194 results about "Routing algorithm" patented technology

The invention provides a power grid resource operation management method, device and equipment based on a service platform, and relates to the technical field of power grid management. The method comprises the following steps: when a flow exception occurs, determining an exception type, determining a self-healing strategy according to the exception type, and reconstructing a flow path according to an intelligent routing algorithm; obtaining resource data of each professional system of the power grid, and generating a resource scheduling scheme according to the resource data, the reconstructed flow path and the dynamic scheduling strategy; and performing resource scheduling according to the resource scheduling scheme, and obtaining resource scheduling real-time data to generate resource situation display information and / or resource early warning information. The stability and response efficiency of power grid resource operation can be improved.

The invention discloses an unmanned aerial vehicle cluster cross-layer cooperative routing method based on TDMA, is applied to the field of wireless communication network resource scheduling and unmanned aerial vehicle autonomous networking cooperative control, and aims to solve the problem that the overall resource utilization rate of a system is low due to hierarchical design of a routing strategy and an MAC layer channel access control strategy in an existing TDMA network. The method comprises a dynamic collaborative framework based on routing and time slot allocation and a time slot state sensing routing algorithm based on deep reinforcement learning, the framework provides real-time time slot resource allocation state input for the algorithm, the algorithm outputs an optimal path meeting the bandwidth requirement for the framework, the problem of resource mismatching of a traditional layered framework is effectively avoided, and the routing efficiency is improved. And finally, collaborative optimization of the service bandwidth achievement rate and the network resource utilization efficiency in a high-load scene is achieved.

The invention discloses an intelligent medical image diagnosis system and method based on hierarchical cross-modal conversion and dynamic feature tracking. The system adopts three-step cross-modal conversion: a first-layer small model for converting user questions to realize medical ontology matching; the second-layer multi-modal model extracts image features, and outputs text states such as JSON data with focus coordinates, density and other features; and the third-layer large model fuses the medical history and the image features to generate diagnosis suggestions, and credibility verification is carried out. A dynamic focus tracking engine is introduced, a focus evolution rule of multiple scanning is analyzed through a convolutional network, and an optical flow field is adopted to compensate artifacts. The system also integrates a multi-expert voting mechanism to simulate a clinical consultation process, and outputs consensus diagnosis and objection viewpoints. A hierarchical routing algorithm is designed for emergency treatment scenes, so that the recognition response time of emergencies such as pneumothorax is shortened. Further, the system automatically generates a full chain of evidence report that conforms to medical regulations, including a model version, a guide reference, and a data hash value.

The invention provides an artificial intelligence semantic processing system and method oriented to digital media creation, and relates to the technical field of artificial intelligence semantic process.The artificial intelligence semantic processing method comprises the steps that predicate argument relation pairs of language texts are extracted, object space relation pairs of sketch images are extracted at the same time, and a basic semantic unit set is constructed; the integrity and accuracy of cross-modal semantic understanding are ensured, further, semantic units are clustered by using a dynamic routing algorithm, a semantic concept cluster with a clear importance weight is generated, deep mining and structured representation of creation intentions are realized, and the creation intentions are quickly and accurately understood. An initial semantic relation graph is constructed, a graph attention network is used for dynamic reweighting, finally, an enhanced dynamic semantic graph is generated, complex association and a hierarchical structure between semantic concepts are effectively captured, finally, hierarchical analysis is carried out on the semantic graph, and a structured semantic blueprint is output, so that the dynamic semantic graph is obtained. And a reliable semantic processing technology is provided for creation of high-quality digital media contents.

The invention discloses a liquid drop routing method under fluid constraint in a digital micro-fluidic biochip based on reinforcement learning and imitation learning, and aims to solve the technical problems of low planning efficiency, low success rate and weak generalization ability of a traditional liquid drop routing algorithm under fluid constraint. The method adopts a strategy combining imitation learning and reinforcement learning and comprises the following steps: firstly, generating expert data by utilizing an expert algorithm meeting fluid constraint after transformation, and pre-training a network model through imitation learning to enable the network model to quickly grasp a basic routing strategy; the model and environment interaction are autonomously optimized through reinforcement learning, and the adaptability to the dynamic environment is improved. And finally fusing the weights to form a final model. Through the hybrid training framework, the success rate and planning efficiency of droplet routing are remarkably improved, and the generalization ability of the model to chip environments with different sizes is enhanced.

The invention provides a multi-source data fusion analysis system for electronic commerce digitization insight, and relates to the technical field of data processing, and the system comprises a reference analysis unit used for selecting a reference analysis unit in a spatial relation structure, calculating fractal dimension features of feature vectors, carrying out multi-level recursive division on the analysis unit based on fractal dimension values, and carrying out multi-level data fusion analysis on the fractal dimension values; each level of division keeps a self-similarity characteristic, and feature partitions are obtained; the partition space distribution module is used for mapping the feature vector distribution to corresponding feature partitions and calculating partition space distribution weights based on vector density distribution and space position relations of the feature partitions; the value evaluation module is used for performing parameter adjustment on the deep learning network by using the partition space distribution weight to obtain a value evaluation result; and the value evaluation module is used for processing a value evaluation result through a multi-modal fusion algorithm, generating a personalized recommendation strategy based on a reinforcement learning framework, and calculating resources and an intelligent routing algorithm so as to complete a digital insight analysis process. The e-commerce data utilization efficiency and the decision-making effect can be improved.

The invention relates to a retrieval routing optimization method and device based on a distributed retrieval system, and relates to the field of computer technology distributed retrieval, the method comprises the following steps: obtaining inverted metadata of a document, including routing information, fragmentation information and a document storage identifier, judging whether the document is a new document, and combining the resource state and availability of each node to optimize the retrieval routing optimization of the document. And determining an optimal routing path by adopting an optimal execution fragmentation formula. A retrieval request is split into a plurality of sub-requests and is directionally issued to a target fragment, and the coordination node integrates return results of the fragments and then returns the return results to the client. The device comprises an information integration module, an inverted metadata recorder and a retrieval routing control module, and supports a dynamic configuration routing strategy, a document state refreshing mechanism and performance monitoring parameters. By introducing the document state identifier, the dynamic routing algorithm and the node resource monitoring mechanism, accurate routing and efficient processing of the retrieval request are realized, so that the retrieval performance and the resource utilization rate of the system are improved.

The invention provides an NoC low-delay data transmission method based on a dynamic routing algorithm, relates to the technical field of data transmission, and aims to solve the technical problems that an existing NoC routing algorithm cannot adapt to a link dynamic load, is lack of congestion trend prejudgment, is slow in path search convergence and is insufficient in QoS differential scheduling. The method comprises the following steps: constructing a dynamic sensing module containing a double-branch LSTM time sequence prediction model, collecting states such as link bandwidth and queue length in real time, and predicting a congestion trend in 50-100ms in the future; constructing a multi-objective evaluation function taking delay as a core, and dynamically adjusting the weight according to the QoS level; solving an optimal path by adopting an improved ant colony algorithm which introduces a congestion penalty and pruning strategy; during transmission, dynamic reselection is triggered through a pre-calculation + fast matching mechanism; and iteratively optimizing the prediction model based on incremental learning. According to the method, congestion is avoided in advance, the path search efficiency and the transmission reliability are improved, the delay is remarkably reduced compared with a traditional algorithm, and the method is adaptive to delay sensitive scenes such as a high-performance processor and an AI chip.

The invention relates to the field of network communication, and discloses a fast message pushing method and device based on converged communication and a medium, and the method comprises the steps: collecting message content data through a multi-source heterogeneous interface, carrying out the normalization processing of the data, and generating standard message metadata; key feature vectors are extracted from the standard message metadata by adopting a deep semantic analysis model, and a message priority evaluation matrix is generated in combination with a user portrait database; based on a multi-channel intelligent routing algorithm, generating an optimal transmission path decision tree according to the priority evaluation matrix and the real-time network state data; and distributing the message to the target communication channel according to the decision tree path through a dynamic load balancing engine, and executing multi-protocol adaptive transmission. According to the method, a whole-process message pushing method from matrix evaluation to intelligent routing and then to multi-protocol adaptive transmission is constructed, a high-reliability and low-delay communication solution is provided for a scene needing rapid message pushing, and the method has remarkable technical breakthrough and commercial application value.

Embodiments of this application disclose an in-network computing packet forwarding method, a forwarding node, and a computer storage medium, and belong to the field of communication technologies. In the method, a forwarding node receives a plurality of in-network computing packets; determines an in-network computing identifier of each in-network computing packet; performs, based on the in-network computing identifier of each in-network computing packet, aggregation computing on in-network computing packets that belong to a same in-network computing message in the plurality of in-network computing packets, to obtain at least one aggregated packet; and forwards each aggregated packet by using a hash routing algorithm based on an in-network computing identifier corresponding to each aggregated packet.

The application discloses a chip based on a reconfigurable neuromorphic interconnection architecture, comprising a layered dynamic reconfigurable interconnection network layer and a memristor-CMOS reconfigurable interconnection unit, and the layered dynamic reconfigurable interconnection network layer and the memristor-CMOS reconfigurable interconnection unit are dynamically adjusted in a routing path through a dynamic routing algorithm. The application has the beneficial effects that: the dynamic routing algorithm is combined with the layered dynamic reconfigurable interconnection network layer and the memristor-CMOS reconfigurable interconnection unit, thereby performing dynamic prediction of network congestion and dynamic adjustment of a routing path, and the CMOS switch and the memristor switch are connected in parallel, avoiding the limitation of traditional single devices or static interconnections, so that the network performance and reliability are improved, and the delay and power consumption of data transmission are reduced.

The invention provides a file co-processing method and system based on distributed multithreading and dynamic sub-libraries, and relates to the technical field of file data processing, and the method comprises the steps: obtaining a to-be-processed file, and generating a file list according to batch information; a production-consumer model is adopted, a producer main thread scans a file list, a task queue is generated, a consumer thread pool concurrently executes downloading tasks, and the maximum concurrency number is controlled through semaphore; file data are uniformly distributed to a plurality of physical storage nodes on the basis of a fragment routing algorithm, real-time updating of a mapping relation between fragments and instances is managed by utilizing a dynamic routing table, resources are preferentially allocated to high-priority file tasks on the basis of a service routing strategy, and the tasks are dynamically allocated to specified database fragments; multi-file parallel processing on a processing node is realized through a three-stage parallel model, dynamic Feign calling is carried out on a service instance dynamic route and a weight load, multi-state table state synchronous updating is carried out based on a two-stage state machine, and a processing log is saved.

The invention discloses a method for deploying a spiking neural network on neuromorphic hardware, and belongs to the technical field of collaborative design of neural network software and hardware. In order to solve the problem of high delay of spiking neural network deployment under different hardware topological structures and routing algorithms, modeling is mainly carried out on a mapping scheme of a neural network between hardware cores under the constraint of preset hardware parameters; and performing iterative optimization on the initial deployment scheme through the deployment scheme selection strategy to meet the response time constraint. The method can be suitable for various hardware architecture and route combinations, response time after deployment is effectively shortened, and system operation efficiency is improved.

The invention discloses a multicast routing and load balancing method applied to a low earth orbit satellite network, which belongs to the field of low earth orbit satellite network communication, and comprises the following steps: acquiring topology and link state information of the low earth orbit satellite network, modeling a multicast tree construction problem into a joint path optimization game, and solving through a cooperative game routing algorithm; by introducing an incentive link cost allocation mechanism and combining with a dynamically adjusted cost weight, multicast path selection is optimized, link cost is effectively allocated, and load balancing is realized; and designing a composite cost function fusing link load and delay to calculate the total cost of the path. According to the method provided by the invention, an innovative and efficient solution is provided for the multicast routing and load balancing problems in the low earth orbit satellite network, and the transmission efficiency, the service quality, the network stability and the overall throughput of the multicast service in the low earth orbit satellite network can be enhanced. And obvious advantages are shown in the aspects of improving the network performance, guaranteeing the service quality and enhancing the network robustness.

The invention relates to the field of data retrieval, in particular to an efficient data retrieval method based on a neural network, which comprises the following steps: obtaining a lightweight biomedical language model through a knowledge distillation method, and generating previous health record feature vectors; analyzing through a dynamic routing algorithm to obtain a query semantic complexity score value, and dynamically selecting a retrieval path for retrieval to obtain a preliminary retrieval result; when it is monitored that the accumulated number of newly-added rare disease cases exceeds a preset threshold value, the lightweight biomedical language model is updated, and feature vectors of the newly-added rare disease cases are seamlessly inserted into a second-level approximate nearest neighbor index; adjusting similarity scores according to a symptom time sequence attention mechanism, and reordering by combining treatment effectiveness feedback to obtain a final retrieval result. The challenges faced by previous health record data retrieval can be solved, the retrieval efficiency and accuracy are improved, and the method adapts to data dynamic changes.

The invention discloses a false information detection model and method based on multi-modal semantic difference and bidirectional prompt, and belongs to the technical field of information processing and artificial intelligence. A model including prompt learning, single-mode feature extraction, semantic difference deepening, multi-mode fusion and a prediction module is constructed, a mixed template of background prompt and virtual prompt is utilized to strengthen semantic understanding, and a clustering-guided triple loss function is combined to enlarge semantic difference. And realizing cross-modal'partial-overall 'relation modeling by means of a two-way attention mechanism and a dynamic routing algorithm of a capsule network, and finally outputting authenticity prediction. According to the method, the task understanding capability and cross-scene adaptability of the model are effectively improved, the feature discrimination capability is enhanced, multi-modal deep fusion is realized, the accuracy and stability of false information detection are improved, and F1 scores of experiments on microblog and Tutt data sets respectively reach 88.6% and 83.9%, which shows that the detection performance of the method is superior to that of a mainstream baseline model.

The invention relates to the technical field of computer graphic processing, and discloses a method for automatically drawing a DCS (Distributed Control System) picture into a real-time database picture, which comprises the following steps of: firstly, identifying a DCS source file format, directly analyzing a public text format or intercepting a bottom layer rendering instruction for a private binary format, and extracting standardized discrete data; constructing an intermediate vector model, and performing coordinate normalization and curve smoothing processing on the static primitives by using an affine transformation matrix; meanwhile, syntactic analysis is conducted on the control script to construct an abstract syntax tree, and dynamic logic is converted; then recombining a composite object based on spatial semantics, and repairing pipeline topology connection by utilizing automatic adsorption and an orthogonal routing algorithm; and finally, calling a target system interface to complete object instantiation and persistent storage. According to the invention, the automatic high-fidelity migration of the DCS picture to the real-time database is realized, the labor cost is reduced, and the consistency and accuracy of the monitoring picture are ensured.

The invention discloses a link congestion control load balancing routing method based on routing domain division. The method belongs to the technical field of low-orbit satellite routing switching application. The problem that a traditional routing algorithm is high in complexity and slow in response time under the condition of a large network scale is solved. A giant constellation is divided into non-overlapping routing domains, global routing is divided into intra-domain local routing calculation and cross-domain routing interaction, on-satellite computing power consumption is reduced, and the method is adaptive to a large-scale satellite network. Meanwhile, a traditional distributed routing algorithm relates to signaling flooding when the state of a satellite link is changed, the signaling overhead is huge in a large-scale satellite network, local response is carried out in the congestion process by means of a sub-domain architecture and inter-satellite link availability prediction, and the signaling overhead of the whole network is reduced, so that the availability of the routing algorithm is improved.

The present application generally relates to electronic trading systems, and more specifically to systems and methods for electronic trade order routing. A routing algorithm may generate an execution style recommendation for incoming IG corporate orders. For example, the style recommendation may be shown as a new column in the trading application dashboard that suggests a course of action to traders for each order. In one implementation, automatic decision making may occur based on the style recommendation.

The embodiment of the invention provides a system-on-chip design method and device, a deadlock detection method and device, electronic equipment and a storage medium. The system-on-chip design method comprises the steps that a network-on-chip included in a system-on-chip in design is mapped into a first directed connected graph; determining a first directed connectivity dependency graph according to the first directed connectivity graph and a routing algorithm of the network-on-chip; mapping subsystems included in the system-on-chip in the design into a second directed connected graph; determining a second directed connectivity dependency graph according to the second directed connectivity graph and a logic routing algorithm of the subsystem; determining a third directed connected graph according to the first directed connected graph and the second directed connected graph; determining a third directed connectivity dependency graph according to the first directed connectivity dependency graph and the second directed connectivity dependency graph; and performing deadlock detection on the system-on-chip in design according to the third directed connectivity graph and the third directed connectivity dependency graph, and optimizing the system-on-chip in design according to a deadlock detection result. According to the scheme, the design cost of the system-on-chip can be reduced.

The invention relates to the technical field of network configuration for interconnection and intercommunication, in particular to a network configuration method, system and device for interconnection and intercommunication and a medium. Determining a network topology structure and dividing a logic area; distributing a unique multicast address field for each area; deploying a self-adaptive routing protocol; distributing preset channels in the core exchange layer through quantum communication; creating an intelligent traffic sculpture engine, predicting burst traffic by using a neural network and presetting a buffer space; implementing a heterogeneous equipment compatibility strategy; constructing an annular redundant architecture; starting a block chain verification mechanism; and deploying a holographic topology monitoring system. Through intelligent linkage of a dynamic routing algorithm and an optical layer self-healing loop, business migration of regional faults can be completed within a human perception threshold, and finance transaction sensitive operation can achieve zero-interruption extreme availability.

This invention discloses a routing method and system for a multi-layered, multi-path switching network. The method includes the following steps: constructing a directed graph based on the multi-layered network, wherein nodes in the directed graph represent switches, edges represent communication links, each node has the ability to switch between different switching technologies, and the communication link has the ability to transmit data according to the switching technologies of its two endpoints; for each node in the directed graph, initializing the routing table of that node and iteratively calculating the optimal routing table; given a starting node and a target node, obtaining the next hop of the minimum-cost continuous path from the starting node to the target node according to the optimal routing table of the current node, and sending data packets hop-by-hop to the next node. The routing algorithm proposed in this invention can solve the minimum-cost path problem between all node pairs.

Systems and methods of configuring and using a machine-learned safety risk model to predict a corresponding risk of vehicular collision for different candidate routes are disclosed herein. In some example embodiments, a computer system obtains accident data and feature data for historical routes that have been communicated electronically as navigation guidance, trains a safety risk model using the accident data and the feature data of the historical routes as training data in a machine learning process, and then evaluates one or more routing algorithms by generating a corresponding set of routes for each routing algorithm and generating a corresponding performance measurement for each set of routes using the trained safety risk model.

This invention discloses an efficient routing method for ultra-high bandwidth (UBF) service flows in Time-Sensitive Networks (TSNs), aiming to solve problems such as load balancing of UBF and improve network performance. The main steps include distinguishing UBF from other data flows to meet their respective needs; then, employing a multi-objective optimization efficient routing algorithm to select the optimal path for transmission for each service flow. This invention can improve the operational efficiency and performance of TSNs, especially in scenarios involving mixed transmission of ultra-high bandwidth and regular service flows, providing more reliable services for real-time applications.

The application discloses a kind of multi-modal offshore target detection methods based on multi-scale capsule and Bi-FPN, comprising: S1, the RGB-D multi-modal image data of offshore scene is carried out multi-scale feature fusion by bidirectional feature pyramid;S2, the fusion effect of shallow feature is optimized by iterative fusion method;S3, the multi-scale feature obtained after feature fusion is input into classification network and regression network based on multi-scale capsule network respectively by hierarchical level;S4, the anchor frame class prediction matrix and the four-tuple vector of target object prediction frame coordinates required finally are calculated respectively by depth separable convolution and dynamic routing algorithm technology.According to the application, a variety of deep neural network technologies are fused, the accuracy of offshore scene target detection is improved, objects of different sizes and different degrees of shielding can also be identified, and the method has wide applicability and strong robustness.

The embodiment of the invention relates to the technical field of data processing, in particular to a data caching method, a plug-in caching system, computer equipment and a storage medium. The method is applied to a proxy layer of the plug-in cache system, the proxy layer comprises a serialization layer and a routing layer, the serialization layer comprises a plurality of preset serialization protocol plug-ins, and the routing layer comprises a plurality of preset routing algorithm plug-ins. The data caching method comprises the following steps: receiving a caching operation request from a client; determining a target serialization plug-in from the plurality of serialization protocol plug-ins, and determining a target routing algorithm plug-in from the plurality of routing algorithm plug-ins; standardizing the cache operation request according to the target serialization protocol plug-in to obtain a standardized request; determining a target cache instance corresponding to the standardized request according to the target routing algorithm plug-in; and sending the standardized request to the target cache instance. By adopting the method, the development cost can be reduced, and the development period can be shortened.

The application discloses a satellite routing method and device based on multi-objective optimization, equipment and storage medium, relates to the technical field of satellite communication. The satellite routing method based on multi-objective optimization comprises the following steps: obtaining the running state information of a satellite communication network; according to the running state information, the satellites in the satellite communication network are divided into at least two stable satellite clusters; topology abstraction is performed on each stable satellite cluster to obtain a cluster time-varying graph corresponding to the satellite communication network; a target transmission path is generated according to the cluster time-varying graph, and satellite routing is performed based on the target transmission path. The application solves the technical problem of excessive operation resource consumption of the dynamic routing algorithm of the satellite communication network in the prior art.

The invention discloses a data transmission method, system and device and a computer readable storage medium, relates to the technical field of network-on-chip, and is applied to a routing node of the network-on-chip to determine a source node for transmitting target data and a destination node for receiving the target data. Determining a node routing direction according to the position relationship between the source node and the destination node; according to the position relation between the routing node and the destination node, screening a next node according to the node routing direction; transmitting target data to the next node through a conventional channel of the routing node in response to the fact that the coordinate of the next node and the coordinate of the routing node have the same value; and in response to the fact that the coordinate of the next node and the coordinate of the routing node do not have the same value, transmitting the target data to the next node through the virtual channel of the routing node. On the premise of not changing a network-on-chip architecture system, transmission congestion is reduced by modifying a routing algorithm on a software level, and the data transmission efficiency of the network-on-chip is improved.

A tunnel dual-energy clustering routing method based on multi-objective optimization comprises the steps that a three-dimensional space model of a single-tube tunnel is constructed and used for representing the geometric structure of the tunnel; the method comprises the following steps of: providing a multi-target clustering routing (TCR) algorithm and a dual energy dynamic supply (DETCR) algorithm of the multi-target clustering routing (TCR) algorithm, and providing a multi-target clustering routing (DETCR) algorithm of the multi-target clustering routing (TCR) algorithm and a dual energy dynamic supply (DETCR) algorithm of the multi-target clustering routing (DETCR) algorithm of the multi-target clustering routing (DETCR) algorithm of the multi-target clustering routing (TCR) algorithm of the multi-target clustering routing (TCR) algorithm; on the basis of a tribe competition and member cooperation algorithm (CTCM), a multi-target tribe competition and member cooperation algorithm (MOCTCM) is provided, the residual energy, the communication distance and the energy consumption of nodes, the election frequency of relay nodes (RN) and other factors are comprehensively considered, the optimal cluster head (Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, Optimal Cluster Head, Optimal Relay Node, optima-RN is selected, so that a decision basis with higher adaptability and global optimization capability is provided. According to the method, the problems of non-uniform node energy consumption and limited energy supply in a dynamic and energy-limited tunnel environment are effectively solved, the life cycle of the network is remarkably prolonged, and the energy efficiency level of the network is improved.

A logistics system uses an application to push notifications as a function of proximity for an appliance that needs a part for replacement. The logistics system consists of a sensor, a parts algorithm, an inventory database, a trilateration sensor, a routing algorithm, and an alerting module. The sensor at a first location detects usage of the appliance. The parts algorithm determines the part which is needed for the appliance. The inventory database at a second location stores inventory information for multiple parts of the appliance. The communication interface transmits data between two locations and the trilateration sensor tracks a location of the user device. The routing algorithm determines distance between the location of the user device and different locations having the part. Finally, the alerting module of the user device triggers when location of the user device is within a determined distance from different locations having the part in stock.