151 results about "Grid network" patented technology

The invention discloses a micro-grid network topology flexible configuration method based on matrix topology, and relates to the field of micro-grids, and the method comprises the steps: constructing a heterogeneous database of a micro-grid network and equipment; mapping a micro-grid network and equipment into a graph structure, and constructing a graph neural network model; setting mapping strategies of different heterogeneous hardware units according to heterogeneous characteristics of the different heterogeneous hardware units, and constructing a scheduling model of the heterogeneous hardware units by adopting a reinforcement learning algorithm; inputting the preprocessed data into a graph neural network model to obtain an incidence relation between a micro-grid network topology structure and equipment parameters, and taking the incidence relation as a constraint condition; inputting the preprocessed data into a scheduling model to obtain a scheduling strategy of the heterogeneous hardware unit, and taking the scheduling strategy as an optimization target; constructing a multi-objective function of micro-grid network topology optimization; and solving the multi-objective function of the microgrid network topology optimization by adopting an intelligent algorithm, and generating a microgrid network topology scheme. According to the invention, the robustness of the topology scheme is improved.

The invention relates to an intelligent power grid communication optimization method based on HPLC and HRF dual-mode communication, and the method is characterized in that the method comprises the following steps: S1, obtaining power grid communication data, and carrying out the preprocessing of the data; s2, according to the preprocessed intelligent power grid communication data, a feature extractor based on a deep neural network automatically extracts two-channel time-frequency domain features, feature importance of different modes is dynamically weighted through an attention mechanism, and a unified channel state matrix CSM after fusion is obtained; s3, constructing a routing strategy model based on reinforcement learning, and obtaining an optimal path decision according to the CSM matrix, the power grid network topology and the service priority label; s4, according to the path obtained by the optimal path decision, adaptive modulation coding is adopted to obtain an optimal modulation coding scheme and a dynamic adaptive channel condition; and S5, performing communication according to the optimal modulation coding scheme and the dynamic adaptive channel condition. According to the method, the communication state sensing capability in a complex scene is remarkably improved.

The invention provides a control method and system for automatic carrying equipment of a special transportation line. The method comprises the following steps: constructing a local environment model based on micro-gridding to collect and transmit equipment state information; performing task allocation and path planning on the automation equipment according to the micro-grid environment model; dynamically optimizing task allocation and path planning in a global range according to the task allocation and path planning in each micro-grid; the execution conditions of optimized task allocation and path planning are monitored in real time, the execution sequence of tasks and path planning are dynamically adjusted through an intelligent scheduling algorithm, and flexible adaptive adjustment is made according to resource states and environment changes. Through combination of the micro-grid network and the ant colony algorithm, the problems of single-point fault risk, poor path planning adaptability, inflexible task scheduling and the like in a traditional automatic transportation system are solved, and a brand new solution is provided for efficient, reliable and flexible operation of an automatic transportation special line.

The invention relates to a three-dimensional occupied grid network sensing method, which comprises the following steps of: acquiring a multi-view camera image shot by automatic driving of a vehicle, inputting the multi-view camera image into an image processing backbone network, and extracting two-dimensional image features; performing view angle conversion on the two-dimensional image features to obtain three-dimensional body features; constructing matching cost body features according to the geometric correspondence of the sampling points at different moments; a convolutional neural network is adopted to extract weights containing depth correction information from the matching cost body features, the weights act on the three-dimensional body features at the current moment, and the three-dimensional body features after depth information correction are obtained; and inputting the three-dimensional body features into an occupied grid decoder, projecting the three-dimensional body features to a discrete semantic space, and generating a three-dimensional semantic occupied grid. Compared with the prior art, by constructing the matching cost body, more accurate depth information and geometric understanding can be obtained, the calculation overhead under a long time sequence is reduced, and accurate and efficient modeling of the automatic driving environment can be realized.

The invention relates to the field of aided design of construction roads, and discloses a planning method for a temporary construction road of a power transmission line, which comprises the following steps: acquiring elevation data, topographic parameters, tower position data, existing road information and raster data of a construction area of the power transmission line; constructing an initial grid network based on a grid method, converting the elevation data into grid elevation values, and storing the grid elevation values into the initial grid network; constructing a final grid network with a communication relationship by taking a slope angle between adjacent grids of the initial grid network and the communication cost of the topographic parameters corresponding to the grids as constraint conditions; constructing a moving window to search the final grid network, and constructing a weighted directed graph; and determining a starting point and an end point of the power transmission line, and searching the weighted directed graph based on an improved Dijkstra algorithm to obtain a design scheme of an optimal temporary construction road with the minimum total construction cost between the starting point and the end point. The accuracy and reliability of temporary construction road planning of the power transmission line can be improved.

The invention discloses a path planning method based on an improved DQN algorithm. The path planning method aims at selecting a collision-free path to reach an ideal position. Path planning needs to solve the problems of target reaching, obstacle bypassing and the like, and an environment map needs to be preset in a traditional method. The deep reinforcement learning is used for solving a dynamic path planning problem, and a common path planning method is separated from online. DRL learns an optimal strategy through trial and error and environment interaction, and a DQN algorithm is applied to path planning but has the problems of slow convergence and the like. According to the improved DQN path planning algorithm and system provided by the invention, the problem is replayed and solved by improving a reward function and an action selection strategy and introducing prior knowledge and prior experience. Comprising the steps of constructing a two-dimensional grid network environment map, constructing, improving and optimizing a DQN path planning model based on the two-dimensional grid network environment map and a Markov decision process, improving strategy covering reward modeling, designing an attenuated epsilon-greedy strategy, and introducing prior knowledge and prior experience for replaying.

The embodiments of the present application relate to the technical field of wireless communications. Provided are a beam pair determination method and apparatus. The beam pair determination method comprises: a network device sending configuration information to a terminal device in a communication area where the network device is located; the terminal device performing configuration of a coordinate grid network on the basis of the configuration information, the coordinate grid network being used for indicating a grid-shaped vertical plane and / or a grid-shaped horizontal plane of the communication area; the terminal device acquiring beam pair quality information corresponding to at least one round of beam pair scanning and / or state change information of the terminal device corresponding to the at least one round of beam pair scanning, and reporting same to the network device; and on the basis of the beam pair quality information corresponding to at least one round of beam pair scanning and / or the state change information of the terminal device corresponding to the at least one round of beam pair scanning, the network device determining an optimal beam pair, the state change information being used for indicating a state change condition of the terminal device during the process of the at least one round of beam pair scanning, and the state change information corresponding to the coordinate grid network. The present application can improve the accuracy of beam pair determination and take into account the privacy of a terminal device.

The invention belongs to the technical field of energy scheduling optimization, and provides a power distribution network distributed energy scheduling optimization method and a related device, and the method comprises the steps: taking the operation cost of a power distribution network as a target function, taking the operation limitation of all equipment in the power distribution network as a constraint condition, and constructing a power distribution network distributed energy operation optimization problem model; based on a power distribution network distributed energy operation optimization problem model, constructing a multi-agent reinforcement learning agent set, and converting an active power distribution network distributed energy operation optimization problem into a Markov decision process; and a multi-agent reinforcement learning framework is constructed, multi-agent training is carried out, and an optimization strategy is obtained after training is completed. According to the multi-agent training framework, the decision-making process of multiple agents can be processed in parallel, and the time required for strategy generation is greatly shortened. And in a dynamically changing power grid environment, the possibility is provided for immediately adjusting and optimizing an operation strategy, so that the overall operation efficiency of the power distribution network is effectively improved.

The invention provides a three-dimensional occupancy prediction method and a three-dimensional occupancy prediction device. The method comprises the following steps: acquiring a multi-view image of a surrounding environment of a vehicle by using a sensor, processing the multi-view image by using a basic occupancy prediction model to obtain a three-dimensional grid network of the multi-view image, performing feature extraction on the three-dimensional grid network to obtain voxel features of the multi-view image, and determining the voxel features of the multi-view image according to the voxel features of the multi-view image. The voxel features serve as conditional variables to guide generation of a diffusion model, and the diffusion model is used for conducting three-dimensional occupancy prediction on the surrounding environment of the vehicle. According to the three-dimensional occupancy prediction method, the voxel features of the three-dimensional grid network of the known scene serve as conditional variables to guide generation of the diffusion model, the diffusion model can be helped to improve the accuracy of occupancy grid generation, missing data caused by shielding and other reasons are filled, a complete occupancy map is generated, and the prediction efficiency is improved. And the generated map is ensured to accord with the actual situation.

The invention relates to the technical field of traffic control, in particular to an airspace situation prediction method and system based on a self-adaptive grid, and the method comprises the following steps: collecting the information of all aircrafts in a current airspace, including the number, speed, x coordinate, y coordinate, z coordinate, course, pitch angle and time of the aircrafts; according to the x coordinate, the y coordinate and the z coordinate of the aircraft, mapping the acquired information of the aircraft into grids of a pre-constructed airspace basic grid network, and obtaining an input feature sequence; and inputting the input feature sequence into an airspace grid situation prediction model based on 3D CNN-GCN-Transform, and outputting to obtain an airspace situation prediction result. According to the invention, accurate prediction of airspace situation change can be realized, and technical support is provided for air traffic control.

A system for performing a three-dimensional computer vision task using a neural radiance field grid representation of a scene produced from two-dimensional images of at least a portion of the scene can include a processor and a memory. A neural radiance field grid network module can produce, from the two-dimensional images, three-dimensional patches of the neural radiance field grid representation of the scene. A three-dimensional shifted window visual transformer module can produce, from the three-dimensional patches, a feature map. A first decoder module can produce, from the feature map, the neural radiance field grid representation of the scene to train the system. A second decoder module can produce, from the feature map, the neural radiance field grid representation of the scene to perform the three-dimensional computer vision task for a cyber-physical system.

The invention relates to the technical field of power transmission line terrain analysis, in particular to a power transmission line terrain analysis method and device based on grid communication and a storage medium. The method comprises the following steps: firstly, acquiring digital elevation data of a power transmission line path area, and establishing a grid network by taking a certain point in the area as a rectangular corner point; taking any point in the grid as a starting point, setting a calculation radius, extracting terrain elevation data in the range, and calculating the maximum height difference with the starting point; and dividing the discrete network according to the height difference based on engineering technical and economic definition, and determining a terrain classification result of the initial grid. And iteratively calculating the terrain classification of each grid in the path region through a preset sampling step length, and communicating the grids of the same type. And according to a preset filtering area threshold value, filtering out grids of which the area is smaller than the threshold value, and obtaining a final terrain analysis result. According to the method, terrain analysis of the long-distance and large-span power transmission line can be realized, model selection errors caused by subjective judgment or low-precision data are avoided, and the design efficiency is improved.

The embodiment of the invention provides a beam pair determination method and device, and relates to the technical field of wireless communication, and the beam pair determination method comprises the steps that network equipment sends configuration information to terminal equipment in a communication area where the network equipment is located; the terminal equipment configures a coordinate grid network according to the configuration information, wherein the coordinate grid network is used for indicating a grid-shaped vertical plane and / or a grid-shaped horizontal plane of the communication area; the terminal device obtains and reports the beam pair quality information corresponding to the at least one round of beam pair scanning and / or the state change information of the terminal device to the network device, and the network device determines an optimal beam pair based on the beam pair quality information corresponding to the at least one round of beam pair scanning and / or the state change information of the terminal device; wherein the state change information is used for indicating the state change condition of the terminal equipment in at least one round of beam pair scanning process; the state change information corresponds to the coordinate grid network. According to the invention, the accuracy of determining the beam pair can be improved, and the privacy of the terminal equipment is considered.

The invention discloses a multi-agent conflict-free path planning method based on a directed space-time network and forward direction decision, which comprises the following steps: 1, acquiring environment information, constructing a grid network according to the environment information, and constructing a directed space-time road network for the grid network by using the space-time network, initializing starting and ending point information of the robot group according to the directed space-time road network; 2, establishing a forward direction decision model of the agent group, and avoiding conflicts by using constraint conditions of the model; and 3, solving a forward direction decision model of the agent group, and planning an overall optimal path. According to the method, the directed space-time road network can be constructed by utilizing the space-time network to accurately describe the environment, the agents and the tasks, the path of the agents is planned by utilizing the advancing direction decision model, and the possibility of multi-agent conflict is avoided, so that the feasibility of the path is ensured, and the efficiency and the safety of multi-agent path planning can be improved.

The invention provides a smart power grid false data injection attack defense method based on a two-person zero sum game. The method comprises the following steps: step 1, constructing a smart power grid network structure model; 2, constructing a false data injection attack attack and defense model; 3, establishing an interaction scene and a task space; and step 4, realizing optimal defense strategy solution based on a depth deterministic strategy gradient algorithm. According to the method, the false data injection attack and defense behavior in the smart power grid are modeled based on the two-person zero-sum game theory, a reward function is set, an approximate Nash equilibrium point in the game is solved through a depth deterministic strategy gradient algorithm, and then the optimal defense strategy is obtained. According to the method, modeling is set to be a continuous process, compared with a discrete process, propagation of malicious software in the real world can be better described, and meanwhile the two-person zero-sum game problem with the continuous action space can be effectively solved through the used depth deterministic strategy gradient algorithm.

The embodiment of the invention discloses a power distribution network fault isolation method, electronic equipment and a storage medium. The method comprises the following steps: for a power distribution network to be subjected to fault isolation, determining an initial island division scheme based on a power grid network structure of the power distribution network and a fault area in the power distribution network; optimizing the initial island division scheme based on a preset cuckoo search algorithm to obtain an optimized island division scheme, and optimizing the optimized island division scheme based on a preset simulated annealing algorithm to obtain a target island division scheme; and isolating the fault area based on the target island division scheme. According to the technical scheme of the embodiment of the invention, the influence of the power distribution network fault on the whole power distribution network area can be reduced to the greatest extent.

The invention relates to an intelligent power grid optimization control method based on dynamic network topology reconstruction. The process comprises the following steps: establishing a mixed integer linear programming optimization model; screening the optimal deployment position of the loop closing device; actual power grid data are collected in real time, the net load fluctuation range of each power grid node is calculated, the flexible supply and demand state of a power grid line is evaluated, and if the flexible demand of the power grid line exceeds the supply or power flow out-of-limit, the optimal power regulation quantity and the optimal power grid network topology structure of a loop closing device are calculated; deploying the loop closing device according to the optimal deployment position and the optimal power regulation quantity of the loop closing device, changing a power grid connection structure according to the optimal power grid network topology structure, and optimally controlling an actual power grid; and calculating to obtain the power grid performance after the deployment of the loop closing device, and if any power grid performance is lower than a preset threshold value, carrying out the above process again. Compared with the prior art, the power of the network topology and the loop closing device can be quickly adjusted according to the actual power grid condition.

The invention discloses a multi-robot conflict-free path planning method combining bilevel planning and a response algorithm, and the method comprises the steps: 1, obtaining the current environment information, constructing a grid network of a certain scale, and constructing a directed space-time road network by considering a time set; 2, initially setting robot group information, and constructing a robot group path planning scheme including starting and ending points of a plurality of robots, path constraints, space-time paths and path costs; 3, obtaining initial shortest paths of all the robots by using a Dijkstra algorithm, detecting path conflicts, and setting a robot group position index and a walking priority sorting scheme so as to perform path re-planning on the corresponding robots; and 4, transforming the walking priority sequence of the robot group in the upper-layer planning by using a genetic algorithm. According to the method, the directed space-time road network can be utilized to more accurately describe the environment, the robots and the conflicts, and the problem of multi-robot conflict resolution is better solved through the path constraint in the road network, so that the feasibility of the multi-robot path can be ensured.

The present invention provides a bottom-up intelligent identification method for land space based on grid, including: step 1, obtaining study area data and reclassifying point of interest data; step 2, identifying the initial land use type based on remote sensing image features; step 3, using the kernel density estimation algorithm to perform spatial estimation on the reclassified point of interest data to obtain the subdivided land use type; step 4, constructing a main function grid based on the subdivided land use type and determining the optimal scale of the grid, identifying the main function of the grid, and obtaining an estimated main function grid; step 5, using an unsupervised classification algorithm to obtain the initial land space pattern; step 6, performing spatial overlay analysis on the estimated main function grid and the initial land space pattern to obtain the final land space pattern. This application effectively solves the current problem of difficulty in unifying land space identification, monitoring and management, and lays the foundation for digital governance of land space.

A data broadcasting method, a network-on-chip, a chip and a data processing method, the data broadcasting method comprising: a node needing to transmit broadcast data carries a predetermined identifier in a broadcast message packet used for transmitting the broadcast data and sends the broadcast message packet, and the node receiving the broadcast message packet transmits the broadcast data to the node according to the predetermined identifier. According to the method and the device, whether the broadcast data carried by the received broadcast message packet is stored or not is determined, and when the node is an intermediate node on the transmission path of the received broadcast message packet, the received broadcast message packet is forwarded, so that the number of the message packets is greatly reduced, the load of a mesh network is effectively reduced, the transmission time of the message packets is shortened, and the transmission efficiency of the mesh network is improved. The data transmission efficiency is improved, the effect of broadcasting the data can be achieved by adding the predetermined identifier for indication, and the data broadcasting can be realized under the condition of simply modifying the transmission protocol without modifying the network grid hardware, so that the cost is low, and the implementation is easy.

Devices, systems, and methods for automatically provisioning containerized intelligent electronic devices (IEDs) of a grid network include identifying, by a device management system, basic details of a containerized IED provided by the containerized IED; determining, based on the basic details, that the containerized IED is running in the network; identifying, based on the basic details, a secure login for the containerized IED; sending a secure login request to the containerized IED based on the secure login; receiving, based on the secure login request, advanced details of the containerized IED provided by the containerized IED; identifying, based on the advanced details, an upgrade available to an application of the containerized IED; instruct a backup virtual machine of the containerized IED to run the upgraded application; and monitoring new upgrades and applications available for containerized IEDs in the network.

The invention provides an improved D * lite path planning method and system based on spatial obstacle degree, and relates to the technical field of unmanned aerial vehicle navigation. The method comprises the following steps: 1) obtaining a three-dimensional point cloud map to form a three-dimensional point cloud grid map; 2) expanding each grid in the three-dimensional point cloud map according to the safety margin of the unmanned aerial vehicle; 3) counting the number of times that each grid is covered by the expansion area; 4) quantizing the counted data to obtain the neighborhood obstacle degree of the grid; 5) forming an obstacle degree map according to the neighborhood obstacle degree of each grid; 6) improving the moving cost of the traditional D * lite algorithm according to the obstacle degree map; and 7) according to the expanded grid network map, performing path planning by using an improved D * lite algorithm to realize unmanned aerial vehicle return path planning. The problems that a traditional electric power inspection method is insufficient in obstacle sensitivity and unsmooth in homing path are effectively solved, and rapid and safe homing of the unmanned aerial vehicle is guaranteed.

The application discloses a regional scale landscape ecological risk index data production method based on ArcPy, and comprises the following steps: step 1, converting a grid network into vector data; step 2, calculating sample data, wherein the sample data is used for counting the frequency of a certain landscape type in a sample data in a patch; step 3, defining a landscape ecological risk index core function; and step 4, calculating a landscape ecological risk index. The application provides a regional scale landscape ecological risk index data production method based on ArcPy, greatly improves the efficiency of automatically calculating a landscape ecological risk index at a regional scale or even a continental scale, and effectively solves the problems of excessive program memory consumption, a complex manual calculation process and a large amount of data processing workload in the prior art when processing regional scale or continental scale data.

The embodiment of the invention relates to a grid spatio-temporal data processing method and device, and the method comprises the steps: carrying out the grid division of a specified road network region according to an H3 grid format, creating a corresponding grid spatio-temporal data table for a grid network, recording the data table as an H3 grid hash table, and storing the H3 grid hash table based on a distributed database; performing queue record rolling adding processing on all grid chain tables of the H3 grid hash table according to a rolling interval t, and performing grid object updating processing on the H3 grid hash table based on real-time traffic feedback of a specified road network area; and when a traffic information query instruction input by a user is received, performing grid spatio-temporal data query on the H3 grid hash table based on the traffic information query instruction, and performing traffic information analysis based on a query result to obtain corresponding instruction feedback data to be fed back to the current user. According to the invention, the dynamic H3 grid can be constructed, and the real-time query service can be provided for the user.

The invention discloses a geographic entity position offset correction method and system, and relates to the field of data information processing. The method comprises the steps of creating a longitude and latitude grid network of a target area; establishing a coordinate mapping network and a positive and negative coordinate transformation relation between the spherical coordinates and the plane coordinates of the online map; acquiring spatial data of the target entity from the longitude and latitude grid network of the target area; based on the coordinate mapping network and the positive and negative coordinate transformation relation, converting the spatial data of the target entity into surface data of the target entity, and converting the surface data of the target entity into point data of the target entity through an entity matching algorithm; and carrying out geometric correction on the point data of the target entity to obtain the geometrically corrected spatial data corresponding to the target entity. According to the scheme, through coordinate transformation and geometric correction, position deviation caused by coordinate deviation in the map is eliminated, the accuracy and reliability of geographic entity positioning are improved, and accurate and reliable data support is provided for building planning and decision making.

The invention belongs to the technical field of metal casting, and particularly relates to a method for inhibiting macrosegregation of elements in the solidification process of a large cast ingot through a grating method. The method comprises the following steps: preparing a plurality of cylindrical metal bars with the same components as a cast ingot target, wherein each metal bar has a stepped melting point structure; establishing a virtual grid network of the cross section of the cast ingot, and dividing the cross section into a matrix node array; the solidification front edge position is monitored in real time, and when a solidification layer reaches grid node coordinates, a metal rod is vertically inserted into a cast ingot through a hydraulic servo mechanism; and applying a micro-area energy field on the surface of the metal rod, namely coating a heat release coating and applying electromagnetic oscillation. According to the method, the ingot casting temperature field real-time mapping model is established, and the large ingot casting solidification process is accurately intervened. On the basis of a grating method, a metal rod is combined with an exothermic coating and mechanical disturbance to delay local solidification, and macrosegregation of elements of a large cast ingot is remarkably improved.

The present invention relates to a method for calculating and providing a lane path of a road using a central computing unit that is connected to vehicles in a vehicle group in a data-technical manner. According to the present invention, the method comprises the following steps: providing a geometric map (K) including geometric lane boundaries (S), applying a grid network (G) having grid cells (G1 to G49) of a predetermined size to the map (K), collecting fleet data of the vehicles in the vehicle group, including a position sequence in which the vehicles in the vehicle group travel, calculating the orientation of the vehicles at the positions of the grid cells (G1 to G49) from the collected position sequence, discretizing the calculated vehicle orientation, generating a histogram (H) for each of the discretized vehicle orientations calculated at the positions of the respective grid cells (G1 to G49) for each individual grid cell position, selecting a map section having a predetermined number of grid cells (G1 to G49), and calculating a lane path in the map section using a learning-based method from the histogram (H) created for the grid cells (G1 to G49) of the map section and the geometric lane boundary (S) in the map section.

The present application discloses a method, device, equipment and medium for label determination, and relates to the field of computer technology. The method comprises: obtaining point cloud semantic information of multiple frames of point clouds to be processed in a specified area; classifying and processing the point cloud semantic information of each frame to obtain static semantic point cloud and dynamic semantic point cloud of each frame; splicing the static semantic point cloud and dynamic semantic point cloud of each frame respectively to obtain dense static semantic point cloud and dense dynamic semantic point cloud; based on the dense static semantic point cloud and dense dynamic semantic point cloud, using a merging strategy, determining the dense semantic point cloud of each frame; based on the voxel grid network of the specified area, voxelizing each point cloud in the dense semantic point cloud of each frame to obtain the point cloud occupancy of each voxel grid; based on the point cloud occupancy of each voxel grid, selecting and processing the semantics of the point cloud in each voxel grid to obtain the occupied grid semantic label.

The present application relates to the technical field of reservoir capacity curve reconstruction, in particular to a reservoir capacity curve reconstruction method and system based on multi-source data fusion, comprising the following steps: obtaining multi-source data fusion elevation information, reconstructing the water level-storage capacity relationship curve, and outputting the reservoir capacity curve reconstruction graphical expression result. In the present application, the water body boundary surface information is obtained by fusing the unmanned aerial vehicle remote sensing image to identify the boundary pixel area, the abnormal water level line number is identified by combining the difference index comparison, the complete three-dimensional fusion data set is constructed by matching the water point cloud and the underwater elevation data, the grid network is generated according to the unified projection and the abnormal elevation points are corrected, the continuous trajectory line sequence is established and integrated to form the two-dimensional boundary expression, which can quickly identify the reservoir capacity change in the dynamic environment, effectively avoid the incomplete boundary extraction and the data precision decline caused by the complex terrain and the tedious operation in the traditional measurement method, and improve the comprehensive performance of the reservoir capacity curve reconstruction in the spatial coverage, data updating and expression precision.

The invention discloses a mesh network topology management method, a mesh network topology management device and electronic equipment. The method is used for gateway devices in a mesh network, the mesh network comprises a plurality of gateway devices and a plurality of node devices, and the method comprises the following steps: acquiring first network information between the plurality of gateway devices and the node devices; obtaining first target data; and selecting a first target gateway device from the plurality of gateway devices according to the first network information, so as to send first target data to the target node device through the first target gateway device. By adopting the processing mode, when the data is sent to the node equipment, the plurality of gateway equipment cooperatively manage the network topology, and one better gateway equipment is selected to send the data to the node equipment, so that only one communication link exists in the same physical space, the interference of wireless signals in the air is avoided, and the data transmission efficiency is improved. Network congestion and transmission delay are avoided; therefore, the data transmission efficiency and the user experience can be effectively improved.