17results about How to "Reduce communication" patented technology

The invention relates to the technical field of power system automation, and discloses a cooperative control method, system and device for inverters in a power distribution area and a medium, and the method comprises the steps: carrying out the identity authentication of the inverters in the power distribution area through constructing a distributed authentication platform, and constructing a logic neighbor network of the inverters; determining the operation capability of the inverter according to the physical constraint and power operation data of the inverter, and constructing a multi-time scale coordination framework according to the real-time demand of the power distribution area to determine a bidding strategy set of the inverter; constructing a transformer area clearing model considering the safety of the power distribution transformer area, and solving the transformer area clearing model according to the logical neighbor network and a distributed optimization algorithm to obtain a power control instruction of an inverter; the distributed authentication platform monitors the operation state of the power grid in the power distribution area, and when the risk is triggered, a security check algorithm is started to correct the power control instruction, and a power correction instruction is obtained to control the inverter to execute; and under the condition of considering the safety and the cost, the refined cooperation of the district level is realized.

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

The present application relates to the technical field of park energy data management, and particularly relates to a zero-carbon smart park comprehensive energy method and system based on big data, wherein the method comprises the following steps: S1, generating a carbon equity unit record; S2, establishing a corresponding source summary for each carbon equity unit; S3, writing the identification information corresponding to the transferred carbon equity unit into the restriction identification set corresponding to the first node; S4, generating a merged source summary; inheriting the source summary before splitting; S5, performing backflow risk verification based on the source summary attached to the to-be-transferred carbon equity unit and the identification information in the restriction identification set; S6, using the registration result for comprehensive energy scheduling and carbon accounting; the method effectively avoids the loss of source information and the risk of repeated offsetting caused by merging and splitting, and facilitates linkage with comprehensive energy scheduling and carbon accounting, thereby improving the real-time performance, implementability and system autonomy of zero-carbon smart park carbon equity management.

This invention relates to the field of enterprise digital management technology, and particularly to an enterprise digital operation management method and system. The method includes: acquiring business activity data, extracting the interaction strength between business activities, and clustering multiple business activities into multiple intelligent agents; extracting technical metadata from the target system's data dictionary and interface documents, constructing a metadata knowledge graph using the technical metadata, and providing data interfaces for the intelligent agents using the data knowledge graph; based on the data interfaces, each intelligent agent uses a probability prediction model to generate a probability distribution of future external variables, and makes individual decisions based on the probability distribution; determining whether there is shared resource coupling in the individual decisions of two intelligent agents, and if so, introducing a collaborative mechanism to correct their independent decisions through shadow prices so that the individual decisions reach global optimality.

The invention discloses a spacecraft adaptive sliding mode saturation formation control method and system based on SE (3), and belongs to the technical field of spacecraft control. The method comprises the following main processes: modeling a system model by utilizing SE (3), and describing the attitude and orbit of a spacecraft; performing error design based on attitude dynamics to obtain a configuration error function; designing a self-adaptive sliding mode saturation controller based on kinematics and dynamics models of a rigid body dynamics system of SE (3) in combination with a configuration error function; a periodic event triggering strategy is provided, and the control rate of the spacecraft is periodically updated. According to the method, event trigger control and periodic sampling data control are combined through the self-adaptive sliding mode saturation controller, the Zeno phenomenon is avoided so as to reduce resource consumption, the unified lower bound of interaction time is deduced, high-precision control of the spacecraft during on-orbit task execution is guaranteed, and the method has the advantages of being simple in structure and convenient to operate. And meanwhile, the formation collision phenomenon is also avoided.

The application provides a log information-based system simulation method and device, equipment and a storage medium, wherein the method comprises the following steps: printing the request interface and parameters of an application system and a response result into the system log of the application system with matched labels; acquiring the interface list and state requirements of the application system and acquiring the system log of the application system; extracting data from the system log, extracting request data and response data, and forming a data pair; constructing a third-party simulation system based on an MLP regression model, and training the MLP regression model by using the data pair as the input parameter of the MLP regression model. The log information-based system simulation method provided by the application can generate a reliable simulation system by analyzing the application system log without detailed interface documents and instruction manuals, which is beneficial to reducing communication problems and cooperation costs and improving the development and test work efficiency.

The invention belongs to the technical field of blockchain security, and discloses an industrial Internet of Things anonymous responsibility-traceable data editing method and system based on a blockchain. The method comprises the following steps: generating a chameleon Hash trap door by a trusted mechanism, splitting the chameleon Hash trap door into shares by using threshold secret sharing, distributing the shares to verifier nodes, and initializing a dynamic accumulator; the owner encrypts the production data and formulates a modification strategy, and generates a hash value and an initial voucher by using chameleon hash and uploads the hash value and the initial voucher to a chain; the modifier initiates a request containing zero-knowledge proof, after verification is passed, the verifier node generates partial vouchers by using the trap door share, and the modifier aggregates the partial vouchers into a one-time voucher to complete editing; and the trusted mechanism decrypts the identity of the malicious modifier, moves the malicious modifier out of the dynamic accumulator and updates the revocation list. According to the method, trap door leakage is prevented through a threshold sharing mechanism, zero knowledge proof and a dynamic accumulator are combined, and effective tracking and permission revocation of malicious behaviors are realized while identity privacy of a modifier is guaranteed.

The invention discloses a trusted cross-organization process mining method and system based on a block chain, and the method comprises the steps: filtering an original event log, and obtaining an interaction event log; private and public process models are mined by using the original and interactive event logs; the public process model after block chain smart contract verification is linked and synchronized among the nodes; any organization submits the merging operation as a transaction to a block chain, and the block chain is driven by a smart contract to fuse the public process model of each collaborative organization into a global public process model and synchronize the global public process model; any organization submits the simplified operation as a transaction to a block chain, the block chain is driven by a smart contract, and public process model fragments related to the own side and the own side related collaborative organization are obtained and synchronized according to global public model simplification; and integrating the public process model fragment and the own private process model under a block chain to generate a cross-organization collaboration process model from a local organization perspective. According to the invention, mining and optimization of cross-organization business processes are facilitated.

This disclosure relates to a method, apparatus, device, and medium for dynamic multi-environment publishing of WeChat Mini Programs. The method includes: obtaining a configuration file set and a private key certificate; packaging and compressing the configuration file set and private key certificate; sending them to the object storage server corresponding to the WeChat Mini Program platform; responding to receiving the target code to be uploaded on the code hosting platform; retrieving the target WeChat Mini Program parameter set corresponding to the target code from the object storage server; modifying the target configuration file corresponding to the target WeChat Mini Program parameter set according to the target code; and transmitting the target configuration file to the WeChat Mini Program publishing script according to the target private key corresponding to the target configuration file, so that the WeChat Mini Program publishing script publishes the Mini Program source code in the target configuration file to the WeChat Mini Program platform; and receiving the upload notification result sent by the WeChat Mini Program publishing script. This automates the code upload process, reducing the manual cost of code transmission in multiple environments.

This invention discloses a distributed inference method for large language models based on intra-layer parallelism and communication quantization. The method relates to the field of distributed inference technology and includes the following steps: computational resource efficiency assessment and control; network environment adaptation assessment; and inference result generation and output. This invention, in distributed inference of large language models, first assesses the efficiency of computational resource utilization; if the efficiency is insufficient, it optimizes synchronous communication and load balancing; then it assesses the network environment adaptability; if the adaptability is insufficient, it optimizes the network topology and transmission protocol; finally, it outputs the inference result. This achieves efficient resource utilization and adaptive control in heterogeneous network environments, improving the practicality of distributed inference for large language models and solving the problem in existing technologies where the existing parallel inference schemes for large language models cannot achieve a balance between high computational efficiency and low network dependence, resulting in low practicality of distributed inference for large language models.

This invention discloses a lattice-based cryptographic authentication and key negotiation method for cross-domain communication in the Internet of Vehicles (IoV). The invention designs a lattice-based certificateless aggregateable signature, which allows a trusted authority (TA) to guarantee the reputation of cross-domain communication users without increasing communication overhead. Furthermore, the invention designs a modular lattice-based certificateless key encapsulation method, achieving secure key distribution without introducing certificate management overhead or key escrow issues. Finally, the invention organically combines these two mechanisms to achieve lightweight and efficient post-quantum cross-domain bidirectional authentication and key negotiation. This invention reduces communication overhead, solves the key escrow problem, and achieves secure authentication and key negotiation resistant to quantum computing attacks.

The application relates to the technical field of industrial internet of things, and discloses an industrial control system, which comprises an intelligent gateway and a plurality of controllers; the plurality of controllers are connected with each other, each controller is used for generating a new block according to industrial data uploaded by an industrial device and broadcasting the new block; each controller is also used for receiving the new block broadcast by the remaining controllers, verifying the new block after finding the unique identifier of the controller in a unique identifier list, and obtaining a first verification result; the intelligent gateway is connected with each controller respectively, is used for receiving the new block broadcast by each controller, verifying the new block, and obtaining a second verification result; and the intelligent gateway is also used for uploading the new block to a block chain after judging that the new block is legal according to the first verification result and the second verification result. Through the above mode, the communication and calculation overheads of an edge-end industrial control system are reduced.

The application discloses a kind of federal learning communication methods for cloud radio access network, its characteristics are the method includes: S1, constructs the federal learning framework for cloud radio access network, the federal learning system of cloud radio access network and quantization neural network, training, cloud radio access network communication model;S2, convergence analysis is carried out to federal learning framework;S3, construct federal learning system energy model, and carry out convergence analysis, according to the convergence result and energy consumption model constructs an optimization problem of system energy minimization, and solve the problem by alternating optimization joint optimization.This application compared with prior art has by quantization neural network using low bit data reduces the energy consumption when training, by using the characteristics of high scalability, throughput and coverage of cloud radio access network, realize the federal learning framework of low energy consumption, solve the problem of large energy consumption of wireless federal learning.

This invention relates to a two-stage federated distillation and large model fine-tuning method based on differential privacy, belonging to the fields of artificial intelligence security, federated learning, and differential privacy technology. The method includes: Step 1, federated pre-training based on complexity adaptive budget management and momentum orthogonal subspace directional noise addition; Step 2, local dataset distillation based on frequency domain-aware complex plane anisotropy noise addition; and Step 3, cloud-based large model fine-tuning and end-to-end privacy compliance assessment based on noise prior-driven adaptive rank. This invention achieves precise allocation and tracking of the privacy budget in both the federated pre-training and data distillation stages by introducing mathematically provable RDP differential privacy protection. It completes high-fidelity generation of the distilled dataset and secure large model fine-tuning while strictly protecting the privacy of the client's original data, which is of great significance for promoting the secure and efficient deployment of large models in distributed privacy-sensitive environments.

The application provides an MCU software integrated system for a DLP vehicle-mounted projection headlamp, a voltage monitoring module can measure and monitor input voltage; a hibernation wake-up control module can control the wake-up and hibernation of the DLP headlamp; a CAN communication module is used for realizing the interaction between a vehicle-mounted host and the DLP headlamp; a diagnosis DTC module comprises a diagnosis service sub-module and a DTC function sub-module; an IIC communication module can initialize and configure the register of a Deserializer chip and configure the light adjustment parameter of a DMD Controller module; and a light adjustment control center module can adjust the light of the DLP headlamp. The software functions of MCU1 and MCU2 are integrated on the same MCU, one MCU is reduced, the complexity of the system is reduced, and the cost of the system is saved.

Aspects of the present invention relate to a control system (100, 500) for a voice assistant system (200) for implementing actions (520, 530, 540) associated with a vehicle (240), the control system (110) comprising one or more controllers (110), the control system comprising an interface (140) configured to receive a request (505) from the voice assistant system (200), wherein the request is indicative of a task requested by a user of the voice assistant system (200), and processing means (120) arranged to execute, in dependence on the request, a task handler (510) corresponding to the task, wherein the task handler (510) is arranged to cause the control system (100) to perform a plurality of actions (520, 530, 540) associated with the task, to generate a response in dependence on an output of at least some of the plurality of actions (520, 530, 540) and to output the response via the interface (140) to the voice assistant system (200).

The application provides an AR real scene map dynamic superimposed label method, system, device and medium, which is applied to a webpage client and includes the following steps: obtaining video decoding information; obtaining AR label information by analyzing SEI frame information in the video decoding information; generating and rendering an operable label layer according to the AR label information; changing the operable label layer in response to user operation; obtaining new AR label information according to the changed operable label layer; outputting the new AR label information to a backend server to enable the backend server to update SEI frame information according to the new AR label information; and re-rendering the operable label layer in response to update information sent by the client after listening to the updated SEI frame information. Through webpage program development, the AR real scene map dynamic superimposed label method provided by the application has cross-platform and dynamic properties, has low development cost, and is flexible to publish. The preview layer and the operable label layer of the application are decoupled, the program complexity is reduced, and the business flexibility is improved.