A method and system for ecological restoration of slopes of pumped storage power stations based on a near-nature concept

Abstract

The invention discloses a pumped-storage power station slope ecological restoration method and system based on a near-nature concept, which relates to the field of ecological restoration. The method comprises the following steps: obtaining the current geomorphic features of the pumped-storage power station slope and analyzing to obtain a characteristic factor sequence, obtaining the geographical location of the pumped-storage power station slope and proportionally generating a virtual model; screening planting materials in a planting material library according to current demand conditions and in combination with the characteristic factor sequence to obtain target planting materials, marking the target planting materials in a virtual model and generating a sowing strategy, simulating the growth of planting materials in the virtual model and recording the growth of virtual planting materials in different cycles; collecting the current growth of planting materials on the pumped-storage power station slope, comparing and analyzing the current growth of planting materials with the growth of virtual planting materials in the same cycle to obtain an ecological restoration evaluation of the pumped-storage power station slope; adjusting the sowing strategy according to the ecological restoration evaluation of the pumped-storage power station slope and performing current remediation.

Description

Technical Field

[0001] The present invention relates to the field of ecological restoration, and in particular to a method and system for ecological restoration of a pumped storage power station slope based on a near-nature concept. Background Art

[0002] In recent years, with the continuous growth of energy demand and the emphasis on clean energy, pumped storage power stations have developed rapidly as an effective energy regulation and storage tool. The construction and operation of these power stations have had a significant impact on the surrounding ecological environment, especially the destruction of the slope drawdown zone habitat caused by frequent water level fluctuations. Slope ecological restoration faces many challenges. The water level fluctuates frequently. The operating characteristics of pumped storage power stations lead to frequent water level fluctuations (such as weekly regulation), making the habitat conditions in the slope area extremely unstable. The water level amplitude difference is large. In some pumped storage power stations, the water level amplitude difference can reach hundreds of meters. This drastic change poses severe challenges to plant growth. Harsh habitat conditions, rock slopes usually lack soil and nutrients, and there are extreme environments such as drought, high temperature or low temperature, which are not conducive to plant growth. Plant screening is difficult, and plant species that are cold-resistant, drought-resistant and flood-resistant are required, which increases the difficulty and complexity of ecological restoration.

[0003] The geocell + eco-bag + hanging net composite project, combined with the practice of Henan Tianchi Pumped Storage Power Station, uses geocells, eco-bags and hanging nets for comprehensive management, effectively coping with the complex environment of the drawdown zone. Vegetation concrete ecological restoration technology, which combines traditional protection and reinforcement technology with new vegetation restoration technology, is suitable for slopes of various slopes. Through a specific formula of vegetation concrete substrate and reasonable construction technology, the natural growth of vegetation is promoted to achieve a permanent greening effect. Multi-level plant configuration, different types of plants, such as herbs, shrubs and trees, are planted at different heights of the drawdown zone to adapt to different hydrological and soil conditions and form a stable ecosystem.

[0004] Therefore, there is an urgent need for a pumped-storage power station slope ecological restoration method based on a near-natural concept to solve the above problems. Summary of the invention

[0005] To solve the above problems, the present application provides a method for ecological restoration of the slope of a pumped-storage power station based on a near-natural concept, so as to achieve more accurate and targeted positioning and restoration.

[0006] In this application, a method for ecological restoration of a pumped storage power station slope based on a near-nature concept is provided, comprising the following steps:

[0007] S1. Obtain the geomorphic features of the slope of the current pumped storage power station and analyze to obtain a characteristic factor sequence, obtain the geographical location of the slope of the pumped storage power station and generate a virtual model in proportion;

[0008] S2. A planting material library is preset. According to the current demand and the characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model, and generate a sowing strategy. The planting material library includes planting materials of trees, shrubs, ground cover plants, herbaceous plants, and vines suitable for ecological restoration of the slope of the pumped storage power station;

[0009] S3, obtaining the growth characteristics of the target planting material to generate characteristic data, simulating the growth of the planting material in the virtual model according to the characteristic data combined with the characteristic factor sequence, and recording the growth of the virtual planting material in different cycles;

[0010] S4, collecting the current growth conditions of the planting materials on the slope of the pumped-storage power station, and comparing and analyzing the current growth conditions of the planting materials with the growth conditions of the virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station;

[0011] S5. Adjust the seeding strategy and carry out immediate remediation based on the evaluation of the ecological restoration of the pumped storage power station slope.

[0012] Preferably, the specific contents of obtaining the geomorphic characteristics of the slope of the current pumped storage power station and analyzing and obtaining the characteristic factor sequence in S1 are as follows:

[0013] A characteristic factor table is preset, and the characteristic factor table is composed of characteristic factor sub-tables;

[0014] The characteristic factor sub-table includes a slope factor sub-table, a slope shape factor sub-table, a geological factor sub-table, a lithology factor sub-table, a soil factor sub-table and a hydrological factor sub-table;

[0015] The slope factor is divided into gradients according to the difficulty of repair to generate a slope factor sub-table;

[0016] The slope factor is divided according to the appearance to generate a slope factor sub-table;

[0017] Generate a geological factor category table based on the existence of faults and fracture zones on the slopes of pumped storage power stations;

[0018] Generate a geological factor degree table based on the number of faults and fracture zones on the slope of the pumped storage power station;

[0019] The geological factor category table and the geological factor degree table are matched to generate a geological factor sub-table;

[0020] Generate a lithology factor sub-table based on the weathering resistance and mechanical properties of the rock;

[0021] Generate soil factor sub-tables according to soil types and different soil properties;

[0022] Generate a sub-table of hydrological factors based on the presence of groundwater and its dynamic changes;

[0023] Conduct an overall analysis of the current landform characteristics to obtain the overall characteristic factors of the current landform characteristics, confirm the table position of the current overall characteristic factors in the characteristic factor table, and generate the overall sequence of the current characteristic factors according to the table position;

[0024] The slope of the current pumped storage power station is divided into blocks, and the geomorphic features of different blocks are analyzed to obtain the block characteristic factors of the current geomorphic features. The table position of the current block characteristic factors is confirmed in the characteristic factor table, and the current characteristic factor block sequence is generated according to the table position.

[0025] Preferably, the virtual model in S1 is a three-dimensional model, and the virtual model restores the slope of the pumped storage power station in proportion;

[0026] The virtual model is meshed according to the current block division of the pumped storage power station slope;

[0027] Mark the current feature factor block sequence in the grid respectively.

[0028] Preferably, the specific contents of S2 in which planting materials are screened in the planting material library to obtain target planting materials and generate a sowing strategy according to the current demand situation and the characteristic factor sequence are:

[0029] The planting material library includes a number of planting materials, and correspondingly marks the growth environment;

[0030] Analyze the growth environment of the slope of the pumped storage power station according to the overall sequence of current characteristic factors, and match the first target planting material;

[0031] Screening the first target planting material according to the current characteristic factor block sequence to obtain the second target planting material;

[0032] The second target planting materials are marked in different grids of the virtual model and the sowing strategy is generated synchronously.

[0033] Preferably, the specific contents of obtaining the growth characteristics of the target planting material to generate characteristic data, simulating the growth of the planting material in the virtual model according to the characteristic data combined with the characteristic factor sequence, and recording the growth of the virtual planting material in different cycles are as follows:

[0034] The virtual model is a three-dimensional visualization model, which is internally integrated with a neural network module;

[0035] The characteristic data include growth environment parameters of the planting material, characteristic data of the planting material and growth result data;

[0036] The characteristic data is cleaned to remove outliers and normalized to obtain sample characteristic data;

[0037] The characteristic factor sequence was analyzed to obtain the influencing characteristics of planting materials;

[0038] The sample characteristic data and the characteristics affecting the planting materials are input into the neural network module, and the neural network module learns the growth pattern and law of the planting materials to obtain output data;

[0039] The output data is brought into a three-dimensional visualization model to simulate the growth of planting materials in different blocks generated in different grids;

[0040] Color rendering is performed according to the height of vegetation, and the height of vegetation is displayed through different color differences;

[0041] Points are confirmed and calibrated according to the degree of vegetation sparseness.

[0042] Preferably, the specific contents of the neural network module include:

[0043] The dataset is divided into training set, validation set and test set, with the ratio of 60% training set, 20% validation set and 20% test set;

[0044] Determine the number of neurons in the input layer according to the type of implant material characteristic data;

[0045] Calculate the number of groups of planting material characteristic data, and take one tenth of the value as the number of hidden layers;

[0046] Set the softmax function as the activation function.

[0047] Preferably, the current growth of planting materials on the slope of the pumped storage power station is collected, and the current growth of planting materials is compared and analyzed with the growth of virtual planting materials in the same period to obtain the specific content of the ecological restoration evaluation of the slope of the pumped storage power station:

[0048] According to the growth height range of plants of different families, the corresponding heights of the grids are divided into gradients;

[0049] Obtaining color difference values ​​of different grids under different gradients, presetting a standard difference value range, and defining a grid whose color difference value is outside the standard difference value range as a first unqualified grid;

[0050] Obtain the vegetation sparseness calibration result, count the calibration points of different grids, preset a standard calibration point number range, and define the grids with calibration points outside the standard calibration point number range as the second unqualified grid;

[0051] Configure the first influence coefficient according to the influence of different grid heights on the overall model;

[0052] Configure the second influence coefficient according to the influence of different grid sparsity levels on the overall model;

[0053] The number of the first unqualified grids and the second unqualified grids under different gradients is obtained and combined with the degree of impact to calculate the evaluation value of the slope ecological restoration of the pumped-storage power station.

[0054] Preferably, the expression of the evaluation value of the slope ecological restoration of the pumped storage power station is:

[0055] ;

[0056] in, is the first influence coefficient, is the second influence coefficient, is the color difference value, is the number of calibration points, is the number of the first unqualified grids, is the number of the second unqualified grids, N is the total number of grids, and m is the different gradients.

[0057] The present application also provides a pumped storage power station slope ecological restoration system based on a near-nature concept, including:

[0058] Data acquisition module: obtain the geomorphic features of the current pumped storage power station slope and analyze to obtain the characteristic factor sequence, obtain the geographical location of the pumped storage power station slope and generate a virtual model in proportion;

[0059] Strategy generation module: There is a planting material library preset. According to the current demand and characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model and generate a sowing strategy;

[0060] Simulation display module: obtain the growth characteristics of the target planting material to generate characteristic data, simulate the growth of the planting material in the virtual model based on the characteristic data and the characteristic factor sequence, and record the growth of the virtual planting material in different cycles;

[0061] Restoration evaluation module: collect the current growth of planting materials on the slope of the pumped-storage power station, compare and analyze the current growth of planting materials with the growth of virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station;

[0062] Correction and adjustment module: adjust the seeding strategy and carry out immediate remediation according to the evaluation of the ecological restoration of the slope of the pumped storage power station.

[0063] In summary, the present invention is a pumped-storage power station slope ecological restoration method based on the near-natural concept. Compared with traditional restoration technology, this method identifies and distinguishes the slopes of pumped-storage power stations, and sows corresponding planting materials in different areas in a targeted manner. It is more practical. In addition, a virtual model is used to predict and evaluate vegetation growth, which helps to correct the implementation strategy based on practicality.

[0064] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is a flow chart of a method for ecological restoration of a pumped storage power station slope based on a near-nature concept of the present invention;

[0066] Figure 2 This is a module diagram of a pumped storage power station slope ecological restoration system based on a near-nature concept according to the present invention. DETAILED DESCRIPTION

[0067] The technical solution of the present invention is further described below by means of the accompanying drawings and embodiments. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​described in these embodiments do not limit the scope of the present application.

[0068] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present application, its application, or uses.

[0069] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0070] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0071] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0072] like Figure 1 As shown, in this application, a method for ecological restoration of a pumped storage power station slope based on a near-nature concept is provided, comprising the following steps:

[0073] S1. Obtain the geomorphic features of the slope of the current pumped storage power station and analyze to obtain a characteristic factor sequence, obtain the geographical location of the slope of the pumped storage power station and generate a virtual model in proportion;

[0074] Furthermore, the specific contents of the characteristic factor sequence obtained by obtaining the geomorphic characteristics of the slope of the current pumped storage power station and analyzing it in S1 are as follows:

[0075] A characteristic factor table is preset, and the characteristic factor table is composed of characteristic factor sub-tables;

[0076] The characteristic factor sub-table includes a slope factor sub-table, a slope shape factor sub-table, a geological factor sub-table, a lithology factor sub-table, a soil factor sub-table and a hydrological factor sub-table;

[0077] The slope factor is divided into gradients according to the difficulty of repair to generate a slope factor sub-table;

[0078] Slope is one of the most important geomorphological features of the slope, which directly affects the stability of the slope. Generally speaking, the steeper the slope, the worse the stability of the slope. For example, the slope of the west bank of the Yanqu Pumped Storage Power Station is between 20° and 35°, and even reaches 48° in some areas. Such high-slope areas may require more stringent protection measures.

[0079] The slope factor is divided according to the appearance to generate a slope factor sub-table;

[0080] Slope shape refers to the appearance of the slope, such as straight, concave, convex, etc. Different slope shapes will have different stress states and erosion modes, thus affecting the stability of the slope.

[0081] Generate a geological factor category table based on the existence of faults and fracture zones on the slopes of pumped storage power stations;

[0082] Geological structures such as faults and fracture zones directly affect the stability of slopes. For example, through high-density electrical profile analysis, the distribution of fracture zones and faults underground can be inferred, which is crucial for assessing slope stability.

[0083] Generate a geological factor degree table based on the number of faults and fracture zones on the slope of the pumped storage power station;

[0084] The type of rock in the slope (sandstone, shale, granite, etc.) also affects its stability. Different rocks have different weathering resistance and mechanical properties, so a detailed understanding of the slope's rock properties is essential.

[0085] The geological factor category table and the geological factor degree table are matched to generate a geological factor sub-table;

[0086] Generate a lithology factor sub-table based on the weathering resistance and mechanical properties of the rock;

[0087] Generate soil factor sub-tables according to soil types and different soil properties;

[0088] The type of soil (e.g. clay, sand, gravel, etc.) affects the hydrological conditions and mechanical properties of the slope. For example, clay has high cohesion, while sand and gravel are more permeable.

[0089] Generate a sub-table of hydrological factors based on the presence of groundwater and its dynamic changes;

[0090] The presence of groundwater and its dynamic changes have a significant impact on slope stability. Especially in pumped storage power stations, periodic fluctuations in water levels may cause changes in water pressure inside the slope, increasing the risk of landslides.

[0091] Surface water sources such as rainfall and snowmelt are one of the main external forces that trigger slope landslides. The erosion of water can weaken the shear strength of the soil and increase the possibility of slope instability.

[0092] Conduct an overall analysis of the current landform characteristics to obtain the overall characteristic factors of the current landform characteristics, confirm the table position of the current overall characteristic factors in the characteristic factor table, and generate the overall sequence of the current characteristic factors according to the table position;

[0093] The slope of the current pumped storage power station is divided into blocks, and the geomorphic features of different blocks are analyzed to obtain the block characteristic factors of the current geomorphic features. The table position of the current block characteristic factors is confirmed in the characteristic factor table, and the current characteristic factor block sequence is generated according to the table position.

[0094] Furthermore, the virtual model in S1 is a three-dimensional model, and the virtual model restores the slope of the pumped storage power station in proportion;

[0095] The virtual model is meshed according to the current block division of the pumped storage power station slope;

[0096] Mark the current feature factor block sequence in the grid respectively.

[0097] S2. A planting material library is preset. According to the current demand situation and the characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model and generate a sowing strategy. The planting material library includes planting materials of trees, shrubs, ground cover plants, herbaceous plants and vines suitable for ecological restoration of the slope of pumped storage power stations, namely, seedlings of trees, seedlings of shrubs, seeds of ground cover plants, herbaceous plant seeds and vine seeds.

[0098] Furthermore, in S2, the specific contents of screening planting materials in the planting material library to obtain target planting materials and generating a sowing strategy according to the current demand situation and the characteristic factor sequence are as follows:

[0099] The planting material library includes a number of planting materials, and correspondingly marks the growth environment;

[0100] Analyze the growth environment of the slope of the pumped storage power station according to the overall sequence of current characteristic factors, and match the first target planting material;

[0101] Screening the first target planting material according to the current characteristic factor block sequence to obtain the second target planting material;

[0102] The second target planting materials are marked in different grids of the virtual model and the sowing strategy is generated synchronously.

[0103] S3, obtaining the growth characteristics of the target planting material to generate characteristic data, simulating the growth of the planting material in the virtual model according to the characteristic data combined with the characteristic factor sequence, and recording the growth of the virtual planting material in different cycles;

[0104] The complexity of the problem and the characteristics of the data determine the appropriate type and architecture of the neural network, ensuring the quality and diversity of the data so that the model can learn the general laws of growth of planting materials.

[0105] Furthermore, the growth characteristics of the target planting material are obtained to generate characteristic data. The specific contents of simulating the growth of the planting material in the virtual model and recording the growth of the virtual planting material in different cycles according to the characteristic data combined with the characteristic factor sequence are as follows:

[0106] The virtual model is a three-dimensional visualization model, which is internally integrated with a neural network module;

[0107] The characteristic data include growth environment parameters of the planting material, characteristic data of the planting material and growth result data;

[0108] The characteristic data is cleaned to remove outliers and normalized to obtain sample characteristic data;

[0109] The characteristic factor sequence was analyzed to obtain the influencing characteristics of planting materials;

[0110] The sample characteristic data and the characteristics affecting the planting materials are input into the neural network module, and the neural network module learns the growth pattern and law of the planting materials to obtain output data;

[0111] The output data is brought into a three-dimensional visualization model to simulate the growth of planting materials in different blocks generated in different grids;

[0112] Color rendering is performed according to the height of vegetation, and the height of vegetation is displayed through different color differences;

[0113] Points are confirmed and calibrated according to the degree of vegetation sparseness.

[0114] Furthermore, the specific contents of the neural network module include:

[0115] The dataset is divided into training set, validation set and test set, with a ratio of 60% training set, 20% validation set and 20% test set. Reasonable division of training set and test set can ensure that the model can make effective predictions on unseen data.

[0116] Determine the number of neurons in the input layer according to the type of implant material characteristic data;

[0117] Calculate the number of groups of planting material characteristic data, and take one tenth of the value as the number of hidden layers;

[0118] Set the softmax function as the activation function.

[0119] It can be understood that the softmax function is an activation function for multi-class classification problems, which converts a real number vector into a probability distribution vector so that the output probability value is between 0 and 1, and the sum of all output values ​​is 1. Subtracting the maximum value from each input value can ensure the stability of the value and avoid overflow problems.

[0120] S4, collecting the current growth conditions of the planting materials on the slope of the pumped-storage power station, and comparing and analyzing the current growth conditions of the planting materials with the growth conditions of the virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station;

[0121] Furthermore, the current growth of planting materials on the slope of the pumped storage power station is collected, and the current growth of planting materials is compared with the growth of virtual planting materials in the same period. The specific content of the ecological restoration evaluation of the slope of the pumped storage power station is obtained as follows:

[0122] According to the growth height range of plants of different families, the corresponding heights of the grids are divided into gradients;

[0123] Obtaining color difference values ​​of different grids under different gradients, presetting a standard difference value range, and defining a grid whose color difference value is outside the standard difference value range as a first unqualified grid;

[0124] Obtain the vegetation sparseness calibration result, count the calibration points of different grids, preset a standard calibration point number range, and define the grids with calibration points outside the standard calibration point number range as the second unqualified grid;

[0125] Configure the first influence coefficient according to the influence of different grid heights on the overall model;

[0126] Configure the second influence coefficient according to the influence of different grid sparsity levels on the overall model;

[0127] The number of the first unqualified grids and the second unqualified grids under different gradients is obtained and combined with the degree of impact to calculate the evaluation value of the slope ecological restoration of the pumped-storage power station.

[0128] Preferably, the expression of the evaluation value of the slope ecological restoration of the pumped storage power station is:

[0129] ;

[0130] in, is the first influence coefficient, is the second influence coefficient, is the color difference value, is the number of calibration points, is the number of the first unqualified grids, is the number of the second unqualified grids, N is the total number of grids, and m is the different gradients.

[0131] S5. Adjust the seeding strategy and carry out immediate remediation based on the evaluation of the ecological restoration of the pumped storage power station slope.

[0132] The present application also provides a pumped storage power station slope ecological restoration system based on a near-nature concept, including:

[0133] Data acquisition module: obtain the geomorphic features of the current pumped storage power station slope and analyze to obtain the characteristic factor sequence, obtain the geographical location of the pumped storage power station slope and generate a virtual model in proportion;

[0134] Strategy generation module: There is a planting material library preset. According to the current demand and characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model and generate a sowing strategy;

[0135] Simulation display module: obtain the growth characteristics of the target planting material to generate characteristic data, simulate the growth of the planting material in the virtual model based on the characteristic data and the characteristic factor sequence, and record the growth of the virtual planting material in different cycles;

[0136] Restoration evaluation module: collect the current growth of planting materials on the slope of the pumped-storage power station, compare and analyze the current growth of planting materials with the growth of virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station;

[0137] Correction and adjustment module: adjust the seeding strategy and carry out immediate remediation according to the evaluation of the ecological restoration of the slope of the pumped storage power station.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for ecological restoration of slopes of pumped storage power stations based on a near-nature concept, characterized in that: The following steps are involved: S1. Obtain the geomorphic features of the slope of the current pumped storage power station and analyze to obtain a characteristic factor sequence, obtain the geographical location of the slope of the pumped storage power station and generate a virtual model in proportion; S2. A planting material library is preset. According to the current demand and the characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model, and generate a sowing strategy. The planting material library includes planting materials of trees, shrubs, ground cover plants, herbaceous plants, and vines suitable for ecological restoration of the slope of the pumped storage power station; S3, obtaining the growth characteristics of the target planting material to generate characteristic data, simulating the growth of the planting material in the virtual model according to the characteristic data combined with the characteristic factor sequence, and recording the growth of the virtual planting material in different cycles; S4, collecting the current growth conditions of the planting materials on the slope of the pumped-storage power station, and comparing and analyzing the current growth conditions of the planting materials with the growth conditions of the virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station; S5. Adjust the seeding strategy and carry out immediate remediation according to the evaluation of the ecological restoration of the pumped storage power station slope; In S2, according to the current demand situation and the characteristic factor sequence, the specific contents of screening planting materials in the planting material library to obtain the target planting materials and generate the sowing strategy are as follows: The planting material library includes a number of planting materials, and correspondingly marks the growth environment; Analyze the growth environment of the slope of the pumped storage power station according to the overall sequence of current characteristic factors, and match the first target planting material; Screening the first target planting material according to the current characteristic factor block sequence to obtain the second target planting material; Marking the second target planting materials in different grids of the virtual model and generating a sowing strategy simultaneously; The growth characteristics of the target planting material are obtained to generate characteristic data. The specific contents of simulating the growth of the planting material in the virtual model and recording the growth of the virtual planting material in different cycles according to the characteristic data combined with the characteristic factor sequence are as follows: The virtual model is a three-dimensional visualization model, which is internally integrated with a neural network module; The characteristic data include growth environment parameters of the planting material, characteristic data of the planting material and growth result data; The characteristic data is cleaned to remove outliers and normalized to obtain sample characteristic data; The characteristic factor sequence was analyzed to obtain the influencing characteristics of planting materials; The sample characteristic data and the characteristics affecting the planting materials are input into the neural network module, and the neural network module learns the growth pattern and law of the planting materials to obtain output data; The output data is brought into a three-dimensional visualization model to simulate the growth of planting materials in different blocks generated in different grids; Color rendering is performed according to the height of vegetation, and the height of vegetation is displayed through different color differences; Points are confirmed and calibrated according to the degree of vegetation sparseness.

2. According to claim 1, a pumped storage power station slope ecological restoration method based on a near-nature concept is characterized in that: The specific contents of obtaining the geomorphic characteristics of the slope of the current pumped storage power station and analyzing the characteristic factor sequence in S1 are as follows: A characteristic factor table is preset, and the characteristic factor table is composed of characteristic factor sub-tables; The characteristic factor sub-table includes a slope factor sub-table, a slope shape factor sub-table, a geological factor sub-table, a lithology factor sub-table, a soil factor sub-table and a hydrological factor sub-table; The slope factor is divided into gradients according to the difficulty of repair to generate a slope factor sub-table; The slope factor is divided according to the appearance to generate a slope factor sub-table; Generate a geological factor category table based on the existence of faults and fracture zones on the slopes of pumped storage power stations; Generate a geological factor degree table based on the number of faults and fracture zones on the slope of the pumped storage power station; The geological factor category table and the geological factor degree table are matched to generate a geological factor sub-table; Generate a lithology factor sub-table based on the weathering resistance and mechanical properties of the rock; Generate soil factor sub-tables according to soil types and different soil properties; Generate a sub-table of hydrological factors based on the presence of groundwater and its dynamic changes; Conduct an overall analysis of the current landform characteristics to obtain the overall characteristic factors of the current landform characteristics, confirm the table position of the current overall characteristic factors in the characteristic factor table, and generate the overall sequence of the current characteristic factors according to the table position; The slope of the current pumped storage power station is divided into blocks, and the geomorphic features of different blocks are analyzed to obtain the block characteristic factors of the current geomorphic features. The table position of the current block characteristic factors is confirmed in the characteristic factor table, and the current characteristic factor block sequence is generated according to the table position.

3. According to claim 1, a pumped storage power station slope ecological restoration method based on a near-nature concept is characterized in that: The virtual model in S1 is a three-dimensional model, and the virtual model restores the slope of the pumped storage power station in proportion; The virtual model is meshed according to the current block division of the pumped storage power station slope; Mark the current feature factor block sequence in the grid respectively.

4. The method for ecological restoration of a pumped storage power station slope based on a near-nature concept according to claim 1 is characterized in that: The specific contents of the neural network module include: The dataset is divided into training set, validation set and test set, with the ratio of 60% training set, 20% validation set and 20% test set; Determine the number of neurons in the input layer according to the type of implant material characteristic data; Calculate the number of groups of planting material characteristic data, and take one tenth of the value as the number of hidden layers; Set the softmax function as the activation function.

5. A method for ecological restoration of slopes of pumped storage power stations based on a near-nature concept according to claim 4, characterized in that: The current growth of planting materials on the slope of the pumped storage power station is collected, and the current growth of planting materials is compared with the growth of virtual planting materials in the same period. The specific content of the ecological restoration evaluation of the slope of the pumped storage power station is obtained as follows: According to the growth height range of plants of different families, the corresponding heights of the grids are divided into gradients; Obtaining color difference values ​​of different grids under different gradients, presetting a standard difference value range, and defining a grid whose color difference value is outside the standard difference value range as a first unqualified grid; Obtain the vegetation sparseness calibration result, count the calibration points of different grids, preset a standard calibration point number range, and define the grids with calibration points outside the standard calibration point number range as the second unqualified grid; Configure the first influence coefficient according to the influence of different grid heights on the overall model; Configure the second influence coefficient according to the influence of different grid sparsity levels on the overall model; The number of the first unqualified grids and the second unqualified grids under different gradients is obtained and combined with the degree of impact to calculate the evaluation value of the slope ecological restoration of the pumped-storage power station.

6. A method for ecological restoration of slopes of pumped storage power stations based on a near-nature concept according to claim 5, characterized in that: The expression of the evaluation value of the slope ecological restoration of the pumped storage power station is: ； in, is the first influence coefficient, is the second influence coefficient, is the color difference value, is the number of calibration points, is the number of the first unqualified grids, is the number of the second unqualified grids, N is the total number of grids, and m is the different gradients.

7. A pumped storage power station slope ecological restoration system based on the concept of near nature, characterized in that: include: Data acquisition module: obtain the geomorphic features of the current pumped storage power station slope and analyze to obtain the characteristic factor sequence, obtain the geographical location of the pumped storage power station slope and generate a virtual model in proportion; Strategy generation module: There is a planting material library preset. According to the current demand and characteristic factor sequence, the planting materials are screened in the planting material library to obtain the target planting materials, mark the target planting materials in the virtual model and generate a sowing strategy; The specific contents of screening planting materials in the planting material library according to the current demand and characteristic factor sequence to obtain target planting materials and generate sowing strategies are as follows: The planting material library includes a number of planting materials, and correspondingly marks the growth environment; Analyze the growth environment of the slope of the pumped storage power station according to the overall sequence of current characteristic factors, and match the first target planting material; Screening the first target planting material according to the current characteristic factor block sequence to obtain the second target planting material; Marking the second target planting materials in different grids of the virtual model and generating a sowing strategy simultaneously; Simulation display module: obtain the growth characteristics of the target planting material to generate characteristic data, simulate the growth of the planting material in the virtual model based on the characteristic data and the characteristic factor sequence, and record the growth of the virtual planting material in different cycles; The growth characteristics of the target planting material are obtained to generate characteristic data. The specific contents of simulating the growth of the planting material in the virtual model and recording the growth of the virtual planting material in different cycles according to the characteristic data combined with the characteristic factor sequence are as follows: The virtual model is a three-dimensional visualization model, which is internally integrated with a neural network module; The characteristic data include growth environment parameters of the planting material, characteristic data of the planting material and growth result data; The characteristic data is cleaned to remove outliers and normalized to obtain sample characteristic data; The characteristic factor sequence was analyzed to obtain the influencing characteristics of planting materials; The sample characteristic data and the characteristics affecting the planting materials are input into the neural network module, and the neural network module learns the growth pattern and law of the planting materials to obtain output data; The output data is brought into a three-dimensional visualization model to simulate the growth of planting materials in different blocks generated in different grids; Color rendering is performed according to the height of vegetation, and the height of vegetation is displayed through different color differences; Confirm and calibrate points based on vegetation sparseness; Restoration evaluation module: collect the current growth of planting materials on the slope of the pumped-storage power station, compare and analyze the current growth of planting materials with the growth of virtual planting materials in the same period to obtain the ecological restoration evaluation of the slope of the pumped-storage power station; Correction and adjustment module: adjust the seeding strategy and carry out immediate remediation according to the evaluation of the ecological restoration of the slope of the pumped storage power station.

Images