713 results about "Electronic map" patented technology

The invention relates to the technical field of path planning, in particular to a path planning method and system for an inspection robot, and provides the following scheme: executing an inspection task through an initial electronic map, collecting first image data and pose information, recognizing an inspection target, completing image registration, and generating second image data; inverting and calibrating the optimal observation direction based on the structural sensitivity distribution of the local visual features and the illumination variation trend, and determining the shooting position and angle to form a path node; a multi-objective optimization model is adopted, the path length, the view angle continuity and the illumination interference are comprehensively considered, and an optimal inspection path is generated; the method is suitable for outdoor inspection scenes with complex structures and non-uniform target distribution.

The invention discloses a land investigation quality monitoring system for remote sensing image intelligent segmentation and ground feature recognition, and relates to the technical field of remote sensing, and the system comprises an image recognition module, a label comparison module and a monitoring module, and specifically carries out the remote sensing image acquisition of a to-be-monitored land through a remote sensing sensor, and carries out the structural complexity analysis and image region division. The method comprises the steps of forming a non-uniform region set, analyzing and acquiring category probability vectors of pixel positions of all regions in the formed non-uniform region set to construct a tag map of a whole remote sensing image, comparing pixel-by-pixel categories on a current tag map and a reference tag map to form a change mask map, identifying a structural change region according to the change mask map, and identifying a structural change region through sequential analysis. And determining whether the corresponding candidate tag inconsistent region under different time phase conditions is still a structural change region, so as to obtain a judgment result, and updating the electronic map based on the judgment result.

The invention relates to the technical field of path planning, and discloses a path planning method and system of an AGV (Automatic Guided Vehicle) for a silver electrolysis process workshop. The method comprises the following steps: carrying out environment characteristic acquisition and electronic map construction on a silver electrolysis process workshop to obtain a silver electrolysis process workshop electronic map; calculating an initial optimal path of the AGV from the current position to the target workstation; detecting the actual driving resistance in the execution process of the initial optimal path to obtain a path correction parameter; performing local adjustment to obtain an energy-saving safe path; and in the process that the AGV executes the energy-saving safe path, the front moving obstacle and the electrolyte leakage area are monitored in real time, and a temporary detour path is generated. According to the application, the path planning is more suitable for the actual environment characteristics of the silver electrolysis workshop, the emergency situation of the silver electrolysis workshop can be timely handled, the equipment safety and the production continuity are guaranteed, the no-load rate of the AGV is reduced, and the overall logistics efficiency of the silver electrolysis workshop is improved.

The invention discloses a robot dog inspection path intelligent planning and dynamic adjustment method, system and device and a medium, and belongs to the technical field of robot path planning, and the method comprises the steps: calculating a task emergency degree index according to a weight coefficient of an inspection point and a time constraint, and determining a task priority; constructing a hierarchical electronic map containing the terrain difficulty coefficient and the moving cost; performing global path planning through a comprehensive cost function by adopting an A star algorithm; environment information is collected in real time through multiple sensors, and the dynamic obstacle layer is updated; performing real-time trajectory optimization by adopting a local path planning mode; selecting local path correction or global path re-planning according to the path execution state score; energy needed for completing the remaining tasks is predicted, and a charging path is planned when necessary. According to the invention, multi-target adaptive optimization of path planning is realized, a coordination mechanism of global planning and local adjustment is established, and the execution efficiency and reliability of inspection tasks are improved.

The invention relates to the technical field of position tracking, in particular to an intelligent bracelet real-time position tracking visualization method and system. The method comprises the following steps: acquiring multi-dimensional sensing monitoring parameters of a user based on a smart bracelet, performing real-time motion state evaluation of the user, and performing adaptive adjustment of a position acquisition frequency to generate an adaptive position acquisition frequency; performing real-time position positioning acquisition based on the adaptive position acquisition frequency, and performing frequency-by-frequency spatial position positioning calculation to obtain a high-precision compensation reconstruction trajectory; the method comprises the following steps: acquiring public electronic map information, performing scene key element identification, and performing key attribute cognitive marking to obtain a plurality of scene attribute memory anchor points; and performing relative position distribution analysis on the high-precision compensation reconstruction trajectory based on a plurality of scene attribute memory anchor points, and constructing an anchor point space trajectory visual mapping graph. According to the invention, high-precision real-time position tracking of the user is realized, and clear and visual multi-level map information rendering is presented.

The invention relates to the technical field of agricultural intelligent equipment, in particular to a field sowing grain distance detection system and method based on computer vision, and the method comprises the steps that an image collection module collects 4KRGB and near-infrared data of a sowing area; the image processing module is used for processing and correcting the acquired image in real time; the grain distance feature deep learning analyzer strengthens seed feature extraction through an attention mechanism based on an improved YOLOv5 algorithm, accurately distinguishes weeds from seeds, and calculates a center distance deviation value of adjacent seeds based on a preset target grain distance; the positioning fusion module fuses Beidou positioning data and a visual odometer track, generates seed longitude and latitude and burial depth coordinates by using a high-precision farmland surface elevation model, and maps the seed longitude and latitude and burial depth coordinates to a farmland electronic map; and the dynamic regulation and control execution mechanism adjusts the rotating speed of the seeder or the seeding gap according to the grain distance deviation value and a priority strategy, and dynamically corrects the grain distance. Therefore, the problems of high detection error rate, single detection algorithm, poor data relevance and the like in the prior art are solved.

The invention discloses an action management identification method based on earthquake site disaster investigation, and relates to the technical field of data processing, and the method comprises the steps: determining a to-be-acted earthquake site region, and planning a disaster search task corresponding to a plurality of unmanned aerial vehicles in the to-be-acted earthquake site region; issuing the disaster situation search task to multiple unmanned aerial vehicles, controlling the unmanned aerial vehicles to execute the disaster situation search task, and obtaining an actual disaster situation investigation result corresponding to the disaster situation search task; according to an actual disaster situation investigation result, generating disaster situation points on the electronic map corresponding to the earthquake field area to be moved, and obtaining a disaster situation investigation map; and finally, the disaster situation investigation map is fed back to equipment specified by a commander to guide disaster relief actions of the commander, so that the earthquake site disaster situation investigation efficiency is improved, comprehensive disaster situation data can be formed, the commander can comprehensively understand the disaster situation, the commander is assisted to quickly form a global and optimal action scheme, and the disaster relief efficiency of the commander is improved. And the disaster disposal efficiency is improved.

An AI-connected-electrified (ACE) heavy truck system equipped with an intelligent multi-mode hybrid (iMMH) powertrain system and a vehicle supervision control strategy based on machine learning (ML) or reinforcement learning (RL) paradigm are presented. This system ensures industry-leading power and braking performance of the ACE heavy truck while automatically optimizes both energy saving and emission reduction based on the vehicle's dynamic driving data and 3D electronic map information of roads for any transport event. In this application, the conventional analog electronic control (AEC) method is replaced by a novel digital pulse control (DPC) method on the instantaneous power function of the engine. The DPC method converts the complex surface working conditions of the AEC engine of the hybrid vehicles into simpler pre-defined working condition lines of the DPC engine. Consequently, the multi-variable nonlinear technical problem of simultaneously optimizing real driving environment (RDE) fuel consumption and pollutant emissions of the ACE heavy truck is simplified into two decoupled quasi-liner optimization problems, and ensures the reduction of on-vehicle computing resources for real-time AI inference computation and the improvement of the optimal performance, the convergent rate, and the robustness of the corresponding fuel-saving algorithm for the trained ML model or the learned RL model. Ultimately, the ACE truck achieves in the engineering sense the global minimum RDE fuel consumption and pollutant emissions meeting the standard consistently at high performance to cost ratio for any transport event and the RDE fuel consumption is decoupled from the vehicle configuration parameters and the human driver.

The invention discloses a visual drawing method and device for an inland ship navigation trajectory and a medium, and the method comprises the steps: collecting GPS positioning data, AIS dynamic parameters and static attribute data of a ship through a ship terminal, carrying out the preprocessing of the GPS positioning data and the AIS dynamic parameters, and storing the processed data in a database according to a timestamp index; calling a geocoding service interface, mapping the processed longitude and latitude coordinates of the ship to an electronic navigation channel chart coordinate system, and periodically updating a ship position mark in an electronic map interface; in response to a time period query instruction input by a user, extracting ship track point data corresponding to the timestamp sequence from the database, and superposing the ship track point data to the electronic channel chart to generate a dynamic track line; a user operation instruction is received through the time axis control, the ship mark position and the course display state on the trajectory line are dynamically adjusted, and visualized backtracking of the historical trajectory of the ship is achieved.

The invention discloses an under-mine environment accurate positioning system based on a UWB technology, and relates to the technical field of data processing and positioning, an underground area is divided into a safe area and a dangerous area by obtaining the structure risk value of each sub-area and combining the structure risk value and the position information of the corresponding sub-area, and the safe area and the dangerous area are accurately positioned. A plurality of rescue robots are arranged in the underground area; acquiring position information of the mobile tag, displaying the position information on an electronic map, generating an air quality coefficient, and dividing the plurality of sub-regions into risk regions and safety regions according to the air quality coefficient; and sending inquiry information to the miner, acquiring a corresponding safety coefficient, and if the acquired safety coefficient is lower than a safety threshold value, planning a support path to the miner for the rescue robot, so that the rescue robot rescues the miner along the support path. After the miner is found according to the position information of the miner, the miner is rescued through guidance of the rescue robot, and the miner is prevented from getting lost and being lost.

The invention discloses an environmental sanitation cleaning performance evaluation method and system based on work trajectory recognition, and relates to the technical field of intelligent environmental sanitation work management and performance evaluation, and the method comprises the steps: collecting the multi-source trajectory data of environmental sanitation vehicles and personnel, and generating a standardized trajectory data set through time synchronization, abnormality elimination and space registration; on the basis of the standardized trajectory data set, distinguishing an effective operation section and a non-operation section in combination with operation types, and labeling abnormal behaviors to output a recognition trajectory; carrying out overlay analysis on the recognition track and an electronic map, generating a regional operation completion degree, and outputting a space coverage and anomaly statistical result; and calculating a comprehensive performance score according to a regional operation completion degree result. According to the method, the effective operation section and the abnormal behavior are recognized in combination with the operation type, and the operation authenticity judgment precision is improved; and the identification track and an electronic map are superposed to calculate the work completion degree and generate a spatial statistical result, and finally a quantitative performance score is formed, so that automatic evaluation and refined management of the whole process of environmental sanitation work are realized.

The invention relates to the technical field of AGV scheduling, and particularly discloses a multi-AGV task scheduling system and method for solving an emergency order insertion problem, and the system comprises a task scheduling module, a path planning module, a real-time monitoring module and a map management module. The task scheduling module realizes multi-objective optimization task allocation based on an improved NSGA-II algorithm, optimizes an initialized population through an NNC (Neighbor Construction) strategy, enhances the global search capability in combination with a 2-opt mutation method, and designs an emergency order insertion strategy to dynamically respond to an emergency task; the real-time monitoring module integrates a MySQL database and a Visual Studio interactive interface, and supports electronic map construction (based on ArcMap10.4), AGV state real-time feedback and task dynamic adjustment; the map management module defines workshop layout and road traffic rules. According to the invention, by fusing the multi-objective optimization algorithm and the dynamic path planning technology, the problem of low efficiency of multi-AGV task allocation is solved, and the logistics efficiency and the system robustness of the track equipment assembly workshop are significantly improved.

The invention relates to the field of combat command and dispatch, in particular to a multistage linkage combat unit command and dispatch system. According to the invention, a basic-level minimum emergency unit element information base is constructed through a data acquisition module; generating an electronic map supporting 2D and 3D switching; an intelligent analysis early warning module identifies abnormal conditions and generates early warning information; a plurality of multi-level linkage combat unit topology networks are generated through the multi-level linkage command architecture module; generating a command data large screen for dynamically aggregating public security indexes and a global situation visualization electronic map through a global situation visualization module; an early warning area is circled and selected through the intelligent scheduling module; and associating the corresponding multi-stage linkage combat unit to generate a deployment instruction. According to the multi-level linkage combat unit command and dispatch system provided by the invention, the multi-level linkage combat unit is effectively combined with a dynamic visual geographical environment from data acquisition, analysis and early warning to command and dispatch through cooperation of multiple modules, so that the command and dispatch efficiency is remarkably improved.

The invention discloses an underground pipeline detection method and system based on multi-source data fusion and intelligent analysis, and belongs to the technical field of pipeline detection. The method comprises the steps of collecting multi-source data of a target area; wherein the multi-source data comprises electromagnetic signal data, electromagnetic wave reflection data and sound wave propagation data; performing filtering and normalization preprocessing on the multi-source data to obtain target data; constructing a multi-source data fusion model to perform feature level fusion on the target data to generate a fusion feature vector; an underground pipeline recognition model based on deep learning is constructed to intelligently analyze and recognize the fusion feature vector, and a recognition result of the underground pipeline is obtained; and marking and displaying the identification result on an electronic map in a visual mode. According to the invention, by fusing data collected by various detection technologies and applying an intelligent analysis algorithm, the accuracy, reliability and efficiency of underground pipeline detection are improved, and the limitation problem of the existing detection technology is solved.

The invention discloses a multi-source data fusion rail train speed monitoring and early warning method, system and device, and relates to the related field of rail traffic safety monitoring, and the method comprises the steps: obtaining the line key parameters of a train test line, and constructing a train test line electronic map; matching a sensor array according to scene features of different operation sections; in the running process of the train, the real-time position and speed of the train are obtained through a real-time matching sensor, and multi-source sensor data are obtained; the ground dispatching center carries out fusion correction to obtain a corrected position and a corrected speed; performing prediction to obtain a predicted speed value and a position at the next moment; according to the train operation scene corresponding to the predicted position, scene speed limit parameters are extracted, and if the predicted speed value is not met, a train-ground cooperative early warning mechanism is triggered to conduct early warning. The technical problems that existing rail train speed monitoring and early warning are inaccurate in monitoring and not timely in early warning are solved, and the technical effect of improving the accuracy and timeliness of rail train speed monitoring and early warning is achieved.

The embodiment of the invention provides an underground engineering personnel composite positioning method and device, and relates to the technical field of indoor personnel space localization, and the method comprises the steps: deploying different types of positioning devices according to an underground engineering structure, and drawing an electronic map, the positioning device comprises a one-dimensional UWB positioning base station, a two-dimensional UWB positioning base station, a camera and an access control device; in a positioning period, acquiring positioning information of a person based on the positioning device; performing information fusion on the positioning information, and determining a positioning coordinate Pi of the person at the moment ti; and performing real-time positioning display and historical track display based on the positioning coordinates Pi of the personnel. On the basis of the UWB positioning technology, necessary access control and camera devices in underground engineering are fully utilized, and low-cost full-coverage real-time positioning of personnel in the underground engineering is realized.

The invention relates to an online supermarket unmanned warehouse intelligent sorting path optimization method based on multi-modal data, and belongs to the technical field of unmanned warehouse sorting, and the method comprises the following steps: S1, data real-time collection: deploying and installing sensing equipment in each area of a warehouse to collect commodity stock; s2, path calculation: constructing a dynamic electronic map, dividing a warehouse into grid units, and marking the state of each area with colors; an elastic priority path algorithm is executed, and paths are selected in different modes for conventional orders and urgent orders; s3, instruction issuing and execution: scheduling management is carried out, passing quantity and time limits are set at a main road intersection where the sorting robot passes, so that congestion at the main road intersection is avoided, and a one-way circulation mode is started in a peak period; and S4, abnormal problem processing, wherein different coping strategies are adopted according to faults of the single sorting robot, channel blockage and system faults.

A position point planning method, comprising: displaying an electronic map on a user interaction interface, the electronic map comprising a region to be operated for a movable platform (S101); synchronously displaying an auxiliary planning identifier on the electronic map along with a cursor, wherein the auxiliary planning identifier synchronously moves in response to the movement of the cursor, and the auxiliary planning identifier is used for providing a user with an indication of whether there is an abnormal factor that is not suitable for planning position points within a preset range with reference to the cursor (S102); and, after step S102 has been executed, in response to an input operation of the user, generating and marking a position point at the position currently indicated by the cursor (S103). The method can improve the rationality of position point planning.

The invention relates to the technical field of high-precision positioning, and discloses a high-precision Beidou multi-mode personnel positioning method and device, and the method comprises the steps: collecting the stability information of a Beidou navigation system and the operation state information of an inertial navigation system; according to the signal state of the Beidou navigation system, dynamically fusing the stability information of the Beidou navigation system and the operation state information of the inertial navigation system, and positioning a person to obtain a person positioning position; matching the personnel positioning position with a preset electronic map to obtain a personnel positioning result, and realizing high-precision personnel positioning; the Beidou positioning data and the inertial navigation data are combined, advantage complementation of the two positioning technologies is achieved, through automatic switching of the two positioning modes, positioning accuracy and continuity are ensured, complex and changeable environments are flexibly coped with, the positioning accuracy and reliability of the positioning system are improved, and high-precision personnel positioning is achieved.

The invention discloses a stereoscopic warehouse goods allocation intelligent binding system and method, and relates to the technical field of stereoscopic warehouse storage management. Comprising the following steps: S1, creating a two-dimensional electronic map of a warehouse, establishing a two-dimensional coordinate system of the warehouse, and based on the two-dimensional coordinate system and shelf positions, establishing coordinates of each shelf by taking a warehouse-out station position as a coordinate origin; s2, the RFID tag is installed at the preset position of the first layer of storage location of each goods shelf, and the coordinates of the goods shelf where the RFID tag is located are pre-stored in each RFID tag; by integrating the advanced navigation technology, the AI intelligent decision-making system and the multi-mode interaction unit, accurate and efficient binding of the goods locations of the stereoscopic warehouse is achieved. The system not only fully considers the three-dimensional space characteristics of the warehouse, but also combines the multi-dimensional factors such as dynamic heat and seasonal demand change of the goods, so that the goods allocation is more scientific and reasonable, and compared with the prior art, the system can dynamically adjust the goods allocation strategy according to the real-time demand.

The invention discloses a user guiding method and a user guiding system for a parking lot. The user guiding method comprises the following steps: at least determining a first target point corresponding to a variable target parking space according to an electronic map of the parking lot; obtaining an initial navigation map of an optimal path from the real-time position to the first target point according to the real-time position of a vehicle in the parking lot; converting the initial navigation map into a projection navigation map formed by a guide pattern, and projecting the projection navigation map on the ground for display through a vehicle lamp; and driving the vehicle to a final target parking space corresponding to the first target point according to the guidance of the projection navigation map. By executing the steps, the parking space navigation path can be dynamically adjusted according to the real-time occupation state of the parking space, and the parking space navigation path is dynamically and accurately projected and displayed by using the existing vehicle lamp in the parking space searching process of the user, so that the parking efficiency is improved, and meanwhile, the safety in the parking space searching process is also improved.

The invention provides a train autonomous positioning method and system in a satellite signal limited environment, and relates to the technical field of train positioning, and the method comprises the following steps: obtaining image data, laser point cloud data and inertial measurement data in a train driving process; constructing an IMU pre-integration residual error factor by using the inertial measurement data, constructing a laser radar inertial odometer residual error factor by using a local plane construction point-surface residual error in combination with the laser point cloud data, and constructing a key point residual error factor by using a key point position pre-stored in an electronic map in combination with the image data; combining the IMU pre-integration residual factor, the odometer residual factor and the key point residual factor to construct a train optimal state equation, and solving the train optimal state equation to obtain positioning data corresponding to the train; according to the invention, high-precision positioning of high-speed and long-distance railway train operation can be realized.

The invention discloses a water body apparent spectrum synchronous acquisition and water quality parameter inversion system based on an unmanned ship, and relates to the technical field of intelligent sensing, and the system comprises the following steps: acquiring environmental parameters of the unmanned ship, constructing a deep reinforcement learning model, inputting the environmental parameters, and outputting a phase control instruction; constructing a water quality parameter inversion model, inputting noise-free spectrum data, and outputting water quality parameters; when the water quality turbidity in the water quality parameters exceeds a dynamic turbidity sudden change threshold value, triggering a laboratory to collect water quality verification data, comparing the water quality verification data with the water quality parameters to output a turbidity error, and when the turbidity error exceeds an inversion verification error threshold value, updating the weight of the water quality parameter inversion model; and performing spatial interpolation calculation based on the updated water quality parameter inversion model, outputting water quality parameter distribution, and displaying a water quality parameter thermodynamic diagram and a traceability pollution path through an electronic map. According to the method, the PLSR weight is updated online through the incremental learning algorithm, and the model adaptation speed is increased.

Disclosed in the present invention is a traffic all-domain safety early warning system based on real-time safety information fusion technology, comprising a traffic all-domain big data cloud center, an onboard intelligent terminal OBU, an intelligent terminal having a client APP installed thereon, and a roadside unit RSU; the onboard intelligent terminal OBU is used for acquiring vehicle self-collected information serving as a first-layer information source; the roadside unit RSU is used for acquiring RSU information serving as a second-layer information source; the intelligent terminal having a client APP installed thereon is used for acquiring all-domain traffic information serving as a third-layer information source; and the traffic all-domain big data cloud center corrects the accuracy of dynamic traffic data comprising the vehicle self-collected information, an RSU information source and the all-domain traffic information, and fuses the corrected data into a unified traffic electronic map. The present invention ensures that all types of individuals entering the public traffic space can be detected in advance, thereby improving the information transparency and operation efficiency of the traffic system, and travel safety.

The invention discloses a train operation electronic map construction method and system based on meta learning, and the method comprises the steps: firstly synchronously collecting the geographic coordinate data of a train high-precision positioning device RTK and the kilometer post data of a train operation monitoring device LKJ, and building a fusion sequence of time-space alignment through time alignment and interpolation processing; electronic map construction is converted into a regression problem of'latitude and longitude backstepping kilometer post ', and a parameterized model is adopted to describe a nonlinear mapping relation between the two; introducing a deviation correction model to compensate RTK drift and kilometer post errors; through a meta-learning mechanism, general initial parameters are learned based on a model-independent meta-learning strategy in an offline stage, and a small number of samples are utilized to quickly adapt to a new line or dynamic deviation in an online stage; and finally fusing the correction data to generate and continuously update the electronic map. According to the method, the electronic map construction precision, the new line adaptation capability and the long-term stability are improved, and the high-precision positioning and real-time calibration requirements of rail transit are met.

The invention discloses a train control system, method, equipment and medium based on active sensing and autonomous localization, and the system comprises a multi-source autonomous sensing system which collects and outputs the information of the environment in front of a train by fusing the sensing data of a plurality of sensors; the vehicle-mounted standby system is in communication connection with the multi-source autonomous sensing system, accesses a pre-stored digital track map and is used for dynamically generating route topology and movement authorization and generating a train control instruction according to the train front environment information, the train real-time position and the line data of the digital track map; a dual-mode communication switching unit is arranged in the vehicle-mounted standby system and used for monitoring the communication state of the main train control system, and when the main train control system breaks down, the train control right is automatically switched to the standby system. Compared with the prior art, after the main train control system loses efficacy, the train can be made to be independent of a central control system and a fixed electronic map, the real-time state of a line is automatically adapted, and the safe driving instruction is generated.

The invention relates to the technical field of map making, in particular to a method and system for making a three-dimensional high-precision map containing road geometric elements, and the method comprises the steps: extracting original data from an original file through employing a user-defined analysis tool; preprocessing and checking the extracted original data to obtain core element data; and according to the core element data, generating a road three-dimensional model by adopting a space calculation model, and according to the core element data and a road design specification, performing derivative element calculation and generative three-dimensional element supplementation to form a three-dimensional lane-level road electronic map. According to the scheme, the three-dimensional high-precision map containing the road geometric elements can be manufactured, the map manufacturing efficiency is improved, the map precision is enhanced, and the cost is reduced.

The embodiment of the invention provides an end changing operation method and device of a train, and the method comprises the steps: determining an end changing direction of a target train in response to an end changing command for the target train, and determining a train operation section corresponding to the target train according to the end changing direction; first movement authorization corresponding to the target train is calculated according to the train operation section, and train route information is inquired according to the end changing direction; the route permission of the target train for the train route information is determined, the first movement authorization is updated according to the route permission, second movement authorization is obtained, and the target train runs in the end changing direction according to the second movement authorization. According to the method, the limitation condition that a turn-back area is formulated in an electronic map in advance is removed, and the movement authorization can be automatically calculated only by using the train operation section, so that the in-situ end changing use is more flexible, and the abnormal degradation mode and the influence on the subsequent normal operation of the train caused by coping with disaster emergency situations of the train are avoided.

The invention relates to the technical field of urban road traffic state analysis and processing based on the Internet of Things, and discloses an urban road traffic state analysis and processing method based on the Internet of Things. A complete analysis chain from sensor data acquisition, error calibration and clock synchronization, road section length extraction by a high-precision electronic map, vehicle density calculation, graph structure modeling, distance matrix generation, attenuation parameter calculation, spectrum matrix construction and characteristic value solving, density prediction, anomaly detection, signal lamp adjustment and path optimization pushing is constructed. Through graph topology modeling and graph calculation, urban traffic is abstracted into a graph model with spatial characteristics and structure association, and the traffic density diffusion modeling and analysis capability is remarkably improved. A power iteration and residual error detection strategy is adopted to replace an empirical rule, so that a self-adaptive anomaly detection and signal regulation and control mechanism is realized, and the real-time performance and the intelligence of the system are enhanced.

The invention relates to the technical field of orchard disease and insect pest early warning and prevention resource management, in particular to an orchard disease and insect pest early warning and prevention resource management decision support method based on multi-source data, and the method comprises the steps: firstly obtaining orchard multi-source data, and constructing a space-time fusion data set with a geographic grid as a unit through space-time alignment and standardization processing; inputting the data set into a machine learning multi-classification model, and outputting a risk quantification index of a future specific pest and disease damage; triggering a prevention and treatment decision engine based on an index, and combining a resource knowledge base to generate an optimal prevention and treatment prescription through multi-objective optimization; then, matching prevention and control resource real-time inventory with agricultural machinery space positions, and generating a resource scheduling scheme and agricultural machinery operation path planning; and finally, the integrated information is visualized on an electronic map, a control instruction is issued, and feedback is received to form closed-loop management. The method improves the accuracy of disease and pest early warning, achieves the optimal prevention and control scheme, improves the utilization efficiency of resources and agricultural machinery, and provides support for scientific management of orchard diseases and pests.