292 results about "Routing algorithm" patented technology

The invention relates to the technical field of computer network communication, and relates to a reconfigurable router architecture based on buffer sharing and a dynamic routing method. The router architecture comprises a demultiplexer used for distributing data packets to centralized buffer areas of other ports according to port load states; the virtual channel distribution module is configured to determine an output port of the data packet according to a routing algorithm and generate a corresponding virtual channel ID; the centralized buffer area supports multi-port sharing and is divided into a plurality of logic sub-channels according to virtual channel IDs, and each sub-channel manages a data packet queue through a head pointer and a tail pointer; the credit management module is used for monitoring the idle capacity of the centralized buffer area and transmitting congestion information through a reserved bit of a data packet; and the congestion register dynamically records the congestion state of the neighbor node through the congestion information table. According to the invention, the problems of unbalanced load, low utilization rate of a buffer area and high congestion control cost of a traditional router are solved.

The invention relates to the technical field of water conservancy system design, in particular to a water conservancy informatization data collection and transmission system and method based on a distributed ad hoc network, and the method comprises the steps: deploying monitoring nodes at each monitoring point of a water conservancy project to collect hydrological data and environmental data; peripheral monitoring nodes are automatically found and connected through a distributed ad hoc network module, a multi-hop wireless network is formed, and communication between the monitoring nodes and gateway nodes is achieved. Specifically, a dynamic routing algorithm is adopted to monitor the delay and signal stability of a link in real time and monitor node residual energy, and an optimal transmission path is calculated; when a node or a link has a fault, a routing path is automatically recalculated according to a fault processing strategy, and disaster recovery transmission is realized; the energy consumption of the monitoring node is reduced through a sleep wake-up mode and an energy-aware routing algorithm; and converging the data of each monitoring node at the gateway node, and uploading the data to a cloud data center. And the flexibility and reliability of data transmission are enhanced.

The invention relates to the technical field of temperature control, in particular to a mass concrete water cooling water temperature control method and system. The method comprises the following steps: collecting concrete key parameters through a multi-source sensor, constructing a microenvironment model based on information geometry, and generating a thermosensitive characteristic spectrum; forming a distributed thermodynamic model by utilizing a mutual information routing algorithm and heat-fluid-solid coupling analysis, and calculating an optimal cooling strategy; water flow path and flow optimization is realized in combination with fractional order particle swarm optimization; a pump set and a valve are adjusted through fuzzy self-adaptive control; and a potential instability region is identified through the spectrum energy gradient, and risk early warning is triggered. The precision and reliability of mass concrete cooling temperature control are remarkably improved, and intelligent, efficient and safe temperature control adjustment in the whole process is achieved.

The invention provides an intelligent computing fusion network routing system and a routing method thereof. The system comprises an entrance gateway, a routing forwarding node, a computing node and a computing network controller, the computing network controller is used for carrying out path selection and computing resource allocation in combination with a real-time network state and load information of the computing node, dynamically generating and updating a computing network routing table through a computing network fusion routing algorithm, and issuing the computing network routing table to the entry gateway and the routing forwarding node; and the entry gateway receives and stores the computing network routing table issued by the computing network controller as a data stream access point, receives a computing power data stream which is input from the outside and carries a computing power service request, executes computing power routing table matching according to the computing power service request, and forwards the computing power data stream to a proper routing forwarding node according to a matching result. According to the invention, by optimizing the joint scheduling of the computing power service paths and the computing nodes, a plurality of paths of the anycast computing power routing and the weights of the paths are generated, the service flow level load balancing is realized, and the end-to-end time delay is reduced.

The invention discloses an automatic financial data collection system based on a web crawler technology. The system comprises an intelligent crawler collection module, a financial data processing module and a data collection module. The intelligent crawler acquisition module comprises a dynamic scheduling crawler cluster unit, a multi-format capture engine and a metadata marking unit; the dynamic scheduling crawler cluster configures a routing algorithm based on reinforcement learning, and dynamically adjusts an IP proxy strategy through an anti-crawling feature matrix; the multi-format capture engine is integrated with a PDF / HTML / JSON heterogeneous data analysis channel; the metadata marking unit generates a data source label by adopting multi-layer coding conversion; and the financial data processing module comprises a cross-format analyzer, a data cleaning pipeline and a structured storage unit. According to the scheme, through innovative designs such as multi-modal data analysis, self-adaptive anti-creeping confrontation, dynamic resource scheduling and intelligent association analysis, the core problems of low heterogeneous data integration efficiency, weak dynamic anti-creeping confrontation capability and the like are solved.

The invention particularly relates to an emergency broadcast intelligent early warning system applied to disaster prevention and reduction, and relates to the technical field of communication. The redundant communication and self-adaptive switching module is configured to establish a multi-mode communication network, monitor link states in real time and realize intelligent switching and load balancing of communication links based on a dynamic algorithm; an intelligent decision-making and precise broadcasting module; and the emergency broadcast terminal is connected with the offline execution module. According to the invention, a multi-mode communication architecture is established, each link monitors parameters such as signal strength, delay, packet loss rate and the like in real time, and intelligent switching and load balancing are carried out through a dynamic routing algorithm; and meanwhile, on the basis of memory thermal characteristic analysis, link faults are pre-judged in advance, switching is triggered, the success rate of early warning information transmission under extreme disasters is ensured, and the problem of transmission interruption of traditional single link communication under the scenes of power failure, base station damage and the like is solved.

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 discloses a dynamic logistics network path optimization method based on a chained state routing algorithm, and belongs to the technical field of logistics network optimization, and the method comprises the steps: firstly, building a node state evaluation model through a distributed state collection mechanism based on a chained state routing protocol, and generating a dynamic elastic network topology structure; secondly, when logistics network nodes change, a logistics path is optimized in combination with a transportation cost prediction model, an emergency response punishment mechanism and a path adjustment weight coefficient; and finally, optimizing an affected path in a node abnormal state by using a local path updating mechanism. Compared with a traditional logistics model, the method has obvious advantages in the aspects of path calculation cost and response time when processing a path problem containing failure nodes, and can effectively optimize logistics path planning, reduce transportation cost and improve system robustness and resource allocation efficiency.

The invention discloses a network architecture based on multi-core transmission, and relates to the field of integrated circuits. The network-on-chip module comprises at least one node ring consisting of M pipeline cascade routing nodes; adjacent routing nodes in adjacent node rings are cascaded according to a longitudinal depth pipeline to form a node matrix; n sending buffers and N receiving buffers are respectively arranged on the node ring on the outermost layer of the node matrix, and each sending buffer and each receiving buffer are respectively connected with the corresponding IP core through directly connected routing nodes; a routing algorithm based on a node matrix is built in the network configuration unit, a target IP core is determined according to data sent into the sending buffer by source IP core data, a node matrix is controlled to plan and generate a data transmission path, and data transmission is executed. The data buffer is added in the network-on-chip architecture, so that the data transmission path is shortened, the feedback is more timely, and the network bandwidth is larger; a routing node adds a data replication realization function to realize multicast and broadcast modes; and the interface complexity of the whole node matrix is reduced.

The invention relates to a satellite network distributed routing method, a satellite network distributed routing system, satellite network distributed routing equipment and a storage medium, belongs to the technical field of wireless communication, and solves the problems of dynamic topological structure change and overlarge load of part of nodes caused by non-uniform service volume distribution in the existing satellite network routing method. The satellite network distributed routing method comprises the following steps: firstly, modeling a routing problem, constructing a problem model, then defining a state space, an observation space, an action space and a reward function of a Markov decision process, constructing a DDQN-based satellite network routing algorithm training framework based on the Markov decision process, and constructing a satellite network routing algorithm training framework based on the DDQN. And then a satellite network routing algorithm training framework based on DDQN is utilized to realize satellite network routing decision, and the network load is reduced with the purpose of minimizing end-to-end delay. The method is not influenced by the dynamic change of the network topology, and can adapt to the frequent network topology change of the low-orbit satellite, thereby ensuring the real-time performance and robustness of data transmission.

The invention discloses a dual-mode communication method and system based on link redundancy check and dynamic hybrid routing, and relates to the technical field of electricity meter reading, and the method comprises the steps: constructing a dual-link parallel channel through HPLC and HRF, and carrying out data synchronization and consistency comparison; when the link is abnormal, dynamically electing an agent coordination node and constructing a cross-protocol mixed link; and optimizing communication path selection and interference suppression by using an intelligent routing algorithm and a noise recognition mechanism. According to the method provided by the invention, the reliability and data transmission efficiency of a communication system are remarkably improved through double-link redundancy check and a hybrid link dynamic reconstruction mechanism. And a parallel acquisition and path optimization method is adopted, so that the meter reading time is shortened, the link switching delay is reduced, and the real-time performance and the resource utilization rate are enhanced. The system has good environment adaptability and can cope with topological changes caused by a complex power grid structure and distributed energy access.

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 discloses a data-driven unmanned aerial vehicle cluster digital twin network binding routing method. According to the method, a tight coupling dependency relationship between data transmission and link control is relieved, and a management plane-control plane-data plane decoupling unmanned aerial vehicle cluster network architecture is constructed. The management plane decides a link weight with the help of a depth deterministic strategy gradient learning method by taking minimization of time delay and packet loss probability as optimization targets. And the control plane formulates a forwarding strategy according to the Floyd shortest path algorithm and the weighted topological graph and issues the forwarding strategy to the data plane. And the unmanned aerial vehicle nodes in the data plane concentrate on data forwarding to realize execution of binding routing. A simulation result shows that the link weight is adaptively adjusted by adopting the method, and compared with a traditional routing algorithm with a fixed link weight, the average end-to-end time delay and the packet loss rate can be effectively reduced, and the network service quality is improved.

An underground space surveying and mapping and environment monitoring system comprises a data acquisition unit, an edge calculation unit, a dynamic scheduling unit and a simulation optimization unit. The data acquisition unit is used for acquiring various parameter data; the edge computing unit receives various parameter data, and predicts future tasks, node energy consumption and network congestion risks based on historical data and real-time states; the dynamic scheduling unit is used for selecting sensor nodes according to future tasks, node energy consumption and network congestion risks, aggregating collected data of the sensor nodes, executing a low-delay routing algorithm, and performing dynamic adjustment to obtain a scheduling strategy; and the simulation optimization unit verifies the performance of the scheduling strategy and feeds back optimization parameters to the dynamic scheduling unit to adjust the scheduling strategy so as to obtain an optimized scheduling strategy. According to the invention, a multi-objective optimization strategy and an energy monitoring and scheduling mechanism are combined, so that the network can realize low-energy-consumption and high-efficiency real-time data transmission and monitoring tasks in a complex underground space environment.

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 discloses a logical reasoning method and device based on knowledge enhancement and capsule network collaboration and a medium. The method comprises the steps that a public knowledge local database is constructed, and a vectorization database and a graph network database are deployed locally; performing preliminary retrieval according to the logical reasoning text, and expanding a retrieval range based on a graph network; inputting the logic text, the problem and the related background knowledge into a large language model to generate a logic reasoning link, and integrating all contents to obtain a logic reasoning text after knowledge enhancement; constructing a semantic graph and a connection graph according to the logical reasoning text after knowledge enhancement; the semantic graph and the connection graph are respectively imported into a capsule network, and a dynamic routing algorithm is applied to promote low-level capsules to be progressive to high-level capsules; respectively executing an average fusion operation on the plurality of high-level capsules in the double images to extract global features of the images; global features of the double graphs are integrated through a fusion strategy, final knowledge text features are formed, and final options are obtained.

The invention discloses a seismic wave acquisition system based on an SDN and a fusion routing algorithm, the seismic wave acquisition system comprises an SDA controller, a fusion routing intelligent closed-loop control framework, a DQL-HRA routing algorithm module and a software architecture, the fusion routing intelligent closed-loop control framework is deployed in the SDA controller, the fusion routing algorithm module is arranged in the fusion routing intelligent closed-loop control framework, and the DQL-HRA routing algorithm module is arranged in the software architecture. The fusion routing intelligent closed-loop control framework comprises a unified state sensing and preprocessing module, a cooperative control intelligent decision module and a control strategy generation and deployment module. The SDN controller and the fusion routing algorithm are combined, the network state change can be dynamically adapted, the purpose of dynamically adjusting and optimizing the routing path is achieved, and through dynamic path optimization, data packet loss and retransmission are reduced, node energy consumption is balanced, local overload is avoided, so that the data transmission efficiency is improved, and the use requirement is met.

The invention relates to a dynamic layer cutting system and method for a large-scale language model, and the method comprises the steps: converting an input audio signal into embedded representation of a plurality of segments of input marks with equal coding lengths through a conversion module, and replacing a converter model architecture of a conventional large-scale language model through a route adjustment device. The global mark perception routing algorithm is adopted to dynamically adjust and calculate resource distribution, so that the problem of low efficiency caused by fixed resource distribution is avoided, the reasoning efficiency is improved, and the unnecessary calculation amount is reduced. Moreover, the route adjusting device performs multiple perceptual estimation mapping and self-attention estimation mapping on the embedded representation of each section of input mark to obtain a corresponding output mark, so that a cutting strategy for decoupling a multi-layer perceptron and a self-attention layer in a converter model architecture is realized, calculation resource allocation is more reasonable, and the calculation efficiency is improved. Resource waste caused by unified cutting is effectively avoided, and meanwhile the model performance is kept.

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 a segmented routing method and system for a low-orbit giant satellite base. The method comprises the following steps: S1, setting part of satellite nodes as preset satellite segment nodes; s2, enabling each satellite node in the satellite network to collect network parameters between adjacent satellite segment nodes; s3, enabling any satellite node to request spatial network data transmission from the routing calculation module through the application sensing module; s4, taking the routing calculation module as a head node of spatial network data transmission, and determining a data transmission path through a quadrant method; and S5, generating a path label stack, pressing the path label stack into a to-be-transmitted data packet header, and sending data to a next-hop satellite segment node. According to the segmented routing algorithm for the low-orbit giant satellite base, the satellite segment nodes are screened and calculated through a quadrant method, a basis is provided for selection of the satellite segment nodes, the data packets are forwarded by the appropriate satellite segment nodes, transmission delay and network congestion are reduced, and QoS guarantee of the data is ensured.

The present invention belongs to the technical field of vehicle networking, and specifically relates to a V2V communication broadcast routing algorithm based on combined weights. The steps include constructing a two-way lane vehicle networking system model based on vehicle ad hoc networks; determining the communication metrics of vehicle networking communication scenarios; constructing a routing algorithm: randomly determining a vehicle source node and a destination node. For the information to be transmitted, according to the methods of broadcasting and constructing a neighbor table, find the vehicles within the communication range, start broadcasting from the source node to find relay nodes outward. Each node existing within the communication range is a relay node, and keep searching from the source node until the destination node is found and the search stops; determine the weights and weight coefficients involved in the routing algorithm, and then establish the weight coefficients according to the analytic hierarchy process, select the most suitable relay node for transmitting information as the optimal path, and transmit the information to the destination node. The present invention can improve the routing selection efficiency and ensure the stability of the link on the premise of ensuring the information transmission speed record.

The invention discloses a software-defined satellite network load balancing routing algorithm, belongs to the technical field of software-defined satellite network load balancing routing algorithms, and constructs a satellite network architecture based on an SDN, applies a software-defined network technology to a satellite network, and sets SDN controllers at a ground station or a plurality of different geographic positions. The controller is used for managing control functions of a satellite network, including regional division of the network according to satellite orbit position, coverage range and service requirements, unified or collaborative management of resource allocation and routing strategies of each region, stage division of services in the satellite network, and management of the services in the satellite network. According to different requirements of the services for time delay, bandwidth and time delay jitter QoS indexes, the services are divided into different levels which at least comprise high-level services and common-level services, and higher priority guarantee is set for the high-level services.

The present invention discloses a dual-mode communication method and system based on link redundancy check and dynamic hybrid routing, which relates to the technical field of electricity metering, including building a dual-link parallel channel through HPLC and HRF to perform data synchronization and consistency comparison; when the link is abnormal, dynamically electing an agent coordination node and building a cross-protocol hybrid link; and optimizing communication path selection and interference suppression using an intelligent routing algorithm and a noise identification mechanism. The method of the present invention significantly improves the reliability and data transmission efficiency of the communication system through a dual-link redundancy check and a hybrid link dynamic reconstruction mechanism. The parallel collection and path optimization method is adopted to shorten the meter reading time, reduce the link switching delay, and enhance the real-time performance and resource utilization. The system has good environmental adaptability and can cope with the topology changes brought about by complex power grid structures and distributed energy access.

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 discloses an energy-saving QoS (Quality of Service) routing protocol implementation method based on ant colony optimization, which aims at solving the problems of low routing efficiency and high path energy consumption in a UANET (User Ad Hoc Network) based on RF / FSO (Radio Frequency / Free Space Optimization) communication, and realizes an energy-saving QoS routing protocol based on ant colony optimization. An energy-saving QoS routing algorithm based on ant colony optimization is provided, and node neighborhood energy density is considered in a path transition probability model, so that the search efficiency of the ant colony algorithm is improved, and energy balance in the network is ensured; energy and distance factors are added into a pheromone updating rule, and the difference between the optimal path and other paths is increased; a self-adaptive pheromone volatilization mechanism is added, and the volatilization rate of pheromones is dynamically adjusted according to the real-time state of the network; and a cross-layer data exchange interface is added, so that real-time updating of link interaction data is ensured, and stable communication in a dynamic network environment is supported.

The invention provides a blind identification and intelligent classification prediction method and system for a signal modulation mode, and relates to the technical field of signal processing, and the method comprises the steps: obtaining a multi-scale time domain feature through wavelet packet decomposition, obtaining an instantaneous frequency feature through Hilbert transform, and constructing a feature correlation matrix; blind identification of a signal modulation mode is realized by using a dynamic routing algorithm and a self-correction mechanism; distinguishing discrete and continuous modulation based on the feature matrix and the signal-to-noise ratio; and signal modulation mode prediction is realized by adopting hybrid filtering and layered Markov decision. According to the invention, the recognition accuracy and prediction stability of the signal modulation mode are improved.

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.