution Environment) for execution; and performing task data encryption and decryption and dynamic key management, and performing multi-level permission verification on the access request. According to the method, hardware-level security isolation and data protection during operation of the localized cloud platform in a multi-tenant operation environment are realized, and the credibility and protection capability of the platform in the links of task scheduling, encryption calculation and remote verification are remarkably improved.

The invention relates to the technical field of terminals, and provides a compiling method, electronic equipment and a computer readable storage medium, the method comprises the following steps: obtaining L types of shader source codes, the L types of shader source codes are source codes corresponding to shaders of L applications, and L is an integer greater than 1; determining a public source code from the L shader source codes, wherein the public source code is a common part in the L shader source codes; the public source code is compiled to obtain N kinds of public executable codes, the N kinds of public executable codes are used for adapting to N kinds of operation environments, and N is a positive integer; and sending a target public executable code to a second device, wherein the target public executable code is one of the N public executable codes matched with the operating environment of the second device. According to the method, the probability of frame loss and jamming in the picture rendering process can be reduced, and the picture rendering performance can be optimized.