Soil ecological restoration method and system for coal mining subsidence area

Abstract

The invention provides a soil ecological restoration method and system for a coal mining subsidence area, and relates to the field of soil remediation, and the method comprises the steps: segmenting the coal mining subsidence area according to topographic features, and obtaining a plurality of subsidence areas; carrying out migration and diffusion analysis on the carrier material according to topographic information in combination with rainfall conditions, and carrying out primary compensation on the initial repair parameters according to diffusion analysis results; according to the soil humidity, activity fluctuation analysis is conducted on the functional microorganisms, secondary compensation is conducted according to fluctuation analysis results, a plurality of optimized remediation parameters are obtained, and soil remediation of the subsidence areas is executed. The method aims at solving the technical problems that migration and diffusion of microorganisms and changes of activity of the microorganisms in the soil remediation process are not fully considered in a traditional microorganism remediation method, and consequently the soil remediation accuracy and stability are insufficient. The accuracy and reliability of microbial remediation parameter setting can be remarkably improved, and the effects of effectively degrading pollutants and restoring soil fertility are achieved.

Description

Technical Field

[0001] The present invention relates to the field of soil remediation, and in particular to a soil ecological remediation method and system for coal mining subsidence areas. Background Art

[0002] In recent years, microbial-based soil remediation technology has been widely used in the remediation of various contaminated soils, especially in the degradation of organic pollutants, heavy metal pollutants, etc., showing good prospects. Microbial remediation uses specific microbial strains to degrade pollutants in the soil. It is a relatively environmentally friendly and low-cost remediation method.

[0003] However, traditional microbial remediation methods still have certain limitations. First, microorganisms in the soil may undergo uneven migration and diffusion during the remediation process, resulting in excessively high microbial concentrations in some areas and excessively low microbial concentrations in other areas. This uneven distribution makes the remediation effect unstable, especially in subsidence areas with complex terrain features. Second, factors such as humidity in the soil environment will directly affect the activity of microorganisms. Traditional methods often ignore the influence of these dynamic factors, causing large fluctuations in the degradation efficiency of microorganisms, which in turn affects the remediation effect. Summary of the Invention

[0004] The purpose of the present invention is to provide a soil ecological restoration method and system for coal mining subsidence areas to address the technical problem that traditional microbial remediation methods fail to fully consider the migration and diffusion of microorganisms and changes in microbial activity during the soil remediation process, resulting in insufficient accuracy and stability of soil remediation. The system includes: In a first aspect, the present invention provides a soil ecological restoration method for a coal mining subsidence area, comprising: detecting and obtaining the pollutant type and concentration of the coal mining subsidence area, matching functional microorganisms and carrier materials using a microbial remediation database, and constructing initial microbial remediation parameters; segmenting the coal mining subsidence area according to terrain characteristics to obtain a plurality of subsidence areas; performing migration and diffusion analysis on the carrier materials based on the terrain information of the plurality of subsidence areas and combined with rainfall conditions, and performing a primary compensation on the initial microbial remediation parameters based on the diffusion analysis results to obtain a plurality of compensated remediation parameters; performing an activity fluctuation analysis on the functional microorganisms based on the soil moisture of the plurality of subsidence areas, and performing a secondary compensation on the plurality of compensated remediation parameters based on the fluctuation analysis results to obtain a plurality of optimized remediation parameters; and performing soil ecological restoration on the plurality of subsidence areas according to the plurality of optimized remediation parameters.

[0005] Preferably, the soil ecological restoration method for coal mining subsidence areas also includes: detecting and obtaining the soil acid-base characteristics of the coal mining subsidence area; using a microbial remediation database to perform functional microbial matching based on the soil acid-base characteristics, pollutant types and pollutant concentrations, and determine several microbial types and several microbial concentrations; performing carrier material matching based on the several microbial types and several microbial concentrations, and determining multiple carrier material types and multiple carrier material concentrations; and constructing initial microbial remediation parameters based on the several microbial types, several microbial concentrations, multiple carrier material types and multiple carrier material concentrations.

[0006] Preferably, the soil ecological restoration method for a coal mining subsidence area also includes: in a simulation space, starting from the lowest point of the coal mining subsidence area, simulating water irrigation to the coal mining subsidence area, and calculating the height difference and slope difference between the current position and the lowest point; if the height difference is greater than a preset height threshold or the slope difference is greater than a preset slope threshold, setting a dividing line at the current position, and starting from the current position, continuing to simulate water irrigation to the coal mining subsidence area until reaching the highest point of the coal mining subsidence area, harvesting multiple dividing lines, dividing the coal mining subsidence area according to the multiple dividing lines, and obtaining several subsidence areas, wherein each subsidence area is marked with a regional slope and regional height.

[0007] Preferably, the soil ecological restoration method for a coal mining subsidence area also includes: obtaining the average annual rainfall and the average annual rainfall intensity of the coal mining subsidence area within a preset historical time range, setting them as rainfall conditions; randomly selecting a first subsidence area from the several subsidence areas, and obtaining the first area slope and the first area height of the first subsidence area; randomly selecting a first carrier material type from multiple carrier material types; performing migration and diffusion analysis on the first carrier material type based on the average annual rainfall, the average annual rainfall intensity, the first area slope and the first area height, and outputting a first diffusion ratio; sequentially analyzing and obtaining multiple diffusion ratios of multiple carrier material types in the first subsidence area, compensating the microbial concentration and carrier material concentration in the initial microbial remediation parameters according to the multiple diffusion ratios, outputting a first compensation remediation parameter, and adding it to the several compensation remediation parameters.

[0008] Preferably, the soil ecological restoration method for coal mining subsidence areas also includes: using the first carrier material type as a retrieval condition, based on the historical microbial restoration records of coal mining subsidence areas, collecting a sample annual average rainfall set, a sample annual average rainfall intensity set, a sample area slope set and a sample area height set, and obtaining the annual diffusion ratio of the first carrier material type under different sample annual average rainfall, sample annual average rainfall intensity, sample area slope and sample area height, and constructing a sample diffusion ratio set, wherein the annual diffusion ratio is a positive or negative value; using the sample annual average rainfall set, sample annual average rainfall intensity set, sample area slope set and sample area height set as input, and using the sample diffusion ratio set as supervision, training the BP neural network until the model converges to obtain a material diffusion analyzer; using the material diffusion analyzer, performing migration and diffusion analysis based on the annual average rainfall, annual average rainfall intensity, first area slope and first area height, and outputting a first diffusion ratio.

[0009] Preferably, the soil ecological restoration method for coal mining subsidence areas also includes: subtracting the multiple diffusion ratios from 1 to obtain multiple primary compensation coefficients; multiplying the multiple primary compensation coefficients by the carrier material concentration of the corresponding carrier material type in the initial microbial remediation parameters, and the corresponding microbial concentration of the corresponding carrier material type, to output a first compensation remediation parameter.

[0010] Preferably, the soil ecological restoration method for coal mining subsidence areas also includes: randomly selecting a first subsidence area, obtaining the first-year average soil moisture value of the first subsidence area, and a first compensation restoration parameter; randomly selecting a first microbial type from several microbial types; predicting and obtaining the first reproduction rate of the first microbial type based on the first-year average soil moisture value, wherein a first activity fluctuation analyzer is constructed based on a BP neural network to perform reproduction rate prediction; setting the ratio of the first expected reproduction rate of the first microbial type to the first reproduction rate as a quadratic compensation coefficient, and analyzing and obtaining several quadratic compensation coefficients in turn, wherein the first expected reproduction rate is the reproduction rate of the first microbial type under standard soil moisture; according to the several quadratic compensation coefficients, multiplying the corresponding microbial concentration in the first compensation restoration parameter and the corresponding carrier material concentration of the corresponding microbial concentration respectively to obtain a first optimized restoration parameter, and adding it to the several optimized restoration parameters.

[0011] In a second aspect, the present invention also provides a soil ecological restoration system for coal mining subsidence areas, which is used to execute a soil ecological restoration method for coal mining subsidence areas as described in the first aspect, including: an initial restoration parameter construction module, which is used to detect and obtain the pollutant type and pollutant concentration in the coal mining subsidence area, use the microbial restoration database to match functional microorganisms and carrier materials, and construct initial microbial restoration parameters; a coal mining subsidence area segmentation module, which is used to segment the coal mining subsidence area according to terrain characteristics to obtain several subsidence areas; a migration and diffusion analysis module, which is used to perform migration and diffusion analysis on the carrier materials according to the terrain information of the several subsidence areas and combined with rainfall conditions, and compensate the initial microbial restoration parameters once according to the diffusion analysis results to obtain several compensated restoration parameters; an activity fluctuation analysis module, which is used to perform activity fluctuation analysis on the functional microorganisms according to the soil moisture of the several subsidence areas, and perform secondary compensation on the several compensated restoration parameters according to the fluctuation analysis results to obtain several optimized restoration parameters; a soil ecological restoration module, which is used to perform soil ecological restoration of the several subsidence areas according to the several optimized restoration parameters.

[0012] In a third aspect, the present invention further provides an electronic device, comprising: At least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so as to enable the at least one processor to perform the steps of any one of the methods described in the first aspect above.

[0013] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed, the steps of the method described in any one of the first aspects are implemented.

[0014] The embodiments of the present invention include the following advantages: By detecting and obtaining the pollutant type and concentration of the coal mining subsidence area, the functional microorganisms and carrier materials are matched using the microbial remediation database to construct the initial microbial remediation parameters; then the coal mining subsidence area is segmented according to the terrain characteristics to obtain several subsidence areas; further, based on the terrain information of the several subsidence areas and combined with rainfall conditions, the carrier materials are subjected to migration and diffusion analysis respectively, and the initial microbial remediation parameters are compensated according to the diffusion analysis results to obtain several compensated remediation parameters; then, based on the terrain information of the several subsidence areas and combined with rainfall conditions, the carrier materials are subjected to migration and diffusion analysis respectively, and the initial microbial remediation parameters are compensated according to the diffusion analysis results to obtain several compensated remediation parameters; finally, according to the several optimized remediation parameters, the soil ecological remediation of the several subsidence areas is performed. In other words, by dynamically adjusting the microbial remediation parameters according to the terrain characteristics, climate characteristics and soil environmental factors of the coal mining subsidence area, the accuracy and reliability of the microbial remediation parameter settings can be significantly improved, and the goal of efficient and stable soil remediation can be achieved, thereby achieving the technical effect of effectively degrading pollutants and restoring soil fertility. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of the steps of a soil ecological restoration method for coal mining subsidence areas according to the present invention; Figure 2 This is a schematic structural diagram of a soil ecological restoration system for coal mining subsidence areas according to the present invention; Figure 3 A schematic structural diagram of the electronic device provided by the present invention; Figure 4 A schematic structural diagram of a computer-readable storage medium provided by the present invention.

[0016] Description of reference numerals: Initial restoration parameter construction module 11, coal mining subsidence area segmentation module 12, migration and diffusion analysis module 13, activity fluctuation analysis module 14, soil ecological restoration module 15, electronic device 500, memory 510, processor 520, first computer program 511, computer readable storage medium 600, second computer program 611. DETAILED DESCRIPTION

[0017] This invention provides a method and system for soil ecological restoration in coal mining subsidence areas, addressing the technical problem that traditional microbial remediation methods fail to fully consider the migration and diffusion of microorganisms and changes in microbial activity during the soil remediation process, resulting in insufficient precision and stability in soil remediation. By dynamically adjusting microbial remediation parameters based on the topographical characteristics, climate characteristics, and soil environmental factors of the coal mining subsidence area, the accuracy and reliability of microbial remediation parameter settings can be significantly improved, achieving the goal of efficient and stable soil remediation, thereby achieving the technical effect of effectively degrading pollutants and restoring soil fertility.

[0018] Below, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention, rather than all, are shown in the accompanying drawings.

[0019] For example, see the attached Figure 1 The present invention provides a soil ecological restoration method for coal mining subsidence areas, which is applied to a soil ecological restoration system for coal mining subsidence areas and specifically includes the following steps: S10: Detect and obtain the pollutant types and concentrations in the coal mining subsidence area, use the microbial remediation database to match functional microorganisms and carrier materials, and construct initial microbial remediation parameters.

[0020] Furthermore, step S10 of the present invention further includes: S11: Detect and obtain the soil acid-base characteristics of the coal mining subsidence area; S12: Utilize the microbial remediation database to perform functional microbial matching based on the soil acid-base characteristics, pollutant types and pollutant concentrations, and determine a number of microbial types and a number of microbial concentrations; S13: Perform carrier material matching based on the several microbial types and the several microbial concentrations, and determine a plurality of carrier material types and a plurality of carrier material concentrations; S14: Construct initial microbial remediation parameters based on the several microbial types, the several microbial concentrations, the multiple carrier material types and the multiple carrier material concentrations.

[0021] Specifically, first, multiple sampling points are identified based on the topographical characteristics of the coal mining subsidence area (such as low-lying areas, sloping areas, and flat areas) to ensure comprehensive pollutant distribution. Next, different sampling depths are selected based on the potential distribution depth of the pollutants. Generally speaking, sampling depths can be divided into surface soil (0 to 20 cm), mid-soil (20 to 40 cm), and deep soil (40 cm and above). Then, depending on the size of the area, a sufficient number of sampling points is ensured. Typically, at least 3 to 5 samples are collected from each area, and sampling is conducted in different seasons to assess the dynamic changes in pollutants. The sampled soil is then tested using pollutant analysis methods. Commonly used pollutant analysis methods include gas chromatography, liquid chromatography, and atomic absorption spectrometry to determine the types and concentrations of pollutants in the coal mining subsidence area. Pollutant types include organic pollutants (such as petroleum hydrocarbons), heavy metal pollutants (such as lead, cadmium, arsenic, chromium, and mercury), and nutrient element pollutants (such as excess nitrogen and phosphorus).

[0022] Next, soil acidity and alkalinity characteristics in coal mining subsidence areas are measured, such as using a pH meter. A pH value less than 7 indicates acidity, greater than 7 indicates alkalinity, and values close to 7 indicate neutral soil. A microbial remediation database is then constructed. These databases, based on historical data, contain extensive information on microorganisms relevant to soil remediation, including their functional characteristics, adapted soil environments, pollutant degradation capabilities, and optimal growth conditions.

[0023] The microbial remediation database is further utilized to match functional microorganisms based on the soil's acid-alkalinity characteristics, pollutant type, and pollutant concentration. Specifically, based on the soil's pH value, the database recommends microorganisms suitable for that pH range. For example, if the soil is acidic, the database recommends acid-tolerant bacteria or fungi; if the soil is alkaline, it recommends alkali-tolerant microorganisms. Based on the type of soil pollutant (such as heavy metals or organic pollutants), the database recommends microorganisms with targeted degradation capabilities. For example, if the soil pollutant is oil or organic solvent, microbial strains capable of degrading petroleum hydrocarbons can be selected; if the soil pollutant is heavy metal (such as lead or cadmium), microorganisms capable of removing or reducing heavy metals can be selected. Based on the pollutant concentration, the database recommends an appropriate microbial concentration: for low-concentration pollution, a lower concentration is recommended; for high-concentration pollution, a higher concentration is recommended to ensure sufficient degradation capacity. Based on these matching results, suitable microbial strains and concentrations are determined, resulting in a number of microbial types and concentrations.

[0024] Then, carrier materials are matched based on the aforementioned microbial types and concentrations. This means that appropriate carrier materials are selected based on the microbial type and soil environment characteristics. Common carrier material types include biochar, bentonite, and natural organic matter (such as humic acid and compost). Different types of carrier materials are suitable for different microbial types and scenarios. For example, biochar is a highly porous carbon-based material that can provide a habitat for microorganisms and has the ability to adsorb pollutants. Biochar can increase the organic matter content of the soil and improve soil structure. It is suitable for the remediation of organic pollutants and heavy metal-contaminated soils and can be matched with microorganisms that can grow in carbon-based environments (such as organic degrading bacteria and heavy metal-reducing bacteria). Bentonite is a natural clay mineral with high adsorption properties. It can absorb water and microorganisms, which helps the survival of microorganisms in the soil. Bentonite also has a good soil improvement effect, which can improve the water retention and air permeability of the soil. It is suitable for remediation in moist, low-acidic soils, especially when the pollutants to be remediated in the soil are organic pollutants or heavy metals. It is suitable for matching with microorganisms that are resistant to moisture and clay environments (such as certain denitrifying bacteria, nitrifying bacteria, etc.).

[0025] Finally, the initial microbial remediation parameters are constructed by combining the aforementioned microbial types, microbial concentrations, carrier material types, and carrier material concentrations. By comprehensively considering multiple factors such as microbial type, concentration, carrier material type, and concentration, the microbial remediation effect in the soil can be maximized.

[0026] S20: Segment the coal mining subsidence area according to terrain features to obtain a plurality of subsidence areas.

[0027] Furthermore, step S20 of the present invention further includes: S21: In the simulation space, starting from the lowest point of the coal mining subsidence area, simulate water injection into the coal mining subsidence area, and calculate and obtain the height difference and slope difference between the current position and the lowest point; S22: If the height difference is greater than the preset height threshold or the slope difference is greater than the preset slope threshold, set a dividing line at the current position, and starting from the current position, continue to simulate water injection into the coal mining subsidence area until reaching the highest point of the coal mining subsidence area, harvest multiple dividing lines, divide the coal mining subsidence area according to the multiple dividing lines, and obtain several subsidence areas, wherein each subsidence area is marked with a regional slope and regional height.

[0028] Specifically, first, a simulation space is constructed, which can be based on a terrain simulation of a digital elevation model or a three-dimensional topographic map, and can accurately represent the terrain undulations of the subsidence area; then, in the simulation space, with the lowest point of the coal mining subsidence area as the starting point, through water injection simulation, the simulated water flow starts from the lowest point and gradually expands to various parts of the subsidence area; in each simulation step, the height difference between the current position and the lowest point is calculated, that is, the difference between the altitude of the current position and the altitude of the lowest point, and according to the changes in the terrain, the difference between the slope of the current position and the slope of the lowest point is calculated. The slope is the rate of change of the ground undulation, usually expressed by the slope of the terrain, and the height difference and slope difference between the current position and the lowest point are obtained.

[0029] Next, configure a preset height threshold and a preset slope threshold. The preset height threshold and the preset slope threshold can be set according to the segmentation accuracy and the area of the coal mining subsidence area. For example, the preset height threshold is set to 1 meter, and the preset slope threshold is set to 2 degrees. If the height difference between the current position and the lowest point is greater than the preset height threshold, it means that the terrain at the current position has changed significantly and needs to be segmented at the current position; if the slope difference between the current position and the lowest point is greater than the threshold, it means that the slope change at the current position is more significant and also needs to be segmented at the current position; that is, if the height difference is greater than the preset height threshold or the slope difference is greater than the preset slope threshold, a segmentation line is set at the current position; then, starting from the current position, continue to simulate watering the coal mining subsidence area, repeat the above steps (calculate the height difference, slope difference, and determine whether segmentation is required) until the simulated water flow reaches the highest point of the subsidence area, and multiple segmentation lines are harvested.

[0030] The coal mining subsidence area is further divided according to the multiple dividing lines, and each subsidence area is confined between two adjacent dividing lines to form a separate area, wherein each area has a specific terrain feature, including its regional height and regional slope. The height of each subsidence area is set by default to the median value of all terrain heights in the area, that is, the median value of the maximum and minimum heights of the area; the slope of each area is set by default to the median value of the slopes in the area, that is, the average value or median value of all slopes in the area; finally, after segmentation, the coal mining subsidence area is divided into several subsidence areas, and each subsidence area is marked with its regional slope and regional height. These values can provide accurate regional division and data support for ecological restoration, effectively improve the accuracy and pertinence of soil remediation, and thus achieve more efficient remediation effects.

[0031] S30: Based on the topographic information of the several subsidence areas and in combination with rainfall conditions, migration and diffusion analysis is performed on the carrier materials respectively, and the initial microbial remediation parameters are compensated once according to the diffusion analysis results to obtain several compensated remediation parameters.

[0032] Furthermore, step S30 of the present invention further includes: S31: Obtain the average annual rainfall and average annual rainfall intensity of the coal mining subsidence area within a preset historical time range, and set them as rainfall conditions; S32: Randomly select a first subsidence area from the several subsidence areas, and obtain the first area slope and first area height of the first subsidence area; S33: Randomly select a first carrier material type from multiple carrier material types.

[0033] Specifically, first, the average annual rainfall and average annual rainfall intensity of the coal mining subsidence area within a preset historical time range (e.g., the last five years) are obtained. Specifically, rainfall data for the coal mining subsidence area within the preset historical time range is obtained, the total annual rainfall amount is calculated, and the average value is obtained. The average annual rainfall intensity within the same historical time range is calculated, where rainfall intensity is the intensity of precipitation per unit time. The average annual rainfall and average annual rainfall intensity are then set as rainfall conditions. Next, any one of the multiple subsidence areas is randomly selected as the first subsidence area, and the first area slope and first area height of the first subsidence area are obtained. Furthermore, a first carrier material type, such as biochar or bentonite, is randomly selected from a plurality of carrier material types.

[0034] S34: performing a migration and diffusion analysis on the first carrier material type according to the average annual rainfall, the average annual rainfall intensity, the slope of the first area, and the height of the first area, and outputting a first diffusion ratio.

[0035] Furthermore, step S34 of the present invention further includes: S341: Using the first carrier material type as the retrieval condition, based on the microbial remediation records of historical coal mining subsidence areas, collect the sample annual average rainfall set, sample annual average rainfall intensity set, sample area slope set and sample area height set, and obtain the annual diffusion ratio of the first carrier material type under different sample annual average rainfall, sample annual average rainfall intensity, sample area slope and sample area height, and construct a sample diffusion ratio set, wherein the annual diffusion ratio is positive or negative; S342: Using the sample annual average rainfall set, sample annual average rainfall intensity set, sample area slope set and sample area height set as input, and using the sample diffusion ratio set as supervision, train the BP neural network until the model converges to obtain a material diffusion analyzer; S343: Using the material diffusion analyzer, perform migration and diffusion analysis based on the average annual rainfall, average annual rainfall intensity, first area slope and first area height, and output the first diffusion ratio.

[0036] Specifically, using the first carrier material type as a search criterion, we searched for historical remediation cases and experimental records based on the selected carrier material type (e.g., biochar, bentonite, etc.) based on historical records of microbial remediation in coal mining subsidence areas. The carrier material type significantly influences the migration and diffusion characteristics of microorganisms, and therefore the selected carrier material directly affects the remediation efficacy of microorganisms. We collected data sets for average annual rainfall, average annual rainfall intensity, slope, and altitude. Next, we obtained the annual diffusion ratio of the first carrier material type for different average annual rainfall, average annual rainfall intensity, slope, and altitude. The annual diffusion ratio refers to the change in the migration and diffusion of the carrier material and microorganisms, reflecting the activity and stability of microorganisms in the soil and indicating changes in the migration and diffusion of microorganisms under different topographic and climatic conditions within a given year. The annual diffusion ratio can be positive or negative, with a positive value indicating an increase in the total microbial population and a negative value indicating a decrease. Finally, we constructed a sample diffusion ratio set.

[0037] Then, the sample annual average rainfall set, the sample annual average rainfall intensity set, the sample regional slope set, the sample regional height set and the sample diffusion ratio set are used as training data, the sample annual average rainfall, the sample annual average rainfall intensity, the sample regional slope and the sample regional height are used as input, and the sample diffusion ratio is used as supervision to train the BP neural network, wherein the BP neural network includes an input layer, multiple hidden layers and an output layer, the input layer will receive four input features, namely, the annual average rainfall, the annual average rainfall intensity, the regional slope and the regional height, the output layer has a neuron for outputting the annual diffusion ratio (positive or negative); in order to improve the training efficiency of the BP neural network, the input data needs to be standardized or normalized, such as normalizing the annual average rainfall, the annual average rainfall intensity, the regional slope and the regional height to the interval of [0, 1], so as to avoid the difference in different feature dimensions affecting the network training. During training, the network's output is calculated through forward propagation, and the input data is calculated at each layer, ultimately resulting in the network's predicted value. Next, a loss function (such as mean squared error) is used to measure the difference between the network's prediction and the true label. The gradient of the loss function with respect to each parameter (weights and bias) is calculated to update the network's parameters to reduce the loss. This process (forward propagation, loss calculation, backpropagation, and parameter update) is repeated multiple times on the training set. With each iteration, the neural network adjusts the weights and biases to minimize the loss function until the loss converges or the maximum number of iterations is reached, resulting in a fully trained material diffusion analyzer.

[0038] Finally, the average annual rainfall, average annual rainfall intensity, slope of the first region, and altitude of the first region are input into the material diffusion analyzer for migration and diffusion analysis, which outputs a first diffusion ratio. The migration and diffusion analysis performed by the material diffusion analyzer accurately predicts the microbial diffusion ratio in a specific region. This result provides data support for actual soil remediation plans, allowing for refined parameter adjustments to ensure the efficiency and stability of microbial remediation.

[0039] S35: Analyze and obtain multiple diffusion ratios of multiple carrier material types in the first subsidence area in sequence, compensate the microbial concentration and carrier material concentration in the initial microbial remediation parameters according to the multiple diffusion ratios, output a first compensated remediation parameter, and add it to the multiple compensated remediation parameters.

[0040] Furthermore, step S35 of the present invention further includes: S351: Subtract the multiple diffusion ratios from 1 to obtain multiple primary compensation coefficients; S352: Multiply the multiple primary compensation coefficients by the carrier material concentration of the corresponding carrier material type in the initial microbial remediation parameters, and the corresponding microbial concentration of the corresponding carrier material type, to output the first compensation remediation parameter.

[0041] Specifically, using the same method for obtaining the first diffusion ratio, the multiple diffusion ratios of the multiple carrier material types in the first subsidence area are analyzed in turn; then, the multiple diffusion ratios are subtracted from 1 respectively, and the difference between 1 and the diffusion ratio is used as a primary compensation coefficient to obtain multiple primary compensation coefficients. Then, the multiple primary compensation coefficients are multiplied by the carrier material concentration of the corresponding carrier material type in the initial microbial remediation parameters, and the product of the two is used as the carrier material concentration after the primary compensation; and the multiple primary compensation coefficients are multiplied by the corresponding microbial concentration of the corresponding carrier material type, and the product of the two is used as the microbial concentration after the primary compensation, and finally the first compensation remediation parameter is obtained, which represents the required microbial concentration and carrier material concentration based on the consideration of microbial diffusion. This process enables the remediation plan to adapt to different regional conditions more accurately, taking into account the influence of microbial diffusion, thereby improving the remediation effect and stability.

[0042] Then, the same method as that used to obtain the first compensation and repair parameters is used to sequentially analyze and obtain a plurality of compensation and repair parameters for the plurality of subsidence areas.

[0043] S40: performing activity fluctuation analysis on the functional microorganisms according to the soil moisture of the plurality of subsidence areas, and performing secondary compensation on the plurality of compensation and remediation parameters according to the fluctuation analysis results to obtain a plurality of optimized remediation parameters.

[0044] Furthermore, step S40 of the present invention further includes: S41: Randomly select a first subsidence area, obtain the first-year average soil moisture value of the first subsidence area, and a first compensation remediation parameter; S42: Randomly select a first microorganism type from several microorganism types; S43: Based on the first-year average soil moisture value, predict and obtain the first reproduction rate of the first microorganism type, wherein a first activity fluctuation analyzer is constructed based on a BP neural network to predict the reproduction rate; S44: Set the ratio of the first expected reproduction rate of the first microorganism type to the first reproduction rate as a quadratic compensation coefficient, and analyze and obtain several quadratic compensation coefficients in turn, wherein the first expected reproduction rate is the reproduction rate of the first microorganism type under standard soil moisture; S45: According to the several quadratic compensation coefficients, multiply the corresponding microorganism concentration in the first compensation remediation parameter and the corresponding carrier material concentration of the corresponding microorganism concentration to obtain a first optimized remediation parameter, and add it to the several optimized remediation parameters.

[0045] Specifically, first, a randomly selected subsidence area is designated as the first subsidence area. The first-year average soil moisture value and a first compensation remediation parameter are obtained for the first subsidence area. For example, humidity data for the first subsidence area over the past 12 months are obtained and the average is calculated to obtain the first-year average soil moisture value. Next, a randomly selected microbial type is designated as the first microbial type, such as heavy metal-reducing bacteria or petroleum-degrading bacteria.

[0046] Next, a first activity fluctuation analyzer is constructed based on a BP neural network. The first activity fluctuation analyzer is a BP neural network model that can be iteratively optimized in machine learning and is used to predict the reproduction rate of a first microbial type (e.g., organic matter-decomposing fungi) under different soil moisture conditions. The BP neural network model includes an input layer, multiple hidden layers, and an output layer. The input data of the input layer is soil moisture, and the output data of the output layer is the reproduction rate of the first microbial type. Then, with the first microbial type as a constraint, a set of sample soil moisture and a set of sample reproduction rates are collected. The first activity fluctuation analyzer is supervised trained using the set of sample soil moisture and the set of sample reproduction rates. During the training process, first, an appropriate loss function (e.g., mean squared error) is selected to measure the error between the network's predicted value and the actual value, with the goal of minimizing this error and adjusting the network weights. Next, the input data is passed through the network to obtain a predicted output, and the error between the predicted output and the actual output is calculated using the loss function. The network weights are then adjusted based on the error to reduce the prediction error, and the gradient descent algorithm is used to minimize the loss function and optimize the network weights. The network undergoes multiple iterations during the training process, and the weights and biases are updated at each iteration to improve the accuracy of the prediction. During training, the network's error gradually decreases until the model converges, resulting in a fully trained first activity fluctuation analyzer. Through supervised learning, the BP neural network gradually learns the relationship between soil moisture and microbial growth rate. Once trained, the neural network can predict microbial growth rates based on given soil moisture conditions, effectively improving the accuracy and efficiency of microbial growth rate predictions.

[0047] Then, the mean soil moisture value of the first year is input into the first activity fluctuation analyzer to predict and obtain the first reproduction rate of the first microorganism type; further, the ratio of the first expected reproduction rate of the first microorganism type to the first reproduction rate is set as the quadratic compensation coefficient, wherein the first expected reproduction rate is the reproduction rate of the first microorganism type under standard soil moisture; then, using the same method, several quadratic compensation coefficients of several microorganism types in the first subsidence area are analyzed in turn.

[0048] Then, the several secondary compensation coefficients are multiplied by the corresponding microbial concentration in the first compensation remediation parameter, and the product of the two is used as the microbial concentration after secondary compensation; the several secondary compensation coefficients are multiplied by the corresponding carrier material concentration of the corresponding microbial concentration, and the product of the two is used as the carrier material concentration after secondary compensation to obtain the first optimized remediation parameter of the first subsidence area, and the same method is used to analyze and obtain several optimized remediation parameters of several subsidence areas in turn.

[0049] S50: Performing soil ecological restoration of the plurality of subsidence areas according to the plurality of optimized restoration parameters.

[0050] Specifically, according to the optimized remediation parameters, the microbial types, carrier materials, and other related remediation materials required for remediation are prepared. For example, based on the selected microbial types and their concentrations, as well as the selected carrier materials and their concentrations, corresponding remediation agents are prepared according to the different requirements of the region. Subsequently, the microbial remediation agents are evenly applied to the soil surface or deep layers through spraying, broadcasting, plowing, and other methods. By performing soil ecological remediation in coal mining subsidence areas according to the optimized remediation parameters, the accuracy and effectiveness of remediation can be significantly improved. This remediation method can dynamically adjust the application amount and concentration of the microbial remediation agent based on the specific conditions of each subsidence area (such as soil moisture, pollutant type, and topographical characteristics), ensuring that the microbial activity and remediation effect during the remediation process reach optimal levels, ultimately achieving pollutant degradation and soil fertility restoration.

[0051] In summary, the soil ecological restoration method for coal mining subsidence areas provided by the present invention has the following technical effects: By detecting and obtaining the pollutant type and concentration of the coal mining subsidence area, the functional microorganisms and carrier materials are matched using the microbial remediation database to construct the initial microbial remediation parameters; then the coal mining subsidence area is segmented according to the terrain characteristics to obtain several subsidence areas; further, based on the terrain information of the several subsidence areas and combined with rainfall conditions, the carrier materials are subjected to migration and diffusion analysis respectively, and the initial microbial remediation parameters are compensated according to the diffusion analysis results to obtain several compensated remediation parameters; then, based on the terrain information of the several subsidence areas and combined with rainfall conditions, the carrier materials are subjected to migration and diffusion analysis respectively, and the initial microbial remediation parameters are compensated according to the diffusion analysis results to obtain several compensated remediation parameters; finally, according to the several optimized remediation parameters, the soil ecological remediation of the several subsidence areas is performed. In other words, by dynamically adjusting the microbial remediation parameters according to the terrain characteristics, climate characteristics and soil environmental factors of the coal mining subsidence area, the accuracy and reliability of the microbial remediation parameter settings can be significantly improved, and the goal of efficient and stable soil remediation can be achieved, thereby achieving the technical effect of effectively degrading pollutants and restoring soil fertility.

[0052] Example 2: Based on the same inventive concept as the soil ecological restoration method for coal mining subsidence area in the above embodiment, the present invention also provides a soil ecological restoration system for coal mining subsidence area, please refer to the attached Figure 2, including: an initial remediation parameter construction module 11, which is used to detect and obtain the pollutant type and pollutant concentration in the coal mining subsidence area, use the microbial remediation database to match functional microorganisms and carrier materials, and construct initial microbial remediation parameters; a coal mining subsidence area segmentation module 12, which is used to segment the coal mining subsidence area according to terrain characteristics to obtain several subsidence areas; a migration and diffusion analysis module 13, which is used to perform migration and diffusion analysis on the carrier materials according to the terrain information of the several subsidence areas and combined with rainfall conditions, and compensate the initial microbial remediation parameters once according to the diffusion analysis results to obtain several compensated remediation parameters; an activity fluctuation analysis module 14, which is used to perform activity fluctuation analysis on the functional microorganisms according to the soil moisture of the several subsidence areas, and compensate the several compensated remediation parameters twice according to the fluctuation analysis results to obtain several optimized remediation parameters; a soil ecological remediation module 15, which is used to perform soil ecological remediation of the several subsidence areas according to the several optimized remediation parameters.

[0053] Furthermore, the soil ecological restoration system for coal mining subsidence areas is also used to: detect and obtain the soil acid-base characteristics of the coal mining subsidence area; use the microbial remediation database to perform functional microbial matching based on the soil acid-base characteristics, pollutant types and pollutant concentrations, and determine several microbial types and several microbial concentrations; perform carrier material matching based on the several microbial types and several microbial concentrations, and determine multiple carrier material types and multiple carrier material concentrations; and construct initial microbial remediation parameters based on the several microbial types, several microbial concentrations, multiple carrier material types and multiple carrier material concentrations.

[0054] Furthermore, the soil ecological restoration system for a coal mining subsidence area is also used to: in a simulation space, with the lowest point of the coal mining subsidence area as the starting point, simulate watering the coal mining subsidence area, and calculate the height difference and slope difference between the current position and the lowest point; if the height difference is greater than a preset height threshold or the slope difference is greater than a preset slope threshold, set a dividing line at the current position, and with the current position as the starting point, continue to simulate watering the coal mining subsidence area until reaching the highest point of the coal mining subsidence area, harvest multiple dividing lines, divide the coal mining subsidence area according to the multiple dividing lines, and obtain several subsidence areas, wherein each subsidence area is marked with a regional slope and regional height.

[0055] Furthermore, the soil ecological restoration system for a coal mining subsidence area is also used to: obtain the average annual rainfall and average annual rainfall intensity of the coal mining subsidence area within a preset historical time range, and set them as rainfall conditions; randomly select a first subsidence area from the several subsidence areas, and obtain the first area slope and the first area height of the first subsidence area; randomly select a first carrier material type from multiple carrier material types; perform migration and diffusion analysis on the first carrier material type based on the average annual rainfall, the average annual rainfall intensity, the first area slope and the first area height, and output a first diffusion ratio; sequentially analyze and obtain multiple diffusion ratios of multiple carrier material types in the first subsidence area, compensate the microbial concentration and carrier material concentration in the initial microbial remediation parameters according to the multiple diffusion ratios, output a first compensation remediation parameter, and add it to the several compensation remediation parameters.

[0056] Furthermore, the soil ecological restoration system for coal mining subsidence areas is also used to: use the first carrier material type as a retrieval condition, collect sample annual average rainfall set, sample annual average rainfall intensity set, sample area slope set and sample area height set according to historical microbial restoration records of coal mining subsidence areas, and obtain the annual diffusion ratio of the first carrier material type under different sample annual average rainfall, sample annual average rainfall intensity, sample area slope and sample area height, and construct a sample diffusion ratio set, wherein the annual diffusion ratio is a positive or negative value; use the sample annual average rainfall set, sample annual average rainfall intensity set, sample area slope set and sample area height set as input, use the sample diffusion ratio set as supervision, train the BP neural network until the model converges, and obtain a material diffusion analyzer; use the material diffusion analyzer to perform migration and diffusion analysis based on the annual average rainfall, annual average rainfall intensity, first area slope and first area height, and output the first diffusion ratio.

[0057] Furthermore, the soil ecological restoration system for coal mining subsidence areas is also used to: subtract the multiple diffusion ratios from 1 to obtain multiple primary compensation coefficients; multiply the multiple primary compensation coefficients by the carrier material concentration of the corresponding carrier material type in the initial microbial remediation parameters, and the corresponding microbial concentration of the corresponding carrier material type, to output a first compensation remediation parameter.

[0058] Furthermore, the soil ecological restoration system for coal mining subsidence areas is also used to: randomly select a first subsidence area, obtain the first-year average soil moisture value of the first subsidence area, and a first compensation restoration parameter; randomly select a first microbial type from several microbial types; predict and obtain the first reproduction rate of the first microbial type based on the first-year average soil moisture value, wherein a first activity fluctuation analyzer is constructed based on a BP neural network to predict the reproduction rate; set the ratio of the first expected reproduction rate of the first microbial type to the first reproduction rate as a quadratic compensation coefficient, and analyze and obtain several quadratic compensation coefficients in turn, wherein the first expected reproduction rate is the reproduction rate of the first microbial type under standard soil moisture; according to the several quadratic compensation coefficients, multiply the corresponding microbial concentration in the first compensation restoration parameter and the corresponding carrier material concentration of the corresponding microbial concentration to obtain a first optimized restoration parameter, and add it to the several optimized restoration parameters.

[0059] For example three, please refer to Figure 3 , Figure 3 Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 500, including a memory 510, a processor 520, and a first computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the first computer program 511, the following steps are implemented: detecting and obtaining the pollutant type and pollutant concentration in the coal mining subsidence area, matching functional microorganisms and carrier materials using a microbial remediation database, and constructing initial microbial remediation parameters; segmenting the coal mining subsidence area according to terrain characteristics to obtain a plurality of subsidence areas; performing migration and diffusion analysis on the carrier materials based on the terrain information of the plurality of subsidence areas and combined with rainfall conditions, and performing a primary compensation on the initial microbial remediation parameters based on the diffusion analysis results to obtain a plurality of compensated remediation parameters; performing activity fluctuation analysis on the functional microorganisms based on the soil moisture of the plurality of subsidence areas, and performing a secondary compensation on the plurality of compensated remediation parameters based on the fluctuation analysis results to obtain a plurality of optimized remediation parameters; and performing soil ecological remediation on the plurality of subsidence areas according to the plurality of optimized remediation parameters.

[0060] For example 4, please refer to Figure 4 , Figure 4 Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4As shown, this embodiment provides a computer-readable storage medium 600, on which a second computer program 611 is stored. When the second computer program 611 is executed by the processor, it implements the following steps: detecting and obtaining the pollutant type and pollutant concentration of the coal mining subsidence area, using the microbial remediation database to match functional microorganisms and carrier materials, and constructing initial microbial remediation parameters; segmenting the coal mining subsidence area according to terrain characteristics to obtain several subsidence areas; based on the terrain information of the several subsidence areas and combined with rainfall conditions, performing migration and diffusion analysis on the carrier materials respectively, and compensating the initial microbial remediation parameters once according to the diffusion analysis results to obtain several compensated remediation parameters; based on the soil moisture of the several subsidence areas, performing activity fluctuation analysis on the functional microorganisms respectively, and performing secondary compensation on the several compensated remediation parameters according to the fluctuation analysis results to obtain several optimized remediation parameters; and performing soil ecological remediation of the several subsidence areas according to the several optimized remediation parameters.

[0061] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0062] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0066] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they understand the basic inventive concepts. It is apparent that those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the present invention and its equivalents.

Claims

1. A soil ecological restoration method for coal mining subsidence areas, characterized in that: Methods include: Detect and obtain the pollutant types and concentrations in coal mining subsidence areas, use the microbial remediation database to match functional microorganisms and carrier materials, and establish initial microbial remediation parameters; Segmenting the coal mining subsidence area according to topographic features to obtain a number of subsidence areas; Based on the topographic information of the plurality of subsidence areas and in combination with rainfall conditions, migration and diffusion analysis is performed on the carrier materials respectively, and the initial microbial remediation parameters are compensated according to the diffusion analysis results to obtain a plurality of compensated remediation parameters; According to the soil moisture of the several subsidence areas, the activity fluctuation analysis of the functional microorganisms is performed respectively, and according to the fluctuation analysis results, the several compensation and remediation parameters are respectively compensated twice to obtain several optimized remediation parameters; According to the plurality of optimized restoration parameters, soil ecological restoration of the plurality of subsidence areas is performed.

2. The soil ecological restoration method for coal mining subsidence area according to claim 1, characterized in that: Utilize the microbial remediation database to match functional microorganisms and carrier materials and construct initial microbial remediation parameters, including: Detect and obtain soil acid-base characteristics in coal mining subsidence areas; Using a microbial remediation database, functional microbial matching is performed based on the soil acid-base characteristics, pollutant types, and pollutant concentrations to determine a number of microbial types and a number of microbial concentrations; performing carrier material matching according to the plurality of microorganism types and the plurality of microorganism concentrations to determine a plurality of carrier material types and a plurality of carrier material concentrations; Initial microbial remediation parameters are constructed based on the several microorganism types, the several microorganism concentrations, the multiple carrier material types, and the multiple carrier material concentrations.

3. The soil ecological restoration method for coal mining subsidence area according to claim 2, characterized in that: The coal mining subsidence area is segmented according to the terrain characteristics to obtain several subsidence areas, including: In the simulation space, starting from the lowest point of the coal mining subsidence area, simulated watering is performed on the coal mining subsidence area, and the height difference and slope difference between the current position and the lowest point are calculated; If the height difference is greater than the preset height threshold or the slope difference is greater than the preset slope threshold, a dividing line is set at the current position, and starting from the current position, simulated water irrigation is continued to be performed to the coal mining subsidence area until the highest point of the coal mining subsidence area is reached. Multiple dividing lines are harvested, and the coal mining subsidence area is divided according to the multiple dividing lines to obtain several subsidence areas, wherein each subsidence area is marked with a regional slope and a regional height.

4. The soil ecological restoration method for coal mining subsidence areas according to claim 3, characterized in that: Based on the topographic information of the several subsidence areas and combined with rainfall conditions, the carrier materials are respectively subjected to migration and diffusion analysis. Based on the diffusion analysis results, the initial microbial remediation parameters are compensated once to obtain several compensated remediation parameters, including: Obtaining the average annual rainfall and average annual rainfall intensity of the coal mining subsidence area within a preset historical time range, and setting them as rainfall conditions; Randomly selecting a first subsidence area from the plurality of subsidence areas, and obtaining a first area slope and a first area height of the first subsidence area; randomly selecting a first carrier material type from a plurality of carrier material types; performing a migration and diffusion analysis on the first carrier material type based on the average annual rainfall, the average annual rainfall intensity, the slope of the first area, and the height of the first area, and outputting a first diffusion ratio; Analyze and obtain multiple diffusion ratios of multiple carrier material types in the first subsidence area in sequence, compensate the microbial concentration and carrier material concentration in the initial microbial remediation parameters according to the multiple diffusion ratios, output a first compensated remediation parameter, and add it to the multiple compensated remediation parameters.

5. The soil ecological restoration method for coal mining subsidence areas according to claim 4, characterized in that: Performing a migration and diffusion analysis on the first carrier material type according to the average annual rainfall, the average annual rainfall intensity, the slope of the first area, and the height of the first area, and outputting a first diffusion ratio, including: Taking the first carrier material type as the search condition, based on the microbial remediation records of historical coal mining subsidence areas, a sample annual average rainfall set, a sample annual average rainfall intensity set, a sample area slope set, and a sample area height set are collected, and the annual diffusion ratio of the first carrier material type under different sample annual average rainfall, sample annual average rainfall intensity, sample area slope, and sample area height are obtained to construct a sample diffusion ratio set, where the annual diffusion ratio is a positive or negative value; The sample annual average rainfall set, the sample annual average rainfall intensity set, the sample area slope set, and the sample area height set are used as inputs, and the sample diffusion ratio set is used as supervision to train a BP neural network until the model converges, thereby obtaining a material diffusion analyzer; The material diffusion analyzer is used to perform migration and diffusion analysis based on the average annual rainfall, the average annual rainfall intensity, the slope of the first area, and the height of the first area, and output a first diffusion ratio.

6. The soil ecological restoration method for coal mining subsidence areas according to claim 4, characterized in that: Compensating the microorganism concentration and the carrier material concentration in the initial microbial remediation parameters according to the multiple diffusion ratios and outputting a first compensated remediation parameter includes: Subtracting the plurality of diffusion ratios from 1 to obtain a plurality of primary compensation coefficients; The plurality of primary compensation coefficients are respectively multiplied by the carrier material concentration of the corresponding carrier material type in the initial microbial remediation parameters and the corresponding microbial concentration of the corresponding carrier material type to output a first compensated remediation parameter.

7. The soil ecological restoration method for coal mining subsidence areas according to claim 1, characterized in that: According to the soil moisture of the several subsidence areas, the activity fluctuation analysis of the functional microorganisms is performed respectively, and the several compensation and restoration parameters are secondary compensated according to the fluctuation analysis results to obtain several optimized restoration parameters, including: Randomly selecting a first subsidence area, obtaining a first-year average soil moisture value and a first compensation restoration parameter of the first subsidence area; randomly selecting a first microorganism type from among a plurality of microorganism types; Predicting and obtaining a first reproduction rate of the first microorganism type based on the average soil moisture value in the first year, wherein a first activity fluctuation analyzer is constructed based on a BP neural network to perform the reproduction rate prediction; The ratio of the first expected reproduction rate of the first microorganism type to the first reproduction rate is set as a quadratic compensation coefficient, and a plurality of quadratic compensation coefficients are sequentially analyzed and obtained, wherein the first expected reproduction rate is the reproduction rate of the first microorganism type under standard soil moisture; According to the several quadratic compensation coefficients, the corresponding microorganism concentration in the first compensation remediation parameter and the corresponding carrier material concentration of the corresponding microorganism concentration are multiplied respectively to obtain a first optimized remediation parameter, which is added to the several optimized remediation parameters.

8. A soil ecological restoration system for coal mining subsidence areas, characterized in that: The steps for implementing the soil ecological restoration method for coal mining subsidence areas according to any one of claims 1 to 7 include: The initial remediation parameter construction module is used to detect and obtain the pollutant types and concentrations in coal mining subsidence areas, use the microbial remediation database to match functional microorganisms and carrier materials, and construct initial microbial remediation parameters; A coal mining subsidence area segmentation module is used to segment the coal mining subsidence area according to terrain features to obtain several subsidence areas; A migration and diffusion analysis module is used to perform migration and diffusion analysis on the carrier materials according to the topographic information of the plurality of subsidence areas and in combination with rainfall conditions, and to compensate the initial microbial remediation parameters according to the diffusion analysis results to obtain a plurality of compensated remediation parameters; an activity fluctuation analysis module, configured to perform activity fluctuation analysis on the functional microorganisms according to the soil moisture of the plurality of subsidence areas, and perform secondary compensation on the plurality of compensation and remediation parameters according to the fluctuation analysis results to obtain a plurality of optimized remediation parameters; The soil ecological restoration module is used to perform soil ecological restoration of the plurality of subsidence areas according to the plurality of optimized restoration parameters.

9. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the steps of the soil ecological restoration method for coal mining subsidence areas as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The storage medium stores a computer software program, which, when executed by a processor, implements the steps of a soil ecological restoration method for a coal mining subsidence area as described in any one of claims 1 to 7.

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