131 results about "Topology mapping" patented technology

A method is provided for enhanced data routing in neural networks using Self-Organizing Maps (SOM) integrated with Autoencoder-GAN. The method comprises training an autoencoder to encode input data into a latent space representation; applying a Self-Organizing Map (SOM) to organize the latent space representation into a topological map; refining the latent space representation using a Generative Adversarial Network (GAN), wherein the generator generates enhanced latent space representations and the discriminator evaluates their quality; using the refined latent space representations to update the SOM topology dynamically; generating routing coefficients based on the updated SOM topology to guide data routing in a capsule network; and dynamically adjusting routing within the capsule network using the generated routing coefficients to enhance performance based on the refined latent representations.

The invention relates to the technical field of electrical digital data processing, and discloses a statistical entropy and multi-factor fused text similarity data processing method, which comprises the following steps that: a processor extracts substring sets which do not contain maximum common values of a first data sequence and a second data sequence, and calculates the quadratic sum of the lengths of substrings to generate local statistical entropy; traversing the maximum common substring set to obtain storage address indexes of the maximum common substring set in the first data sequence memory space and the second data sequence memory space, and constructing a topological mapping vector of a mapping structure displacement relationship; calculating the total number of inverted pairs of the topology mapping vector by using a merge sorting algorithm, and generating a normalized topology dissipation index; and by taking the local statistical entropy as an information carrier and taking the topological dissipation index as a structural damping factor, executing nonlinear damping modulation operation to obtain a final similarity score, and solving the technical problem that the block-level displacement cannot be identified by linear scanning logic by quantizing topological entropy increase of data distributed in a storage space.

The invention relates to the technical field of electric digital data processing, and discloses a multi-dimensional data logic processing method based on an artificial intelligence algorithm, which comprises the following steps: receiving a target discrete data packet, extracting metadata, and calculating to generate a dimension entropy feature vector representing data logic complexity; inputting the vector into a preset topological mapping model, and outputting an initial adjacent matrix; calling a feedback suppression mask matrix generated based on a historical operator utility state, and executing bitwise logic AND operation with the initial adjacent matrix to generate a corrected effective topological matrix; the matrix is analyzed, a logic operator function pointer is dynamically indexed in an instruction cache, and a directed acyclic execution linked list is constructed; according to the method, redundant logic nodes in AI prediction are definitely eliminated through a bit operation mask mechanism based on historical feedback, and deterministic convergence of processing delay and optimal matching of computing power resources are achieved.

The invention discloses a dynamic topology mapping and GPU heterogeneous flood coupling model real-time early warning method, and solves the problems of inflexible coupling of a one-dimensional model and a two-dimensional model, low calculation efficiency, poor dynamic response capability and the like in traditional flood simulation. A dynamic topology mapping mechanism is introduced to respond to emergencies such as dike burst and overflow in real time, the calculation efficiency is remarkably improved by utilizing a GPU heterogeneous parallel architecture, rapid and accurate simulation of the whole process of flood formation, evolution and submerging is achieved, reliable technical support is provided for flood control dispatching and emergency decision making, and the method is suitable for large-scale popularization and application. The method comprises the following steps: constructing a two-dimensional hydrodynamic model based on an unstructured grid, establishing a dynamic topology mapping mechanism and realizing GPU parallel numerical calculation; a two-dimensional model lateral connection coupling mechanism is constructed, dam overtopping flow is calculated in real time, and breach flow dynamic calculation of an improved DAMBRK method is carried out; multi-target parameter calibration, multi-dimensional model verification and one-two-dimensional model GPU collaborative parallel computing are realized.

The invention relates to the technical field of power distribution network fault positioning, in particular to a power distribution network fault traveling wave positioning method and system, and the method comprises the steps: synchronously collecting a transient signal through a distributed traveling wave sensing unit, and extracting an initial traveling wave arrival time; constructing an adaptive wave velocity model based on line physical parameters to calculate an equivalent propagation velocity; dynamically generating a traveling wave propagation tree according to the real-time switch state to determine an effective monitoring path; based on the propagation path and the actual arrival time, an optimization algorithm is adopted to determine a preliminary fault point; and calculating a consistency index of the polarity of the traveling waves of the adjacent nodes, starting a multi-hypothesis tracking mechanism in a preliminary point neighborhood when the consistency index is lower than a threshold value, performing confidence coefficient weighted evaluation by combining a traveling wave attenuation model, and outputting an accurate positioning result. According to the method, through cooperation of dynamic topology mapping, adaptive wave velocity correction and multi-source closed-loop verification, the precision, reliability and adaptive capability of fault positioning in a complex power distribution network environment are remarkably improved, and the operation and maintenance requirements of rapid self-healing are met.

The invention relates to the technical field of display, in particular to a Mini LED backlight module intelligent control system and method of a distributed driving architecture, and the system comprises a processor unit, an LED driving chip, a Mini LED module and a sensor. The processor unit converts an RGB color space into a backlight brightness signal in an XYZ tristimulus value form based on a topological mapping theory; the LED driving chip receives the signal, controls the light intensity of the Mini LED module, and executes verification and compensation based on a Bayesian inference framework; the Mini LED modules are arranged in a distributed architecture, receive the brightness signal and output backlight brightness; a sensor collects backlight brightness signals of an RGB color space to form closed-loop feedback, a calibration coefficient matrix is generated through a polynomial fitting calibration algorithm optimized through matrix decomposition, and high-precision and high-reliability backlight control is achieved in combination with adaptive parameter adjustment and a dynamic compensation mechanism.

The invention relates to the technical field of fault positioning, in particular to a power distribution network line fault positioning method and system based on a fault indicator, and the method comprises the following steps: obtaining node current data, calculating a jump rate, screening an early warning node, recognizing an intersection section, determining a fault position, and generating a recognition result. According to the invention, through collecting periodic current data of each node fault indicator, combining node numbers and topological structure mapping, systematically establishing a current sequence table and calculating a current increment difference value in unit time, and through grade division and periodic stability identification of a jump rate, key nodes with early warning characteristics can be accurately screened. The method comprises the following steps of: acquiring a path intersection area, positioning a fault centralized distribution section by virtue of jump intensity trend change analysis of the path intersection area, and determining a fault initial position and a grade identifier in combination with a comparison relationship between a sampling time point and trigger delay between nodes, so that accurate identification and quick response of a multi-path fault are realized under a complex topological structure of a power distribution network.

The invention relates to the technical field of computer data processing and network security, in particular to an illegal character automatic cleaning system, which comprises a rule compiling module for monitoring rule change, performing semantic fusion and topological mapping on a rule set, constructing a deterministic finite automaton and mapping the deterministic finite automaton into a state transition table; the state switching module is used for constructing a double-buffer context and operating lock-free switching through an atomic pointer to realize hot updating; the speculation execution module is used for carrying out vectorization pre-scanning based on a state transition table by utilizing single-instruction multi-data stream parallel loading, identifying a walk path, falling into a safe state for releasing and falling into a trap state for triggering external verification; the self-adaptive feedback module is used for counting trap state triggering frequency, generating a rule allergy report and dynamically adjusting the size of a read fragment; according to the method, the contradiction between rule flexibility and execution efficiency is solved, and high-performance cleaning based on speculative execution is realized.

The application relates to the field of gas pressure safety monitoring, and discloses a multi-scene gas pressure safety guarantee and remote monitoring system. The system comprises a dual-mode sensing module, a topology mapping module, a wave speed cooperation module, a fluid routing module, a routing locking module and a remote monitoring module. The wave speed cooperation module utilizes the difference between the propagation speeds of radio waves and pressure waves to send a preemptive wake-up frame, drives a downstream node to start sampling and backtrack to read a hardware cache before a pressure wave arrives, and realizes complete capture of a transient waveform. The fluid routing module constructs a high-reliability control slice containing only physically connected links and a full-through monitoring slice based on radio frequency based on fluid connectivity parameters. The routing locking module generates cascaded locking instructions bound to the control slice, prevents mis-transmission of the instructions beyond a physical breakpoint by using a routing overhead mechanism, and reports a state after a circuit is opened by the monitoring slice. The application effectively solves the problems of transient leakage of low-power devices and mismatch between wireless control logic and physical topology.

This invention discloses a system for identifying and simulating key nodes in traffic networks based on deep reinforcement learning. Addressing the high computational complexity of key node search and the lack of dynamic verification in traffic networks, this invention employs the following system: a road network topology mapping module parses GIS map data and removes redundant information to generate a weighted topology map; a deep reinforcement learning identification module, based on a deep Q-network, maps node features to graph embedding information through graph representation learning, with the optimization objective of minimizing cumulative normalized connectivity, outputting the optimal key node sequence; and a traffic effect simulation verification module uses a traffic simulation platform to establish a realistic road network model, quantitatively analyzing the impact of key node failures on average travel time and waiting time. This invention features low time complexity, the ability to generalize from small synthetic networks to extremely large-scale real networks, and simulations have verified its high application value in actual traffic management and disaster prevention.

The invention discloses an asset market dynamic valuation method and system based on deep learning, and the method achieves the dynamic updating of the asset value through adaptive multi-source heterogeneous data fusion and time sequence dependence modeling, and comprises the steps: S1, ubiquitous heterogeneous data integration; s2, performing dynamic noise cleaning and feature alignment; s3, constructing a multi-order coupling valuation framework; s4, carrying out time-varying feature topological mapping; s5, an adversarial dynamic training mechanism; s6, outputting and correcting a joint estimation state; and S7, an estimation robustness verification module. According to the method, millisecond-level multi-dimensional fusion of satellite images, logistics information and high-frequency transaction data is realized through a space-time tensor compiling technology of multi-source heterogeneous data, and the problem of synchronous lag of derivative signals in a traditional architecture is solved; through reconfigurable feature topology evolution, self-evolution of a factor interaction path when a market structure drastically changes is realized, and the problem of response delay of fixed model topology to industry rotation events is solved.

This invention relates to the field of industrial internet security technology, and discloses a method and system for evaluating industrial internet data security protection capabilities. The method includes acquiring network traffic logs and system response records; performing time-series correlation analysis and sequence causal relationship completion based on the logs and records to obtain a dynamic evolution sequence of attack behavior; constructing an attack path graph model and parsing the correlation structure based on the sequence to obtain an attack path correlation structure; identifying high-latency paths and calculating response time differences to obtain a set of high-latency paths; extracting time feature vectors and quantifying the similarity of protection effectiveness from this set to obtain a quantitative score for path protection effectiveness; combining the score and difference index to perform a comprehensive risk assessment of physical topology mapping and node cascade failure analysis to obtain the system's comprehensive protection weaknesses; and performing adaptive scenario reconstruction closed-loop verification based on the weaknesses. This method can achieve accurate evaluation and dynamic verification of system protection weaknesses in complex adversarial scenarios.

The invention relates to the technical field of power system relay protection and fault detection, and discloses a power distribution network insulation fault detection positioning method and system based on multi-source transient data, and the method comprises the following steps: S1, synchronously collecting a transient traveling wave signal generated by a fault at a monitoring point of a power distribution network, capturing fault initial traveling wave head data reaching each monitoring point; and S2, carrying out time-frequency analysis on the captured initial traveling wave head data. According to the power distribution network insulation fault detection positioning method and system based on the multi-source transient data, a fault branch is directly identified through a unique mapping relation between a high-frequency attenuation spectrum of a traveling wave head and a power distribution network path topology, a unique positioning result is achieved, false point interference is avoided, and the fault detection positioning accuracy is improved through a dynamic topological image and a branch fingerprint database. The method can automatically adapt to the change of a network operation mode, shows strong robustness and practical value for weak fault signals such as high-resistance grounding and a complex network structure, and remarkably improves the fault positioning reliability and operation and maintenance efficiency of the power distribution network.

This application provides a method and related equipment for constructing a skill tree profile of maintenance personnel based on work order task topology mapping, which can improve overall work efficiency. The method includes: acquiring historical work order data from the maintenance work order system, which includes equipment information, task information, and personnel information; performing structured processing on the historical work order data to construct a full lifecycle map of equipment and a personnel skill tree, establishing a bidirectional mapping relationship between task nodes in the equipment lifecycle map and skill nodes in the personnel skill tree through personnel and equipment information; when receiving new work order data, extracting feature information from the new work order data to generate a composite identifier, and verifying the composite identifier against historical composite identifiers in a pre-stored topology cache library, where the composite identifier includes equipment type and task level; if the verification result is invalid, calculating the mapping relationship in real time based on the equipment lifecycle map and the new work order data to obtain the target mapping relationship.

The application relates to the technical field of electric power information communication, and discloses an abnormal behavior detection method and system for an electric power information communication network, which comprises the following steps: collecting traffic data and node connection information in real time, adopting a topological mapping algorithm to construct a network topological representation; analyzing data packet timestamps and source address features based on the representation to determine abnormal indexes; extracting relevant data packet sequences, simulating a propagation process through a path tracking algorithm to obtain a preliminary path; cross- verifying in combination with node position data to determine an abnormal initiation position; obtaining adjacent node logs according to the abnormal position and comparing data packet features to determine a propagation expansion direction; and tracking variation records of data packets in a dynamic network to obtain a complete propagation track. The application can realize accurate and complete abnormal behavior tracking and positioning through real-time topological modeling, multi-dimensional feature analysis, path simulation and cross-verification.

This application discloses a PCBA production control method based on digital twins and edge federated scheduling, including: deploying edge computing nodes at key process equipment to collect data and construct an equipment communication topology mapping table and original state vectors; obtaining enhanced state vectors by predicting production line data through spatiotemporal predictive digital twins; sending probe commands to physical entities and observing response differences, performing physical virtual bidirectional calibration to obtain calibrated state vectors; training a local scheduling strategy model based on the calibrated state vectors, uploading model gradient parameters and contribution proofs based on contract theory, so that the central server performs weighted federated aggregation based on contract weights and reputation values ​​to obtain a global scheduling strategy model; constructing a multi-timescale hierarchical scheduling controller based on the calibrated state vectors and the global scheduling strategy model, generating collaborative scheduling commands and issuing them to production line execution units for collaborative scheduling, significantly improving production line operating efficiency.

The invention relates to the field of robot technology and artificial intelligence, and discloses a robot intelligent obstacle avoidance navigation method based on semantic segmentation and path prediction, which comprises the following steps: an environment perception and modeling stage: identifying social semantic attributes of a dynamic agent and predicting an autonomous intention baseline of the dynamic agent; in the dynamic game topology mapping stage, a master-slave, collaborative or non-cooperative game topology model is selected according to social semantic attributes; an anti-fact reaction generation stage: deducing a reaction track of the dynamic intelligent agent to candidate actions of the robot according to the selected game topology; and a variable structure planning and solving stage: dynamically constructing a joint interaction cost function according to the game topology, and evaluating the candidate actions to solve the optimal action. The problems that a traditional robot navigation strategy is single and cannot adapt to complex social situations are solved, and the navigation safety, efficiency and social adaptability of the robot in a dynamic man-machine coexistence environment are improved.

The application relates to the technical field of electric digital data processing, and discloses a multi-dimensional data logic processing method based on an artificial intelligence algorithm, which comprises the following steps: receiving a target discrete data packet, extracting metadata and calculating a dimension entropy feature vector representing data logic complexity; inputting the vector into a preset topological mapping model to output an initial adjacency matrix; calling a feedback inhibition mask matrix generated based on a historical operator utility state, performing bitwise logical AND operation on the initial adjacency matrix to generate a corrected effective topological matrix; analyzing the matrix, dynamically indexing a logical operator function pointer in an instruction cache, and constructing a directed acyclic execution linked list; and driving a processor to sequentially call logical operator execution operation, wherein the application determines redundant logic nodes in AI prediction through a bitwise operation mask mechanism based on historical feedback, realizes the deterministic convergence of processing delay and the optimal matching of algorithm resource.

This invention relates to the field of game data processing technology, specifically to a method and system for determining the validity of grids in a match-3 game. The method includes the following steps: parsing the acquired game layout configuration data to determine geometric boundary features; traversing each scan line using a scan line algorithm to extract continuous valid intervals; constructing a compact index list containing only valid units based on the valid intervals; and generating interactive objects based on this index list. This invention introduces a discrete topology mapping mechanism to directly locate valid interactive areas, eliminating redundant calculations for invalid empty areas in the traditional full matrix traversal mode. This significantly reduces the time complexity and memory space consumption of logic initialization, solves the technical problem of low efficiency in constructing irregularly shaped layouts, ensures rapid construction and accurate response of game logic in complex terrain scenes, and effectively improves the frame rate stability and user interaction smoothness.

The application relates to the technical field of underground pipe gallery asset management, and discloses a BIM-driven underground pipe gallery asset dynamic management and emergency decision-making platform, which comprises the following: a dynamic topological mapping module, which realizes dynamic grid density adjustment of a BIM model by monitoring an environmental parameter change rate, and generates a logical topological network in real time, which is synchronous with a physical pipe gallery structure; an asset state reverse derivation unit, which reversely deduces asset deterioration based on environmental data by using a physical law library loaded dynamically in a time domain; a logic rule self-triggering engine, which constructs a multistage response rule chain containing time and space prediction, and optimizes an emergency plan; and an edge-cloud collaborative architecture, which realizes real-time decision-making with low bandwidth dependence through intelligent caching and asynchronous incremental synchronization. When the dynamic topological mapping is driven by the environmental parameter change rate, the real-time state of the underground pipe gallery can be more finely characterized, and a high-reliability data basis is provided for subsequent accurate analysis and decision-making.

This invention relates to a smart device connectivity maintenance method for automatic switching of multimodal communication links, aiming to solve the problems of inconsistent state data, context drift, and limited real-time adaptability of end-side models in multi-source heterogeneous links. The technical solution uses a graph neural network model to perform multimodal standardization, dynamic topology mapping, and deep extraction of spatiotemporal features on link state data, including signal quality, service load, device movement trajectory, and environmental interference information, generating a multi-candidate link switching strategy distribution. On the end side, a lightweight temporal graph neural network is used, along with cloud-based knowledge distillation and single-step strategy alignment mechanisms, to calibrate local inference model parameters in real time, improving the accuracy and robustness of switching decisions. This solution significantly improves the real-time performance, stability, and service continuity of communication link switching, and can adaptively adjust the end-side knowledge synchronization frequency to achieve optimal communication experience under end-cloud collaboration.

This invention relates to the field of intelligent monitoring and fault diagnosis technology for power equipment, specifically a cloud-based intelligent diagnostic system for switchgear status. It includes units for multi-source topology mapping, physical constraint embedding, global state reconstruction, residual decoupling diagnosis, and adaptive parameter correction. The system maps sensor data into a dynamic graph structure and generates constraint vectors using physical conservation logic. Its core is to correct the state based on physical constraints to reconstruct the state graph, locate faults by calculating the residual sequence between measured data and the reconstructed graph, and establish feedback closed-loop correction parameters. This invention achieves zero-sample diagnosis without relying on a large number of samples, solving the problem of pure data-driven solutions failing due to a lack of fault samples.

The invention relates to the technical field of big data processing and information security, and discloses a cloud architecture-oriented multi-dimensional credit data processing system. Comprising a multi-source data acquisition and standardization module, a multi-dimensional space-time topology mapping engine, a query intention analysis and topology preheating module, a cold and hot layered encryption storage scheduler, a path integrity verification and cache management module and an event driving and incremental calculation module. According to the method, a multi-dimensional spatio-temporal topological graph containing entities and field domain nodes is constructed, and the influence of spatial attributes on credit is quantified; performing cold and hot layered encryption storage by utilizing query mode recognition; constructing a cache fingerprint based on the encrypted object to verify the path integrity; and in response to data change, performing dynamic incremental calculation by using a credit potential energy conduction model in combination with a consistency verification result. According to the method, on the premise of ensuring data privacy and consistency, the calculation efficiency and evaluation accuracy of the large-scale credit graph are improved.

The application discloses a kind of based on Internet of Things distributed edge computing system and method, belong to edge computing and intelligent sensing technical field, by constructing node level three-domain coupling model, realize the collaborative modeling of original sampling sequence, clock signal and electromagnetic environment disturbance data;Further identify pseudo-synchronous interval and generate phase distortion indicator function, reconstruct the phase of data;On this basis, extract phase collapse entropy gradient parameter and cross-node phase hysteresis loop area parameter, construct topological mapping matrix to depict phase collapse propagation path;Task dynamic decomposition and path avoidance are realized in combination with the topological mapping matrix, and phase distortion compensation is introduced in asynchronous computing process;Finally, output high-confidence state evaluation results through reverse consistency check and fusion;The application can effectively inhibit the influence of phase collapse, improve the accuracy and stability of distributed edge computing.

The present application relates to a kind of geographic information network topology data visualization method, system, equipment and medium, comprising: using mapping engine to the geographic information non-topology data of acquisition is visualized, obtains non-topology data view;Geographic information topology data of acquisition is converted to coordinates, using the attribute information of geographic information topology data, using topology mapping engine to the geographic information topology data is visualized, obtains topology data view;If new geographic topology point or geographic topology line data is added, then draw new geographic topology point data and new geographic topology line data on topology data view, and the zooming and roaming synchronization of updated topology data view and non-topology data view;If a topology point is moved on topology data view, then based on the position of the topology point data, topology data view and non-topology data view are updated.The present application can be widely applied to geographic information and its geographic information application field.

The invention provides a transformer station insulation tubular bus path trend optimization method comprising the following steps: parallelly constructing an insulation tubular bus topology mapping frame and a bus-level collaborative optimization frame: the insulation tubular bus topology mapping frame splits a bus into bus segment calculation units capable of synchronous optimization, and each unit generates a discrete node chain through iteration according to a starting coordinate under comprehensive constraints; quantizing by a path evaluation model to obtain cost values, and converging the cost values into total topological cost; the latter issues constraints and coordinates through a constraint injection module, and a decision module outputs the total cost. When the framework is constructed, a path evaluation model is firstly established in a bus segment equivalent network, a node coordinate distributor and a cost value collector are configured, and then redundant nodes are identified and removed. According to the method, the global optimality and adaptability of path planning can be improved, the construction cost and the operation and maintenance difficulty are reduced, and the safety and reliability of a power system are enhanced.

The invention relates to the technical field of building energy and building automatic control, in particular to a building curtain wall photovoltaic integrated energy efficiency improving system assisted by artificial intelligence. The data acquisition interface module is used for receiving time sequence data organized according to partitions; the topology mapping management module is used for maintaining a partition-electrical-optical-ventilation topology mapping table; the combined control engine outputs a combined control instruction; the model management module is used for loading and updating a time sequence prediction model and a control strategy; the time scheduling module is used for maintaining the consistency of a control period and a timestamp; and the instruction coding module is used for coding the combined control instruction into a control message output outwards. Through the formed system, unified alignment and unique addressing of multi-source data, joint optimization decision oriented to power generation-comfort-energy storage and versioned and auditing instruction coding and gating issuing are achieved in the same control period, and therefore the problems of cross-subsystem time sequence and collaborative fracture are systematically eliminated.

The application relates to the field of computer-aided design automation, and discloses an automatic document generation system, which comprises a data input analysis module, a trigger rule analysis module, a dynamic topology mapping engine and a multi-version adaptive engine; the data input analysis module is used for reading a structured data file and extracting project parameters and operation instructions; the trigger rule analysis module is connected with the data input analysis module and is used for analyzing special symbols defined by a user based on the operation instructions, and constructing a multi-level trigger rule tree; the dynamic topology mapping engine is connected with the trigger rule analysis module and is used for modeling a template document into a directed acyclic graph, and generating an optimized block operation instruction sequence through matrix operation based on the operation weight of the trigger rule tree; and the multi-version adaptive engine is connected with the dynamic topology mapping engine. Through the version perception decomposition and containerization isolation mechanism of the multi-version adaptive engine, the compatibility problem caused by object structure differences of different versions of AutoCAD files is solved.

The application discloses a power system model simulation test method and device, a terminal and a medium. The technical scheme provided by the application comprises the following steps: first, a first power system simulation model based on conventional simulation software is acquired; then, system steady state and / or fault state simulation is performed through the first power system simulation model to obtain a first simulation data set as a standard data set; then, a second power system simulation model based on second simulation software and having consistent topology and parameters with the first power system simulation model is converted from the first power system simulation model through a topology mapping mode; then, the same system steady state and / or fault state simulation is performed through the second power system simulation model to obtain a second simulation data set as a verification data set; finally, the simulation test result of the second power system simulation model is determined according to the comparison result of the first simulation data set and the second simulation data set, and the efficiency of the model comparison test process is improved.

This invention relates to the field of emergency management technology, specifically to a dynamic emergency material dispatching system and method based on multi-source sensing and digital twins. It includes: a multi-source sensing data acquisition and preprocessing unit; a digital twin construction and situational simulation unit; an intelligent emergency material dispatching decision-making unit; and a dispatching execution feedback and adjustment unit. This invention combines dynamic connectivity verification and dynamic passage risk thresholds using digital twins to achieve road network neighborhood shrinkage, limiting the algorithm search space to a subset of feasible paths, reducing edge computing load, and improving dispatching optimization efficiency and topology mapping accuracy. Simultaneously, it employs a three-variable coupled coding system to integrate core dispatching variables, allowing for local iteration only on affected segments during sudden situational changes, avoiding global recalculation; and relies on execution feedback to achieve virtual-real synchronization, shortening the scheme adjustment cycle and ensuring the compliance of multi-variable optimization constraints.