55 results about "Pollution dispersion" patented technology

The invention discloses a plot pollution monitoring, predicting and early warning system and method, and relates to the technical field of environment monitoring and pollution early warning, and the method comprises the steps: obtaining multi-source data of a target plot; performing preprocessing, feature extraction and fusion on the multi-source data; inputting the multi-source data into the dynamic pollution diffusion model to obtain a pollutant concentration field of the target plot; jointly inputting the fusion data and the pollutant concentration field into a land parcel pollutant concentration prediction model for prediction to obtain a pollutant concentration prediction value of the target land parcel in a future target time period; comparing the pollutant concentration predicted value of the target land parcel in the future target time period with the early warning threshold values of all levels, and generating an early warning instruction of the corresponding level according to a comparison result; generating corresponding early warning information according to the early warning instruction; and executing corresponding early warning measures according to the early warning information. According to the invention, through multi-dimensional data integration and model optimization, scientific assessment and hierarchical management and control of pollution risks can be realized.

The invention relates to the field of underground water pollution monitoring, in particular to a dynamic intelligent monitoring method and system for underground water pollution. The method comprises the following steps: constructing and updating an underground water solute transport model; generating a comprehensive pollution feature vector by using the obtained multi-source data which is related to the groundwater pollution and comprises a plurality of pollution indexes; respectively constructing a pollution source positioning model and a pollution diffusion model; triggering a pollution alarm according to the comprehensive pollution feature vector; according to the multi-source data and the current hydrogeological data, utilizing the pollution source positioning model to obtain a pollution source position; respectively utilizing the pollution diffusion model and the groundwater solute transport model to carry out prediction simulation to obtain first pollution distribution changing along with time and second pollution distribution changing along with time; and carrying out weighted fusion on the first pollution distribution and the second pollution distribution to generate predicted pollution distribution changing along with time. The problem that underground water pollution monitoring is not timely and accurate enough in the prior art is solved.

The invention discloses an unmanned aerial vehicle inspection system for environmental state monitoring, which relates to the technical field of unmanned aerial vehicle control and comprises a pollutant monitoring data acquisition module, a pollutant monitoring data analysis module, a pollution diffusion point judgment module, a pollution diffusion trend line acquisition module, an inspection point coordinate acquisition module and an inspection route acquisition module. By generating an optimal or suboptimal inspection route, the unmanned aerial vehicle can efficiently pass through the predicted inspection points in sequence, accurate tracking and monitoring of the predicted pollution diffusion route are achieved, it is ensured that the unmanned aerial vehicle can be located at the front edge or a key area of pollution diffusion all the time, and by sequencing the prediction points and planning the route, the unmanned aerial vehicle can be accurately tracked and monitored. According to the invention, an efficient inspection route can be generated, unnecessary detour can be reduced, the unmanned aerial vehicle can adapt to the change of a pollution diffusion path in real time, the effectiveness and timeliness of monitoring can be ensured, and the inspection route can be rapidly adjusted and the pollution diffusion area can be emphatically monitored in an emergency pollution event of the unmanned aerial vehicle.

The invention provides an unmanned aerial vehicle intelligent positioning cleaning method and system for photovoltaic pollution, and relates to the technical field of photovoltaic array cleaning maintenance, and the method comprises the steps: firstly obtaining a pollution related image set, flight parameters and power generation efficiency related data collected when an unmanned aerial vehicle flies over a photovoltaic array; pollution area positioning processing is carried out based on the data, and space positioning information is generated; planning a pollution cleaning path in combination with the spatial positioning information, the pollution diffusion trend data and the power generation priority data; controlling an unmanned aerial vehicle carried cleaning device to execute cleaning operation according to the path, and synchronously acquiring a real-time pollution change image and power generation efficiency change data to generate an operation result; and finally, carrying out cleaning effect evaluation based on an operation result and related data, generating pollution cleaning evaluation information containing supplementary cleaning suggestions, and realizing intelligentization and high efficiency of photovoltaic array cleaning.

The invention provides a multi-source data fused water quality pollution monitoring method and device and a storage medium, and relates to the technical field of water quality monitoring. According to the method, through the key steps of data preprocessing, cross-modal feature fusion, pollution concentration estimation, graph neural network traceability and the like, multi-source water quality data and monitoring point space topology information are deeply integrated, and a whole-process automatic monitoring system is constructed. According to the method, end-to-end processing from data standardization to pollution emission source positioning is realized, a multi-source heterogeneous data barrier is effectively broken, the complementary value and the time-space association rule of different modal data are fully mined, the integrity, accuracy and efficiency of water quality pollution monitoring are improved, the emission source position and the pollution diffusion path can be accurately positioned, and the water quality pollution monitoring efficiency is improved. Full-link and targeted technical support is provided for water quality pollution control and treatment decision, and the problems that traditional monitoring data is low in utilization rate and insufficient in traceability accuracy are solved.

The application relates to the technical field of water quality detection, and discloses a water quality detection stability control feature extraction method, which comprises the following steps: collecting water area data to construct a regional water system network model; performing node importance analysis on the constructed regional water system network model to obtain a key node set; collecting sample data at the key node positions; if pollution components are detected in the sample data, then combining a water pollution diffusion model to perform reverse deduction on the pollution positions, and collecting stable sample data at the pollution positions to perform water quality detection. The water system node with higher importance is selected as the key node, sample data is collected in the key node, water system pollutant missing detection is avoided, according to the concentration change trend of the pollutant components in the sample data, the water pollution diffusion model is used to calculate the probability density function of different pollution positions and pollution intensities, the pollution positions are determined, sample data is collected, and sample data with higher stability is obtained.

The application discloses a kind of based on Ray distributed environment sudden pollution emergency decision support system and working method, belong to environmental emergency management technical field.The environmental sudden pollution emergency decision support system based on distributed architecture includes infrastructure module, distributed computing module, data processing module, model service module and application service module.System bottom layer uses Ray distributed computing framework, combines pollution diffusion simulation, multi-source data fusion and real-time computing analysis, realizes the rapid assessment and dynamic response to sudden environmental pollution event.The application can solve the problem of the limitations of traditional emergency decision support system in computing performance, response time and expansibility.Through modular design, cover pollution source tracking, diffusion path prediction, emergency scheme optimization and resource scheduling management and other functions, support multi-scenario application.

The invention relates to the technical field of computer modeling, and provides a pollution diffusion path modeling method and system based on multiple sensors, which are used for improving the accuracy and adaptability of pollution diffusion path modeling. The method comprises the following steps: synchronously acquiring original observation data through a multi-source sensor deployed in a pollution monitoring area, and establishing a data association index based on a spatial arrangement position and a data acquisition timestamp of the multi-source sensor; extracting spatio-temporal characteristics representing gas migration in combination with the data association index and the physical diffusion characteristics of the pollution gas; establishing a basic model structure of a gas migration model based on spatial-temporal characteristics, analyzing and determining a correlation weight in combination with characteristic responsivity, and generating a parameter self-learning strategy; starting a parameter self-learning strategy, and iteratively updating the parameters by using a particle swarm search space to obtain optimized parameters; and importing the optimized parameters into a gas migration model for inversion calculation, determining initial distribution of path nodes in combination with topographic features and meteorological conditions, performing iterative updating, and outputting a pollution diffusion inversion path.

The invention provides an ecological environment monitoring system and method, and the method comprises the steps: building a three-dimensional digital twinborn model of a designated city in a target region, and enabling the three-dimensional digital twinborn model to comprise thermal environment dynamic data of different environment nodes; determining spatial structure characteristics of different environment nodes, and constructing a spatial communication relationship through the spatial structure characteristics; determining diffusion intensity indexes of each environment node in different thermal diffusion ranges, and further determining the heat island effect intensity of each environment node by combining all the diffusion intensity indexes with the spatial communication relationship; based on the heat island effect intensity, evaluating the influence of the heat island effect intensity on a pollution diffusion field, and obtaining the heat influence pollution diffusion risk of each environment node in different heat diffusion ranges; and generating a multi-scale thermal pollution report of the target area through all the thermal influence pollution diffusion risks. By adopting the scheme of the invention, multi-scale monitoring can be carried out on urban thermal pollution based on a space-time cooperation mechanism of digital twinning.

The invention relates to a mobile air purifier control method, system, equipment and medium, and relates to the technical field of air purification, the method comprises the following steps: according to the scene information of the space, obtaining the distribution position of each key article in the space and the diffusion range of the corresponding pollution gas in the space in real time, and dividing the space into a plurality of subspaces; based on the gas sensing data of each subspace, generating a dynamic three-dimensional pollution thermodynamic diagram of the space; and calling a purification strategy executed by the purifier according to the pollution thermodynamic diagram of the space, the user behavior mode and the crowd distribution information. According to the method, air purification is carried out according to the object pollution diffusion mode of the space where the purifier is located and the activity behavior of the user, and the dynamic response accuracy and scene self-adaption collaboration of operation of the air purifier are improved and adjusted.

The invention discloses a casting workshop waste gas efficient purification treatment system, which comprises the following modules: a pollution state sensing module, which is used for constructing a pollution state map; the pollution diffusion prediction module is used for inputting the pollution state atlas into a three-dimensional space time prediction network constructed based on a light cone convolution structure to generate a pollution diffusion prediction atlas; the pollution residue mapping module is used for generating a pollution repayment map; the strategy parameter generation module is used for inputting the pollution diffusion prediction atlas and the pollution repayment atlas into the purification scheduling model to generate a purification strategy parameter set; the response inertia modeling module is used for constructing a response inertia curve; the start-stop time sequence correction module is used for correcting the start-stop time sequence based on the response inertia curve; and the equipment control module is used for generating an equipment control instruction and controlling the operation of the corresponding purification equipment. By combining the three-dimensional space time prediction network, the purification scheduling model and response compensation, efficient purification treatment of the waste gas of the casting workshop is realized.

The application discloses a land pollution monitoring, predicting and early warning system and method, relates to the technical field of environmental monitoring and pollution early warning, and comprises the following steps: acquiring multi-source data of a target land; pre-processing, feature extraction and fusion of the multi-source data; inputting the multi-source data into a dynamic pollution diffusion model to obtain a pollutant concentration field of the target land; inputting the fused data and the pollutant concentration field into a land pollutant concentration prediction model for prediction to obtain a pollutant concentration prediction value of the target land in a future target time period; comparing the pollutant concentration prediction value of the target land in the future target time period with early warning threshold values of different levels, and generating early warning instructions of corresponding levels according to a comparison result; generating corresponding early warning information according to the early warning instructions; and executing corresponding early warning measures according to the early warning information; and the application can realize scientific evaluation and hierarchical control of pollution risks through multi-dimensional data integration and model optimization.

The application discloses a water environment pollution monitoring system based on data analysis and belongs to the technical field of environment monitoring and data analysis. The system comprises the following modules: a spectrum collection module, which collects multi-band water body optical signals in real time through a distributed spectrum sensing node array to form a primary monitoring data set; a phase space reconstruction module, which reconstructs the phase space of time series spectrum signals by using a chaotic mapping theory to generate a high-dimensional attractor trajectory matrix representing the pollution diffusion state; a fractal feature extraction module, which extracts a singularity index sequence reflecting the pollution source intensity change from the high-dimensional attractor trajectory matrix by using an adaptive fractal dimension calculation method; and a pollution identification module, which dynamically identifies a pollution event triggering threshold and outputs a pollution source positioning and diffusion path prediction result based on the correlation integral analysis of the singularity index sequence and a historical pollution sample database.

This invention relates to the field of environmental science and technology, and discloses a simulation system for atmospheric pollution diffusion, including a data acquisition module, a data preprocessing module, a dynamic simulation model module, a simulation calculation module, a visualization module, and a decision support module. The data acquisition module collects data from multiple sources; the data preprocessing module cleans, fuses, and optimizes the collected data; the dynamic simulation model module employs a dynamic hybrid diffusion model and combines deep learning to optimize model parameters; the simulation calculation module performs efficient simulation of pollutant diffusion; the visualization module dynamically displays the pollutant concentration distribution and diffusion path in three dimensions; and the decision support module generates pollution control suggestions and risk warning information based on the simulation results. In this invention, by introducing a dynamic hybrid diffusion model, intelligent switching between Gaussian plume models and CFD models is achieved, enabling adaptation to various scenarios ranging from simple to complex terrains.

The invention belongs to the technical field of flue gas monitoring, and provides a multipoint patrolling method, system and device. The method comprises the following steps of adaptive sampling and preprocessing, distributed full-dimensional self-diagnosis and fault early warning, fault root cause mining and processing, LIBS spectral analysis and 4D pollution diffusion model construction, environment-data dual-drive dynamic calibration mechanism and data fusion and collaborative analysis. According to the method, LIBS spectral analysis and a CFD model are coupled to construct a 4D pollution diffusion model, and an environment-data dual-drive dynamic calibration mechanism is combined, so that accurate simulation and prediction of a pollution diffusion rule are realized; through space fusion and time trend prediction, a scientific basis is provided for pollution source responsibility division and emission reduction decision, adaptive sampling, multi-modal fault diagnosis and dynamic pollution modeling are integrated, closed-loop and environment-data dual-drive dynamic calibration from data acquisition to decision support is achieved, limitation of a traditional static model is broken through, multi-dimensional collaborative decision support is achieved, and the method is suitable for large-scale popularization and application. And a landing emission reduction scheme is provided.

The invention relates to a spatial-attribute heterogeneous feature-based drainage basin pollution traceability hierarchical network construction method and system, and belongs to the technical field of environmental science and computer crossing. According to the method, heterogeneous environmental factors such as population, GDP, rainfall, land utilization and water quality are divided into a plurality of layers through combination of attribute correlation analysis and spatial layering modeling, an intra-layer connection relation under spatial adjacency and attribute driving is constructed, an inter-layer interaction rule is designed, a three-dimensional heterogeneous layering graph is formed, and the three-dimensional heterogeneous layering graph is constructed. Therefore, the subsequent high-fidelity modeling of the pollution diffusion path and the accurate quantification of the traceability contribution rate are realized. The method not only can accurately capture a space path and key influence factors of pollution diffusion, but also can realize upstream backtracking identification of downstream pollution points and pollution contribution rate estimation of non-monitoring areas, has the advantages of high adaptability and universality and the like, is suitable for pollutant traceability modeling and environment decision support of multiple types of drainage basins, and has wide application prospects. And the method has good engineering popularization and practical application values.

The invention provides a pollution diffusion prediction method and device based on gamma radioactivity and a wind field, and relates to the technical field of pollutant monitoring, and the method comprises the steps: carrying out the feature peak extraction, nuclide recognition and concentration calculation of a gamma radioactivity energy spectrum data set, and obtaining a nuclide concentration set; constructing a three-dimensional wind field diffusion field through the topographic data and the wind field data set; performing coupling calculation and correlation matching on the nuclide concentration set and the three-dimensional wind field diffusion field through a Gaussian diffusion model, and constructing a correlation matrix of the nuclide concentration and the wind field; obtaining a nuclide half-life period, a gamma-ray emissivity and a terrain, and performing weighted fusion on elements in the incidence matrix through the nuclide half-life period and the gamma-ray emissivity to obtain a fusion coefficient; correcting the fusion coefficient through the terrain to obtain a diffusion trend coefficient set; and constructing a radioactive pollution prediction model, and according to the diffusion trend coefficient set, performing diffusion prediction in a future time period through the radioactive pollution prediction model to obtain a pollution diffusion prediction result.

The application relates to the technical field of environmental monitoring and discloses a water ecological pollution diffusion prediction method and system based on big data, which comprises the following steps: a sensing network of a water body environment is constructed, real-time water body environment data are acquired, the data are preprocessed by using an edge computing node, and then the data are synchronously transmitted to a central platform; a dynamic prediction model of pollutant boundary condition parameters is established based on historical data and the real-time water body environment data; a pollutant propagation graph is constructed according to the dynamic boundary condition parameters, the spatiotemporal distribution trend of pollutant concentration is analyzed, and the position of a pollution source is identified; according to the pollution source position identification result, a time-effect prediction is performed, and a pollution early warning response is triggered in combination with a set threshold value. The spatial coverage and timeliness of pollution monitoring are improved, the intelligence and credibility of pollution tracking are enhanced, and the intelligence and scientific level of water ecological environment pollution prevention and control are improved.

The application discloses a mine underground water pollution multi-element sensing and intelligent early warning method and system, and the method comprises the following steps: constructing a mine underground water pollution full-element sensing network, collecting pollution source, hydrogeology, underground water dynamic monitoring and environmental correlation data, and storing the standardized data into a unified database. The pollution source, monitoring well and hydrogeology zoning data vector layers are superimposed to generate a pollution risk distribution base containing the correlation of "pollution source-aquifer-monitoring point". A migration model coupling pollution dissolution and seepage is established to quantize the influence weight of elements on pollution diffusion. The pollution concentration time sequence is extracted, and the real-time data sliding window is combined to output the pollution diffusion path, concentration peak value and sensitive target time to arrival by using LSTM. Based on the risk base and the prediction result, the sensitive target grading is combined to form a research conclusion, and the key prevention and control areas and key nodes are determined. The application provides a scientific basis for mine pollution prevention and control.

The invention belongs to the technical field of numerical control machine tools, and particularly relates to a multi-tool-position antifouling semicircular tool magazine which comprises a cabin, a servo motor, a transmission shaft and a tool disc, the tool disc is fixedly connected to the middle of the transmission shaft, the transmission shaft and the tool disc are both located in the cabin, the servo motor is fixedly connected to the upper portion of the cabin, and the servo motor is fixedly connected to the lower portion of the cabin. The transmission shaft is in transmission connection with the output end of the servo motor, cutter position frames distributed at equal intervals are fixedly connected to the side edge of the cutter disc, and cutter sleeves are fixedly connected into the cutter position frames. By arranging the high-pressure fan, the convex gasket, the guide wheel, the reset spring and the pressure switch, automatic cleaning of the cutter is achieved, accumulation of cutting fluid and metal scraps is reduced, high-pressure airflow provided by the high-pressure fan is directionally jetted, pollution diffusion is avoided, the service life of the cutter is prolonged, and the machining precision of the cutter is improved; the mechanical linkage design of the convex gasket, the guide wheel, the reset spring and the pressure switch simplifies the control logic, ensures that the high-pressure fan is accurately and timely started and stopped, and reduces the energy consumption.

The invention discloses a traffic environment coordination control method and device based on a mixed space-time diagram neural network. The method comprises the following steps: constructing a mixed space-time diagram neural network model consisting of a discrete wavelet transform module, a dual-channel learning module, a space-time mixed diagram module and a prediction module; training the mixed space-time diagram neural network model; and predicting the traffic flow time and space based on the trained mixed time-space diagram neural network model, and dynamically identifying and predicting the pollution diffusion trend of the urban area in combination with the pollutant emission of the vehicle. The device comprises a processor and a memory. By fusing the traffic data and the environmental data (such as pollution concentration and meteorological information), the prediction precision is improved, the real-time pollution emission reduction strategy is generated, and collaborative application of an intelligent traffic system and environmental sustainable management is supported.

The application discloses a kind of based on multi-source data fusion's bottom mud pollution analysis dynamic distribution optimization method and system, comprising: constructing pollution diffusion space-time coupling model, generates pollution heat map and uncertainty field;Through the multi-objective optimization of improved NSGA-III algorithm, dynamically adjust sampling point density;Combining reinforcement learning framework generates dynamic sampling sequence, constructs action space, reward function, and through bayesian decision tree real-time updates the optimal scheme of sampling point arrangement;Real-time planning sampling path, according to the feedback of field sampling data update pollution diffusion space-time coupling model and re-plan sampling path.The application realizes the high-precision prediction of pollution space-time distribution, improves the pollution hotspot identification rate, reduces redundant sampling, and adapts to complex environment.

This invention discloses an ecological damage assessment system based on pollution diffusion simulation, relating to the technical field of marine ecological security. The system includes: an oil spill sensing monitoring network with multiple buoy probes deployed on the water surface, centered on the berth of a wharf; each buoy probe has a built-in communication device that wirelessly transmits the collected information to a data analysis module; the data analysis module constructs a computational grid based on the oil spill sensing monitoring network and maps each buoy probe to a grid node, obtaining the continuous spatial field of the entire area using Kriging interpolation; the data analysis module constructs a pollution diffusion equation and solves for the pollution concentration field; the data analysis module defines the real-time ecological damage rate and the cumulative ecological damage amount and continuously sends them to an early warning module; the early warning module triggers a prevention and control mechanism based on a comparison of these two values ​​with a preset threshold.

The invention relates to the technical field of data analysis, in particular to a pollution data analysis method and system based on deep learning, and the method comprises the steps: obtaining a historical pollution data set, determining the coordinates of a pollution source through a pollution concentration value, and building a pollution diffusion model through a convolutional neural network. A target water area is divided into grid units, unmanned aerial vehicle cruise schemes carrying a hyperspectral camera are generated, and each scheme comprises the cruise state, the cruise height value and the pollution concentration prediction value of the grid units. And optimizing the unmanned aerial vehicle circulation path sequence through a genetic algorithm, smoothing the cruise path sequence, and adjusting the cruise height according to the pollution concentration gradient. According to the invention, through the hyperspectral camera, the spectral resolution effect is improved and the data processing amount is reduced under different types and concentrations of polluted water, and the cruise height of the unmanned aerial vehicle is adjusted.

This invention discloses an indoor pollutant diffusion analysis method based on CFD simulation. The invention relates to the field of pollution diffusion analysis technology and includes the following steps: setting up a real-time monitoring unit to collect indoor environmental data to be monitored and inputting it into a CFD model; setting boundary conditions; constructing a background flow field including velocity, pressure, and temperature fields through iterative calculations; dividing an initial grid according to the indoor spatial layout; constructing a pollutant diffusion equation based on the background flow field; obtaining estimated pollutant concentration values ​​for a historical reference time period; outputting actual concentration values ​​through a pollutant concentration detection unit; determining whether to split or merge the grid based on the difference between the estimated and actual concentrations and the concentration gradient; correcting the parameters of the pollutant diffusion equation using the updated actual concentration values ​​of the grid to obtain an accurate diffusion equation for real-time monitoring of pollutant diffusion, while significantly improving the accuracy of the model.

The present application relates to the technical field of environmental monitoring, and more particularly to a soil multi-element online monitoring method and system based on a wireless sensor network. The method periodically collects soil pollutant concentration data by deploying a sensor network and constructs a spatio-temporal data cube. The method identifies a pollution diffusion active area and calculates the pollutant input direction of each point to generate a direction field distribution map. Based on the direction field, the method reversely traces from a high concentration point to locate a pollution source point and draw a pollution diffusion path. The present application realizes real-time, multi-point synchronous monitoring of soil pollution conditions and can automatically and accurately trace the location of a pollution source and a diffusion path, thereby improving the efficiency and accuracy of pollution source analysis.

The invention relates to the technical field of automatic control, in particular to an intelligent ventilation cabinet and a control system thereof, and the system comprises a pollution trend identification module, a trend deviation judgment module, a pre-control response setting module, a risk weight rearrangement module and a linkage trigger mechanism module. According to the invention, through correlation analysis and abrupt change feature extraction of pollution monitoring point concentration data, accurate tracking of a pollution diffusion trend and dynamic positioning of a boundary space position are realized, angle conversion is completed by combining a space proportion of a boundary and an air valve, and a driving signal is generated. The opening degree of the air valve can be adjusted in real time according to the pollution diffusion speed and the air speed change, meanwhile, efficient distribution of ventilation resources is achieved by combining priority dynamic rearrangement, a control signal is automatically triggered at a key node, and air valve state switching is completed. The pollution change identification precision, the space control sensitivity, the linkage response coordination and the ventilation efficiency are effectively improved, and the risks of uneven resource distribution, air exchange delay and local environment imbalance are reduced.

The invention discloses an environmental pollution monitoring method and system based on big data processing, and relates to the technical field of big data processing, and the method comprises the steps: building a cross-scale pollution diffusion and crowd exposure prediction model according to an initial field of pollution distribution and a social behavior parameter matrix, obtaining a pollutant concentration distribution grid through rolling prediction, and carrying out the prediction of the pollution distribution. Calculating the crowd exposure amount, and generating an exposure risk hot area map; and establishing a scene library of strategy intervention simulation by using the pollutant concentration distribution grid and the exposure risk hot area map, calculating the change trend of future pollution levels and the change trend of crowd exposure risks under different strategies, and obtaining a pollution reduction curve and an exposure reduction amount of each strategy scene. According to the invention, a complete link from multi-source data acquisition to optimal governance decision making is formed on the whole, and the precision of environmental pollution monitoring and the practicability of governance decision making are improved.

The invention relates to the technical field of pollution diffusion prediction, in particular to a soil pollution diffusion prediction method and system, and the method comprises the steps: obtaining the monitoring data of each monitoring point in a plurality of monitoring points in a target region; determining a plurality of pollution expansion routes based on the pollutant concentration of each monitoring point; determining the pollution influence weight of each pollution expansion route based on the monitoring data of the monitoring points at the two ends of each pollution expansion route; and based on the pollution influence weights of the plurality of pollution expansion routes, a diffusion coefficient in the soil pollution diffusion prediction model is corrected so as to be used for soil pollution diffusion prediction of the target area. The method can improve the prediction accuracy and reliability of the soil pollution diffusion prediction model for the target area.

The invention discloses a dynamic optimization method and system for urban air pollution monitoring, relates to the technical field of environment monitoring and intelligent control, and discloses a dynamic optimization method and system for urban air pollution monitoring. A deep reinforcement learning model is utilized to generate a scheduling strategy in real time and optimize position distribution of monitoring units, and meanwhile, multi-source data is fused to generate a pollution map, so that the problems of limited coverage range, response lag and untimely model updating of a traditional monitoring method are effectively solved; monitoring resource distribution can be dynamically adjusted, a pollution diffusion model is updated in real time, intelligent fusion of monitoring data is achieved, and therefore the coverage range, the response speed and the precision of pollution monitoring are improved.