166 results about "Consensus algorithm" patented technology

The invention relates to the technical field of energy storage systems, and provides a self-adaptive power distribution method and system for multiple energy storage units of an island microgrid. According to the invention, a discrete consistency algorithm is adopted to realize coordination control of multiple units, each unit only exchanges information with adjacent units, and power distribution targets of all the units are converged to a consistent value through iterative computation, so that the communication bottleneck and the single-point fault risk of centralized control are avoided; according to the invention, a complete fault-tolerant processing mechanism is designed, the operation state of each energy storage unit is monitored in real time, topology updating and power redistribution are automatically carried out when a unit fault is detected, and the self-healing operation of the system is realized. Experiments show that compared with a traditional method, the method has remarkable advantages in key performance indexes such as capacity balance among energy storage units, system operation efficiency, communication overhead and fault recovery time, and the operation efficiency and reliability of the island microgrid system are remarkably improved.

The invention relates to the technical field of power systems and energy management, and discloses an energy-carbon integrated virtual power plant multi-agent collaborative management and control method and system, and the method comprises the steps: S1, constructing a three-layer control architecture comprising a resource sensing layer, a region coordination layer and a global optimization layer; s2, establishing an energy-carbon coupling state space model, and outputting a target optimization result by taking photovoltaic output, energy storage charging and discharging power, a load demand elastic coefficient and a carbon emission right transaction volume as input variables; s3, generating a scheduling instruction by adopting a rolling optimization strategy; and S4, realizing multi-agent collaboration through a distributed consistency algorithm, exchanging power deviation information by each node based on a local constraint condition, and carrying out iterative calculation until the power deviation of all nodes is less than 1%. A three-layer control architecture is constructed, scheduling lag is shortened through decision making and stage processing of the global optimization layer after preprocessing of the regional coordination layer, the limitation of a single node is broken through through cross-regional coordination, and the overall operation efficiency of the virtual power plant is enhanced.

The invention discloses a Raft consensus algorithm-based dynamic management method and a related device, and relates to the technical field of communication, when a slave node server does not receive a heartbeat packet of a master node server overtime, the slave node server is automatically converted into a candidate node server and broadcasts an election request; and if the number of the received feedback information for confirming that the candidate node server is changed into the master node server is greater than half of the total number of all the slave node servers, determining that the candidate node server is changed into the master node server. The delay risk that a master-slave centralized architecture depends on manual monitoring and manual switching is thoroughly eliminated, fault discovery and response are solidified on an algorithm level, and automatic disaster recovery without human intervention is achieved.

The invention discloses a dynamic optimization method for a USV-AUV collaborative navigation network topological structure based on a consensus algorithm, and relates to the technical field of collaborative navigation of an ocean unmanned system. Comprising the steps that according to a positioning equation between the unmanned surface vehicles and the autonomous underwater vehicles, the relation between the positioning error of the autonomous underwater vehicles and the distance measurement error between the unmanned surface vehicles and the distance measurement error between the autonomous underwater vehicles and the position error between the unmanned surface vehicles is constructed through a partial differential method; designing a positioning precision evaluation function by using an optimal estimation criterion; solving an optimal solution for the evaluation function by using an alternating direction multiplier method, and performing consistency estimation on a formation center and adjusting dynamic formation parameters through a consensus algorithm to obtain an optimal topological structure; and acquiring the number of the formation aircrafts in real time, if the number of the formation aircrafts changes, performing iteration, and if the number of the formation aircrafts does not change, keeping a topological structure. The method is high in dynamic adaptability, constraint collaborative optimization is achieved, the safety margin is improved, and robustness is enhanced.

The invention provides an eyesight health data management and privacy protection method based on a block chain, and the method comprises the steps: verifying the role identity of a requester through an intelligent contract if a query request is detected in an encrypted archive structure, judging whether the role identity accords with a preset hierarchical authorization rule or not, and obtaining an authorization verification result; after the filtered data response is obtained, generating a hash value of query operation by adopting an encryption algorithm, and determining a unique identifier of the access so as to facilitate subsequent tracking; broadcasting the generated hash value and access details to all nodes of the block chain network through a consensus algorithm, judging whether the network is consistent or not, and obtaining a confirmed log recording block; historical access behaviors are retrieved from the confirmed log record blocks, if an abnormal access mode is found, an alarm mechanism is triggered, and a complete traceable audit path is obtained to maintain data privacy.

The invention discloses an internet protocol address access protection method and equipment, and relates to the technical field of internet. According to the scheme, the method comprises the steps that IP access records and safety related data are recorded in a tampering-free mode through a block chain distributed account book, and after a newly-added block is chained, a block chain node automatically updates a state database through an intelligent contract to maintain safety attribute information of an IP in real time. Before a terminal initiates IP access, a query request is sent to a plurality of nodes in a block chain network, after security attribute information fed back by each node is obtained, distributed verification is completed through a preset consensus algorithm, and finally an access control action is determined. A single central server is replaced by a multi-node distributed architecture, so that the risk of single-point failure is eliminated; secondly, an automatic updating mechanism driven by the smart contract greatly shortens a time window for responding to novel threats and IP redirection; and finally, all access records are publicly and transparently recorded on the block chain, so that the credibility and reliability of the system are enhanced.

The invention provides a self-adaptive data consistency maintenance method for an electric power information system based on incremental updating, and relates to the technical field of big data processing, and the method comprises an initialization step, a detection step and a feedback step. In the initialization step, a network including regional power data nodes and a distributed account book is constructed, and full power data is stored; in the detection step, power data changes are confirmed, key attributes are used for marking data, automatic conflict detection is carried out through a distributed consensus algorithm, solutions for coping with conflicts are dynamically selected, and then an incremental updating mechanism is adopted for synchronously changing the data; in the feedback step, a monitoring system with a closed-loop feedback mechanism is established, the data consistency state is automatically tracked when the electric power data is changed, and abnormity is recognized. Compared with a traditional data synchronization method which needs to synchronize full data, the method provided by the invention only synchronizes the changed data fragments through an incremental updating mechanism, thereby ensuring the consistency of the data, remarkably improving the data processing efficiency and saving the network bandwidth.

The invention provides a multi-agent cooperative medical treatment system and method based on dynamic weighted consensus. The method comprises the following steps: acquiring original medical data of a patient from a hospital heterogeneous information system; the dynamic weight of each specialized agent is calculated based on the domain correlation, the evidence authority level and the historical decision accuracy, and opinions are fused and processed and conflicts are processed through a weighted consensus algorithm; and recording the corresponding subsequent determination result of the final processing scheme, updating the historical decision accuracy of each specialized agent, and providing an efficient, accurate, comprehensive, personalized and explainable diagnosis and treatment scheme for each patient.

The invention relates to a practical consensus algorithm for file resource sharing, which comprises reputation-driven task allocation: according to reputation values calculated in real time, nodes with high reputation values are preferentially selected by the algorithm to form a core consensus group to execute the most critical consensus task, and the number of nodes participating in core communication is remarkably reduced. And protocol flow optimization: fundamentally reducing the communication complexity to O (n) level by limiting the scale of the core consensus group and reconstructing a message transmission path. And node state dynamic autonomy: the algorithm has real-time evaluation and dynamic adjustment capabilities on node types. The reputation model continuously monitors node behaviors, can automatically perform degradation processing on low-reputation or fault nodes, and can timely discover and safely isolate or delete bad nodes through a specific mechanism without restarting the system. Through test verification, the reliability, safety, higher throughput and lower delay of the consensus algorithm are verified.

The invention discloses an abnormal transaction identification method and device based on edge node collaboration and electronic equipment, and relates to the technical field of distribution.The method comprises the steps that an encrypted transaction feature vector transmitted by an infrastructure end is received, a transaction request is generated based on the encrypted transaction feature vector, the transaction request is sent to a plurality of adjacent edge nodes, and the edge nodes send the transaction request to the infrastructure end; and receiving collaborative verification results of a plurality of adjacent edge nodes on the transaction request based on a preset consensus algorithm, performing abnormal transaction identification based on the collaborative verification results of all adjacent edge nodes by using a gradient boosting decision tree model, and executing the transaction request under the condition that the transaction identification result indicates that the transaction is a normal transaction. And a transaction execution result is fed back to the basic equipment end. According to the invention, the technical problem that the protection capability of a localized single-node detection system is easy to reduce for large-scale network attacks or fault conditions of individual nodes in the prior art is solved.

Decentralized information-security (IS) mitigates against cross-channel threats vectors with a photonic quantum computing machine (PQCM). Threat signals are communicated to consortium members. Live model libraries regarding the threats, characteristics, metadata, model solutions, etc. are in distributed ledgers. PQCM extracts metadata and analyzes permutations to identify configuration(s) with the highest propensity to mitigate the threat. PQCM determines optimized set(s) of the threat-vector mitigation models for the configuration(s). PQCM auto-generates, dynamically by AI / ML based on the optimized set, IS rules for the configuration. Updated threats, threat characteristics, model configurations, IS rules, etc. for the cross-channel threat can be stored in distributed ledger blockchains, shared with consortium members, and deployed to prevent the threat. Nodal consensus algorithms may be used to reach agreement amongst consortium members to independently confirm threat signal validity, best model combinations, highest propensity scores, and proposed dynamically generated IS rules to address the threat.

Systems and methods for bias testing and remediation are disclosed. Decentralized Web Application Testing Systems use a Holochain framework to distribute testing workloads across Full Nodes and Lightning Nodes. A Holochain Node Management Application for configuring nodes, a UI Application creates test cases, and a Version Management System tracks changes. Test results are stored and analyzed in a Test Result Store, with a Bias Intelligence module detecting biases and generating additional test cases. A Consensus Algorithm validates test cases through decentralized nomination. An AI-Driven Defect Remediation System automates defect detection, root cause analysis, and remediation using AI modules. Machine learning algorithms identify patterns and anomalies, while NLP techniques generate code fixes. Predictive maintenance monitors application performance to preemptively address issues. A feedback loop mechanism continuously improves AI models through reinforcement learning. Together, these systems provide a holistic approach to web application testing and maintenance.

The invention belongs to the technical field of three-dimensional geometric measurement, and particularly relates to a three-coordinate detection data processing method and system for automobile parts, and the method comprises the steps: obtaining an actual point cloud and a standard point cloud; by calculating the maximum angle gap of the data points, screening to obtain actual and standard feature point sets; anti-noise geometric descriptors based on tangential weights are constructed for the feature points in the two sets of feature point sets respectively; matching the two groups of feature points based on the descriptors and generating an initial matching set; solving global optimal transformation from the initial matching set by adopting a random sampling consistency algorithm; and the transformation is applied to the actual point cloud, fine registration is carried out by using an iterative nearest point algorithm, and finally deviation analysis is completed. The technical problem that traditional registration depends on initial alignment and is prone to falling into local optimum is solved, and the robustness and accuracy of registration are improved.

This invention proposes a method and system for regulating an integrated energy system that considers operational cost consistency, belonging to the field of integrated energy system regulation technology. The method includes: revising the initial scheduling instructions of each cluster to determine the power to be regulated and the available regulation margin of each cluster; establishing a distributed cooperative communication network topology model of the system; using a distributed consensus algorithm to determine the consistency correction coefficient for power regulation based on the available regulation margin of each cluster; determining the operational cost consistency coefficient for power regulation based on the marginal cost of each cluster; and determining the additional regulation power of each cluster; when each cluster responds to the additional regulation power, determining the response time consistency correction parameter within the regulation cycle to update the power value of the cluster at the current moment, thus obtaining the regulation power instruction for the cluster in the next scheduling cycle. This invention improves the utilization rate of regulation resources in the integrated energy system and reduces the overall operating cost of the integrated energy system.

The application discloses a V-shaped groove weld deviation detection method based on a YOLO model and groove reconstruction in the field of welding. First, a single YOLO model is trained to synchronously identify and intercept the left and right edge windows of a groove and the center window of a welding torch in a globally collected image of a welding area. Second, the groove edge window image is subjected to a gray scale transformation and a local adaptive threshold method, and the left and right edges of the groove are reconstructed in combination with a random sample consensus algorithm and a multi-level rollback mechanism. Then, the center of the groove is located by a midpoint recursion method based on the reconstructed groove edge, and the center of the welding torch is determined according to the center window of the welding torch. Finally, the deviation between the center of the groove and the center of the welding torch is calculated, and a two-level filtering mechanism combining Kalman filtering and moving average filtering is adopted to obtain a stable weld deviation value. The synchronous positioning of the double groove edges is realized by a single model, the arc light interference is effectively inhibited by combining the local adaptive threshold and the reconstruction method, and the robustness and precision of the weld deviation detection are improved.

A point cloud processing device and a point cloud processing method are provided. The point cloud processing method includes: receiving a vertically scanned point cloud; performing a random sample consensus algorithm on the vertically scanned point cloud to obtain a fitting plane; filtering a first ground point of the vertically scanned point cloud according to the fitting plane to update the vertically scanned point cloud; and generating a processed point cloud according to the updated vertically scanned point cloud and outputting the processed point cloud.

The invention discloses a vehicle network system based on a block chain hybrid consensus algorithm DTSP-PBFT. The vehicle network system comprises a main chain, a side chain, and a vehicle, an automobile manufacturer and a road side unit which are in communication connection. The main chain is constructed and maintained by an automobile manufacturer and is used for storing privacy data or hash values of vehicles; the side chain is constructed by a plurality of road side units and is used for processing a vehicle service request and performing identity authentication by adopting a DTSP-PBFT-based hybrid consensus algorithm; the vehicle carries a vehicle-mounted unit, interacts with the road side unit and the main chain through a dedicated short-range communication protocol, and participates in the network as a side chain light node; and the road side unit is used for communicating with the vehicle, forwarding the zero knowledge proof to the main chain, and executing the flow of the DTSP-PBFT-based hybrid consensus algorithm as a consensus node. According to the method, the communication overhead in the consensus process is effectively reduced, and remarkable effects are achieved in the aspects of expansibility, safety, system throughput rate and the like.

The invention relates to a coordinate processing method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a first coordinate point set corresponding to a target point in a programming coordinate system, and obtaining a second coordinate point set corresponding to the target point in a preset actual coordinate system; performing transformation parameter calculation on the first coordinate point set and the second coordinate point set based on a least square method to obtain an initial transformation matrix; calculating the initial transformation matrix based on an error function to obtain an error value; if the error value is greater than an error threshold value, optimizing the initial transformation matrix by using a random sampling consensus algorithm based on the first coordinate point set and the second coordinate point set to obtain a first transformation matrix; performing iterative optimization on the first transformation matrix based on an iterative nearest point algorithm until an iteration termination condition is met, and obtaining a target transformation matrix; and performing coordinate transformation on the first coordinate point set based on the target transformation matrix to obtain a corresponding target coordinate point set. According to the invention, the precision of coordinate conversion can be effectively improved.

The application belongs to the technical field of block chain, and discloses a DPOS consensus algorithm method and system based on a reputation value and a strong blind signature algorithm, which comprises the following steps: judging whether a node enters a system for the first time and sorting; selecting a proxy node set according to the sorting; mutually voting between the proxy nodes, finally counting the number of votes received by each node, summing up the reputation value, and then sorting the nodes again; selecting the nodes ranked in the top 21 as a set of witness nodes, and the remaining nodes as a set of backup witness nodes; supervising the block generation process of the witness nodes, and dynamically converting with the set of backup witness nodes by using the proposed reputation mechanism; and the witness nodes pack blocks and generate blocks. The application rewards or punishes the positive or malicious behavior of the nodes, thereby restricting the behavior of the nodes and reducing the possibility of the nodes doing evil; the power is reduced in the hands of a few nodes, and the risk of centralization is reduced; the identity information of the voting nodes is avoided from being leaked, and the system security is improved.

The invention provides a container mirror image source tracing and verification method based on a block chain, and the method achieves the transparent tracing of a whole process from the construction, updating to distribution of a mirror image through the non-tampering performance and distributed storage of the block chain. Generating a mirror image unique identifier through SHA-256, and performing uplink storage on metadata; and the IPFS is adopted for multi-copy redundant storage, so that the availability is improved, and a single-point fault is avoided. And the edge node verifies the integrity of the mirror image through on-chain hash, and carries out dynamic reward and punishment in combination with a reputation management model driven by an intelligent contract to inhibit malicious behaviors. The encryption and hybrid consensus algorithm is adopted to guarantee the communication security and performance, the mirror image credibility and the system robustness are remarkably improved, and the method is suitable for distributed scenes such as cloud computing and the Internet of Things.

The application discloses a centerless distributed battery equalization device and a control method, the device is composed of a plurality of battery equalization units, each unit has the ability of battery state detection, charge and discharge control, calculation and communication with other modules. The communication between the units forms a centerless distributed collaborative network, forming a centerless distributed multi-agent system, each unit can use local information to derive a reasonable equalization strategy, and charge and discharge control is performed on the battery monomer according to the equalization strategy, so that all battery monomers are balanced. The application also discloses an improved consensus algorithm, which solves the problem of slow convergence time of the classical consensus algorithm.

The application provides a distributed offshore wind turbine control method based on a consistency algorithm, comprising: taking the distributed offshore wind turbine as a distributed intelligent agent, and obtaining total active power shortage of a plurality of intelligent agents; establishing an initial first adjacency matrix according to a communication relationship between adjacent intelligent agents, and adjusting the first adjacency matrix to obtain a second adjacency matrix; modifying an initial first Laplacian matrix according to the second adjacency matrix to obtain a second Laplacian matrix; establishing a target function taking maximization of a wind energy utilization coefficient of each distributed offshore wind turbine as an objective, and obtaining an output power increment allocated to each distributed offshore wind turbine according to the second Laplacian matrix, so that the distributed offshore wind turbine outputs corresponding output power; and the application can improve power quality and improve power control accuracy of the distributed offshore wind turbine.

The application belongs to the technical field of block chain, and provides an intelligent financial auditing system based on cross-validation of block chain, which comprises: a space-time anchoring calibration module, a cross-chain calibration node is deployed, a cross-chain unified time reference is output through a consensus algorithm and is synchronized to chain A and chain B; a multi-dimensional state proof module, chain A generates a space-time anchoring hash and a signature list, chain B confirms the asset locking state through triple verification of hash consistency, signature validity and time validity; a dynamic time window adjustment module, a historical delay library is built to calculate the initial time lock of chain A, and the time lock of chain B is dynamically adjusted; a cross-chain consensus detection module, the chain B verification node judges the asset state between chains based on RAFT consensus, and when an exception occurs, asset freezing, original route return and attacker blacklist marking are triggered; time synchronization error can be eliminated, repeated transfer attacks can be prevented, and the security, accuracy and real-time performance of cross-chain financial auditing can be improved.

This application discloses a competition rights management system, method, apparatus, and related equipment. The system includes: a blockchain network consisting of provincial nodes deployed in various provincial-level administrative regions and core nodes deployed in the Chinese Athletics Association. The provincial nodes employ the Hyperledger Fabric framework, and the nodes interact using the Practical Byzantine Fault-Tolerant (PBFT) consensus algorithm; edge computing nodes deployed at the event site, communicating with the blockchain network, for real-time collection of athlete performance, event level, and regional difficulty coefficient data; a smart contract module deployed in the blockchain network, for determining a comprehensive score based on athlete performance, event level, and regional difficulty coefficient data, and dynamically adjusting competition rights based on the comprehensive score and preset conditions; and a competition rights allocation engine coupled to the smart contract module, for generating a competition rights allocation scheme based on the comprehensive score, host city requirements, and athlete influence data.

The invention provides an optimized PBFT consensus method based on clusters and reputation, and belongs to the technical field of logistics supply chain information. The method comprises the following steps: firstly, constructing a hierarchical architecture of sensing network topology by using a dynamic reputation model and an adaptive DBSCAN algorithm, and generating a core consensus cluster for processing dense services and a bridging cluster for guaranteeing connectivity according to node positions; then, a leader is elected in the cluster according to the reputation value and topology centrality, and a global task is decomposed into a local PBFT consensus process parallel in the cluster; and finally, the reputation is updated through a dynamic feedback mechanism to punish malicious nodes. Aiming at the characteristics of the cross-border logistics large-scale heterogeneous network, the method effectively solves the structural mismatching problem of the consensus algorithm and the logistics topology, has obvious advantages in the aspects of consensus time delay, throughput and communication overhead, and remarkably improves the expansibility and stability of the system.

The invention discloses a financial data security management system and method based on artificial intelligence, and relates to the field of financial technology security management, and the system comprises a data preprocessing module, a security storage module, a risk detection module and a dynamic optimization module. The method comprises the steps of data preprocessing, secure storage, risk detection and dynamic optimization. The data preprocessing module encrypts standardized financial data by adopting a hybrid encryption mechanism in combination with symmetric and asymmetric encryption algorithms, and divides security levels through a BiLSTM and attention mechanism fusion model; the secure storage module stores the encrypted data in a block chain and IPFS dual-architecture system, the block chain adopts a practical Byzantine fault-tolerant consensus algorithm, and the IPFS stores data fragments through a Merkle-DAG structure; the risk detection module extracts long-term and short-term risk features based on a Transform-TCN fusion model and fuses the long-term and short-term risk features; and the dynamic optimization module dynamically adjusts a risk detection threshold value through a reinforcement learning algorithm to realize full-life-cycle safety management of financial data.

The invention relates to the technical field of computing power networks and distributed computing, and provides a dynamic slicing and intelligent decision-making-based computing power network efficient data transmission method, which comprises the following steps of: performing main node election by adopting a Raf consensus algorithm; based on a dynamic slicing mechanism, the main node collects key information of the distributed computing power network; judging whether a re-slicing operation needs to be executed or not according to the key information by adopting a deep reinforcement learning algorithm; adopting a data transmission method based on dynamic slicing to carry out distributed storage transmission and slicing recombination of data in a computing power network environment; based on a deep reinforcement learning algorithm, a slicing strategy is optimized through experience playback and continuous training. According to the method, a main node election and deep reinforcement learning decision mechanism is adopted, dynamic optimization of the data slice size and the transmission path is achieved, the efficiency and reliability of large-scale data transmission in the computing power network are effectively improved, and the self-adaptability and stability under the conditions of network fluctuation and node failure are guaranteed.

The application relates to a kind of digital certificate processing methods based on blockchain, belong to network communication technical field, solve the problems of lack of effective supervision of existing certificate authority power and low certificate management efficiency. Including: multiple certificate authorities are used as nodes to form a blockchain network;Any node receives a certificate management request, constructs a certificate operation request and sends it to the current master node in the blockchain network;Certificate operation request contains operation type identifier and certificate key information;The current master node carries out consensus processing on the certificate operation request based on the improved byzantine fault tolerance consensus algorithm;Wherein, a threshold signature mechanism is introduced in the consistency protocol, and a new master node is dynamically elected based on the weight value of the node in the view change protocol;When consensus is reached, the certificate key information is recorded in the block of the blockchain ledger, and the corresponding operation result is generated and returned. Dynamic supervision of the power of certificate authority and improvement of certificate management efficiency are realized.

This invention proposes a distributed anti-interference control method and system for 3D drone swarm performances, comprising: establishing a distributed communication network for each drone based on quantum key encryption and quantum entanglement links; each drone node detecting, classifying, and broadcasting interference in real time through sensor fusion to form a shared interference situation map; adaptively hopping frequencies accordingly, and automatically rerouting when the link is interrupted to reconstruct the communication topology; based on the reconstructed topology, using a distributed consensus algorithm to fuse the poses of neighboring nodes, calculating and synchronizing deviation corrections to maintain formation; for deceptive interference, initiating multi-source positioning cross-validation and switching to a cooperative positioning mode without a positioning module; simultaneously, nodes continuously monitor their health status, and low-scoring nodes trigger a distributed task takeover mechanism from neighboring nodes. This invention improves the anti-interference robustness, self-healing capability, and security of the drone swarm performance system.

This invention discloses a dynamic optimization method for the topology of a USV-AUV cooperative navigation network based on a consensus algorithm, relating to the field of cooperative navigation technology for marine unmanned systems. The method includes: constructing the relationship between the positioning error of the AUV and the distance measurement errors between the surface unmanned surface vessels (Surface UVs) and AUVs, and the positional errors between the Surface UVs, based on the positioning equations between the Surface UVs and AUVs using partial differential equations; designing a positioning accuracy evaluation function using optimal estimation criteria; obtaining the optimal solution for the evaluation function using the alternating direction multiplier method; simultaneously estimating the consistency of the formation center using a consensus algorithm and adjusting the dynamic formation parameters to obtain the optimal topology; and continuously acquiring the number of formation vehicles in real time. If the number of formation vehicles changes, the method iterates; if the number of formation vehicles does not change, the topology is maintained. This invention exhibits strong dynamic adaptability, constrained cooperative optimization, improved safety margin, and enhanced robustness.