425 results about "Routing algorithm" patented technology

The invention relates to the technical field of wireless communication, discloses an air-sea cross-domain network reinforcement learning routing algorithm based on an SDN (Software Defined Network), and mainly aims to solve the problems of poor dynamic environment adaptability, insufficient multi-task QoS (Quality of Service) demand guarantee capability and the like caused by a static rule or local optimization of an existing air-sea cross-domain routing algorithm. Global network state perception and resource centralized scheduling are realized through an SDN controller, and a dynamic routing decision model driven by deep reinforcement learning (DRL) is constructed. A network state is sensed in real time through an SDN controller, a multi-target reward function is designed, and a cross-domain path selection strategy is dynamically optimized. According to the method, the limitation of a traditional routing protocol in a cross-domain heterogeneous network is broken through, the end-to-end transmission efficiency, the resource utilization rate and the multi-task differentiated service quality guarantee capability are remarkably improved, and the method can be widely applied to the scenes of marine environment monitoring, emergency rescue, cross-domain cooperative detection and the like.

The invention provides a wireless communication network method and system of a mobile first-aid station. The method comprises the following steps: monitoring and evaluating a surrounding environment in real time, selecting an optimal working frequency band, and adjusting a frequency band switching strategy to obtain a self-adaptive multi-frequency-band access mechanism; the bandwidth and the connection priority of the wireless communication network are dynamically adjusted, the task priority is evaluated, and a dynamic resource allocation strategy is generated; deploying a distributed cache and synchronization system, realizing balanced distribution and rapid positioning of data, and generating a distributed temporary data cache pool; establishing an intelligent routing algorithm of deep reinforcement learning, calculating an optimal transmission path from a source to a destination, and finally generating an intelligent routing planning scheme; a redundant path is preset on the path, and a redundant path planning scheme is generated according to a dynamic resource allocation strategy and an intelligent routing planning result. According to the technical scheme provided by the invention, the reliability and the response speed of the wireless communication network of the mobile first-aid station are improved.

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 discloses a routing optimization method and system based on an attention mechanism and a time sequence diagram convolutional network, and belongs to the technical field of communication networks, the method classifies traffic in the network, when the network traffic is mouse traffic, a trained A3T-GCN model is adopted to predict the network state of each link, and when the network traffic is mouse traffic, the A3T-GCN model is adopted to predict the network state of each link; optimizing the link by adopting an improved butterfly optimization routing algorithm, calculating the time delay and the fluctuation of the link according to the network state, obtaining the link with the minimum time delay and the minimum time delay fluctuation through iterative optimization, and routing the mouse flow along the link corresponding to the optimal solution; when the network flow is an image flow, the A3T-GCN model is utilized to predict the average residual bandwidth of each link in the shortest hop count link set in the future w periods, and the link object flow with the maximum average residual bandwidth is adopted for routing; according to the method, distribution and utilization of network resources are optimized, so that the overall efficiency and throughput of the network are effectively improved.

An automatic compilation method and framework for generating a layout for an integrated memory-compute circuit design is provided. The automatic compilation method comprises: constructing a design database with at least one basic design library and a collection of referencing architecture templates; receiving a user specification associated with the integrated memory-compute circuit design; selecting a referencing architecture template from the design database and parameterizing the selected architecture template according to the received user specification to generate an architecture for the integrated memory-compute circuit design; generating a physical layout based on the generated architecture according to one or more placement-and-routing algorithms; iterating a design exploration loop on the generated layout with one or more expertise experience-based optimization schemes to obtain one or more explored physical layouts; and evaluating hardware metrics of the one or more explored physical layouts to determine an optimal physical layout.

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, which relates to the technical field of communication, discloses a dual-network-integrated voice scheduling exchange system comprising the following steps: collecting network state information in real time, receiving and analyzing a voice scheduling request, and carrying out division processing on both communication parties; calculating a communication path through an intelligent routing algorithm according to the network state information and the division processing; performing network quality evaluation on the communication path calculated by the intelligent routing algorithm, and selecting an optimal communication path; selecting a voice compression parameter to compress the voice signal, and generating a compressed voice data packet; sending the compressed voice data packet to a receiver through the optimal communication path; and the receiver receives the compressed voice data packet, decompresses the compressed voice data packet to obtain an original voice signal, and outputs clear voice information. According to the invention, through integrating the information collection module, the intelligent routing module, the network evaluation module, the voice compression module, the voice transmission module, the terminal receiving module and the like, the overall safety of the dual-network integrated voice scheduling exchange system and the voice scheduling efficiency and quality are effectively improved.

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 a path determination method and device, a medium and a product, and relates to the technical field of communication. A node hop count strategy is determined by adopting an XOR threshold rule and a direct or indirect connection relation between a source routing node and a target routing node, and then a final routing path is determined according to path marks of the node hop count strategy and a path link rule. Different routing paths are determined through path marks according to specific core schemes (data of actual exclusive or results and preset data contained in binary data) of two cases through two rules under an exclusive or threshold rule. Compared with the unique limitation of the path of the 1-2-4 routing algorithm of the conventional network with the structure, the path diversity and flexibility of the network with the structure are improved.

The invention relates to the technical field of low earth orbit satellite network communication, in particular to a low earth orbit satellite network load balancing intelligent routing algorithm based on a DQN, which adopts a time slicing method to learn node connection relation and load condition in each time slot static topology, according to the method, multiple targets such as the distance between target satellites, the node congestion degree and the link available bandwidth are jointly optimized, an optimized next-hop selection strategy is given for each node, a link connectivity matrix is updated for different time slots, training is continued to update network parameters, and the method has better performance in the aspects of time delay and network throughput, and can be applied to the field of wireless communication. The multiplexing of each satellite node in the network is reduced, the problem of uneven load in the network is relieved, and the network performance is 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 provides a maritime communication optimization method and system based on artificial intelligence. Wherein the maritime communication parameters are comprehensively analyzed and processed to obtain a communication quality report; according to the communication quality report, combining with a ship navigation plan, performing optimization selection processing on available frequency bands by applying an intelligent spectrum allocation algorithm, further improving the scientificity and rationality of frequency band allocation through a spectrum use efficiency analysis technology, and generating an optimized communication resource allocation scheme; based on the optimized communication resource configuration scheme, after a safe and stable bidirectional data channel is established, an efficient and reliable communication path is obtained; and integrating the efficient and reliable communication path with the real-time ship position information and a shore-based support system, planning an optimal communication path by using an intelligent routing algorithm, and generating a comprehensively optimized maritime communication solution. According to the technical scheme provided by the invention, the flexibility, the security and the response speed of the communication system are improved.

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 embodiment of the invention provides a data transmission method and device of a network-on-chip, electronic equipment and a storage medium. The method comprises the following steps: dividing at least two computing nodes with spatial topology into multicast domains; determining a target node for receiving the first message; according to a target multicast domain to which the target node belongs, adding a multicast control field in the first message to obtain a target message; determining a first routing path outside the target multicast domain according to the multicast control field and a routing algorithm; transmitting the target message to the target multicast domain based on the first routing path; determining a second routing path in the target multicast domain according to the intra-domain mask field; and sending the target message to the target node based on the second routing path. In the embodiment of the invention, the routing path of each message can be directly determined according to the multicast control field added in the message, so that the design complexity of the network-on-chip is reduced, and the data payload proportion and the data transmission efficiency of the network-on-chip are improved.

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.

The invention discloses an SDN-fused multilayer QKD constellation model and a key distribution routing algorithm building method, and relates to the technical field of quantum key distribution. According to the method, orbit distribution and dynamic characteristics of a satellite in a free space are deeply analyzed, a trusted relay quantum key distribution constellation model fusing GEO / MEO / LEO three-layer orbits is provided, and a software defined networking (SDN) technology is introduced into the model, so that centralized control and efficient management are realized, and the reliability of the system is improved. A self-adaptive quantum key flow aware routing algorithm (AQKAR) is designed on the basis of a trusted relay quantum key distribution constellation model fusing GEO / MEO / LEO three-layer tracks, so that a key distribution path is dynamically optimized; a simulation result shows that compared with a traditional LEO single-layer network and a GEO / LEO double-layer network, the framework provided by the invention has the advantages that the request success rate is remarkably improved, the end-to-end network delay is lower, and meanwhile, the algorithm provided by the invention can effectively improve the flexibility of the network under the condition that the network is extremely congested.

The invention relates to the field of routing algorithms of a mobile ad hoc network, discloses a multi-path routing optimization method and system for the mobile ad hoc network based on a graph attention network, and mainly solves the problem that in a traditional mobile ad hoc network, due to the fact that link characteristics and a routing scheme can generate nonlinear influence on network performance, the network performance is not influenced. And the problem of network resource waste caused by an improper routing scheme is solved. The content provided by the invention comprises a mobile ad hoc network multi-path network model, a graph attention network prediction model and a routing optimization system. The method comprises the following steps: firstly, generating path information through feature vectors of nodes and links obtained by a software defined network technology; secondly, constructing a multi-path network model of the mobile ad hoc network according to the hidden state relationship between the links and the paths; and finally, constructing a graph attention network prediction model in an application layer, thereby realizing the mobile ad hoc network multipath routing optimization method based on the graph attention network. In addition, a cross-layer routing optimization system is established according to the mobile ad hoc network multipath routing optimization method based on the graph attention network. According to the mobile ad hoc network multipath routing optimization method and system based on the graph attention network provided by the invention, node aggregation is optimized, the requirements of simultaneously learning network features and network complex structures in the mobile ad hoc network are met, the accuracy of predicting the network performance is improved, the routing strategy can be selected in an auxiliary manner, and the routing efficiency is improved. And the utilization rate of network resources is effectively improved.

The invention provides a network layer multi-path forwarding method, and relates to a sending end, a receiving end and a network node. The method for processing the message by the network node comprises the following steps of: after receiving the message, determining whether the message has a multi-path forwarding requirement; obtaining a group of logic network topologies meeting application requirements, and determining a candidate logic topology set by combining the topology condition of the receiving end or the network node connected with the receiving end; determining a multi-path forwarding strategy according to the transmission intention field of the message header; selecting one topology from the candidate logic network topology set or still using the original topology based on a multi-path forwarding strategy; and when the logic network topology is selected, taking the network address of the receiving end as a transmission destination address, calculating through a routing algorithm to obtain a next forwarding node network address of the message, rewriting the destination address of the head of the message as the next forwarding node network address, and forwarding the data message. The method has the advantages that network resources are fully utilized, and diversified transmission requirements of users can be met.

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.