A method, device and system for evaluating the ecological restoration effect of a steep bare rock mine slope

Abstract

The present application provides a kind of abrupt bare rock slope ecological restoration effect evaluation method, device and system, the method comprises: based on abrupt bare rock mine slope ecological restoration after field investigation obtains abrupt bare rock mine slope ecological restoration related data;With evaluation target, determine the evaluation index corresponding to different evaluation levels in the abrupt bare rock slope ecological restoration effect evaluation system and establish evaluation model;With the data collected, the corresponding weight value of the index corresponding to different evaluation levels in the abrupt bare rock slope ecological restoration effect evaluation system is determined;The closeness to ideal solution is calculated by combining the evaluation index evaluation value and the weight value of each evaluation index, and the abrupt bare rock slope ecological restoration effect evaluation result is obtained.The method can realize the rapid evaluation of abrupt bare rock slope ecological restoration effect.

Description

Technical Field

[0001] This invention relates to the field of mine ecological restoration technology, and in particular to a method, device and system for evaluating the ecological restoration effect of steep bare rock mine slopes. Background Technology

[0002] Mining damages the vegetation of the original ecosystem. During mining, the original soil layer and rock mass are excavated, resulting in many steep, exposed rock slopes within the excavation area. The primary goal of ecological restoration of steep, exposed rock slopes is to mitigate potential geological hazards. Secondly, it involves constructing a soil layer on the slope, and finally, using vegetation reconstruction techniques and diverse planting methods to restore vegetation. Due to the complex and diverse characteristics of steep, exposed rock slopes, such as slope gradient, lithology, and rock weathering, the restoration difficulty is significantly increased compared to ordinary slopes. Furthermore, the ecological restoration effect varies depending on the ecological restoration techniques used.

[0003] Currently, there are numerous ecological restoration technologies for steep bare rock slopes, and the restoration effects of different technologies vary. Previous evaluations of slope ecological restoration effects have mostly focused on ordinary slopes after mining operations. However, steep bare rock slopes present significant challenges in restoration, including high elevation, low water retention, difficulty in topsoil covering, limited soil thickness, and difficulty in vegetation growth. Existing evaluation index systems for slope ecological restoration are insufficient to address these challenges. Therefore, establishing a corresponding evaluation system based on field investigations and indoor experimental analysis results has strong practical significance and application value for evaluating the ecological restoration effects of steep bare rock mining slopes.

[0004] The effectiveness of ecological restoration of steep bare rock mine slopes is influenced by multiple factors, and there is currently no definitive evaluation index or system for assessing the effectiveness of such restoration. Therefore, this study aims to address the shortcomings of existing methods for evaluating the effectiveness of ecological restoration of steep bare rock mine slopes by proposing a new method based on field investigation and multi-factor analysis. Summary of the Invention

[0005] The purpose of this invention is to provide a method, device, and system for evaluating the ecological restoration effect of steep bare rock mine slopes. Through on-site investigation, indoor experiments, and the establishment of an evaluation model, the invention achieves the effect of rapid evaluation of the ecological restoration effect of steep bare rock mine slopes.

[0006] To achieve the above objectives / to solve the above technical problems, the present invention is implemented using the following technical solution.

[0007] In a first aspect, the present invention provides a method for evaluating the ecological restoration effect of steep bare rock mine slopes, including:

[0008] Step S1. Obtain restoration status data: Obtain restoration status data of the indicator layer evaluation indicators for the ecological restoration effect of steep bare rock mine slopes; establish an evaluation model including the target layer, criterion layer and indicator layer;

[0009] Step S2. Determine the evaluation level of the indicators: Based on the current restoration status data of the evaluation indicators of the indicator layer, and combined with the preset evaluation indicator level range of the ecological restoration effect of steep bare rock mine slopes, determine the evaluation level corresponding to each indicator layer.

[0010] Step S3. Calculate the weights of the evaluation indicators: Divide the hierarchical relationship between the evaluation indicators of the criterion layer and the evaluation indicators of the indicator layer, set the importance discrimination matrix between the evaluation indicators of the criterion layer and between the evaluation indicators of the indicator layer corresponding to each criterion layer, and perform a consistency test on the importance discrimination matrix. If the consistency ratio meets the set parameter requirements, then determine the weights of the evaluation indicators of the criterion layer and the weights corresponding to the evaluation indicators of each indicator layer.

[0011] Step S4. Constructing the normalization and weighting matrix: Based on the current status data of the evaluation indicators at the indicator layer, the normalization method is used to process the data to obtain the normalized data matrix of the evaluation indicators; combined with the weights of the evaluation indicators at each indicator layer determined in step S3, the weighted decision matrix is ​​calculated.

[0012] Step S5. Obtain the ideal solution of the index: Based on the weighted decision matrix, obtain the positive and negative ideal solutions corresponding to the precise number index, the interval number index, and the triangular fuzzy number index in the index layer evaluation index respectively;

[0013] Step S6. Determine the final evaluation result: Based on the positive ideal solution and the negative ideal solution, calculate the Euclidean distance from each indicator layer of the evaluation object to the positive ideal solution and the negative ideal solution respectively; calculate the closeness of the evaluation object to the ideal solution based on the Euclidean distance, compare the closeness with the closeness threshold corresponding to the preset evaluation level, and determine the final evaluation result of the ecological restoration effect of the steep bare rock mine slope.

[0014] In some embodiments of the first aspect, in step S2, the evaluation level is divided into five levels, namely, excellent, good, average, and poor. The evaluation level is determined by judging the preset evaluation index level range in which the restoration status data of each index layer is located, and then determining the evaluation level of that index layer evaluation index accordingly.

[0015] In some embodiments of the first aspect, in step S3, the hierarchical relationship between the criterion-level evaluation indicators and the indicator-level evaluation indicators is as follows: each criterion-level evaluation indicator corresponds to several indicator-level evaluation indicators with the same characteristics, and all indicator-level evaluation indicators belong to a unique corresponding criterion-level evaluation indicator.

[0016] In some embodiments of the first aspect, step S3, including the setting of the importance discrimination matrix, consistency verification, and weight determination, specifically includes the following:

[0017] Step 4.1 Determining the weights of evaluation indicators at the criterion level:

[0018] Define the importance judgment matrix of the evaluation indicators at the criterion level. : ;

[0019] in: This is a matrix for judging the importance of evaluation indicators at the criterion level. The importance judgment matrix of the evaluation indicators at the criterion level Order; Evaluation indicators for the criteria layer Relative Quasi-Layer Evaluation Index The importance of each pair of values ​​is compared, and the following conditions are met: , , The number of evaluation indicators at the criteria level;

[0020] based on Calculate the weight vector of evaluation indicators at the criterion level. and normalized weights : ; ;

[0021] in, The number of evaluation indicators corresponding to the criterion layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the criteria layer when calculating the weights of the evaluation indicators;

[0022] Step 4.2 Consistency check of the importance judgment matrix of the criterion layer evaluation indicators:

[0023] calculate The largest eigenvalue : ;

[0024] Calculate the consistency index : ; Calculate the consistency ratio : ;

[0025] in, This serves as a consistency index for the importance judgment matrix of each evaluation indicator at the criterion level. The largest eigenvalue of the evaluation index importance discrimination matrix of the criterion layer. The order of the evaluation index importance judgment matrix for the criterion layer; The consistency ratio of the importance judgment matrix of the criteria layer evaluation indicators; The average consistency index of the importance judgment matrix of the criteria layer evaluation indicators, when When the importance discrimination matrix is ​​consistent, then the importance discrimination matrix is ​​consistent; if In such cases, the importance discrimination matrix needs to be reset;

[0026] Step 4.3 Determining the weights of evaluation indicators at the indicator layer:

[0027] Set up an indicator layer to evaluate the importance of the indicators. : ;

[0028] based on Calculate the weight vector of evaluation indicators at the indicator layer. and normalized weights : ; ;

[0029] in, This is a matrix for judging the importance of indicators at the indicator level. The order of the matrix used to determine the importance of indicators at the indicator level; This represents the number of evaluation indicators at the corresponding indicator layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the indicator layer when calculating the weight of the evaluation indicators; Evaluation indicators for the indicator layer relative indicator layer evaluation indicators The importance of pairwise comparison values; , , The number of evaluation indicators at the indicator level.

[0030] Step 4.4 Consistency check of the importance judgment matrix of the indicator layer:

[0031] calculate The largest eigenvalue : ; Calculate the consistency index : ; Calculate the consistency ratio : .

[0032] in, As a consistency indicator, The largest eigenvalue of the evaluation index importance discrimination matrix of the index layer. The order of the judgment matrix for the importance of indicators at the indicator level. The consistency ratio of the importance judgment matrix of each evaluation indicator in the indicator layer; The average consistency index of the indicator importance discrimination matrix is ​​used to evaluate the indicator layer. When the importance discrimination matrix is ​​consistent, then the importance discrimination matrix is ​​consistent; if In such cases, the importance discrimination matrix needs to be reset.

[0033] In some embodiments of the first aspect, step S4 involves obtaining a normalized data matrix and a weighted decision matrix for the evaluation indicators based on the evaluation indicator data, the normalization method, and the corresponding weights. Specifically, this includes:

[0034] Step 5.1 Obtain the initial data matrix of evaluation indicators : ;

[0035] in, For the initial data matrix, The evaluation index data are for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. This represents the number of steep, bare rock mine slopes that have been repaired.

[0036] Step 5.2 Initial data matrix Perform normalization processing to obtain the evaluation index normalization matrix. :

[0037] in, For normalized data matrices, This is the normalized evaluation index data for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. The number of steep, bare rock mine slopes that have been repaired; based on the type of evaluation index in the index layer, the corresponding normalization method is adopted, specifically including:

[0038] Step 5.2.1 The evaluation index is a precise numerical index (denoted as...). Normalization of )

[0039] The normalized expression for extremely large data metrics is:

[0040] The normalized expression for extremely small data metrics is:

[0041] The normalized expression for intermediate data metrics is: ; ; in, For precise numerical indicators, the values ​​have been normalized. For precise numerical values, The intermediate evaluation index data approaches the optimal value; The number of targets to be evaluated;

[0042] Step 5.2.2 The evaluation index is the interval number index ( The normalized expression for ) is:

[0043] in, This is the normalized value of the lower bound of the interval number. This is the normalized value of the upper bound of the interval number; The lower bound of the interval number. This is the upper bound of the interval number.

[0044] The evaluation index is the triangular fuzzy number index (denoted as ). The normalized expression for ) is:

[0045] in, This is the normalized value of the lower bound of the triangular fuzzy number. This represents the normalized value in the triangular fuzzy number. This is the normalized value of the upper bound of the triangular fuzzy number; This is the lower bound of the triangular fuzzy number. The median of the triangular fuzzy number. This is the upper bound of the triangular fuzzy number.

[0046] Step 5.3 Obtain the weighted decision matrix of evaluation index data : ;

[0047] in, For a weighted decision matrix, The overall weight of each evaluation indicator, For normalized matrix data, ;

[0048] In some embodiments of the first aspect, step S5, obtaining the ideal solution for the evaluation indicators of the indicator layer based on the weighted decision matrix of the indicator layer evaluation indicators, specifically includes: ; ;

[0049] in, For the positive ideal solution of the evaluation index, The negative ideal solution for the evaluation index; For the precise numerical evaluation index, the positive ideal solution is... For precise numerical evaluation indicators, the negative ideal solution is used. For interval number evaluation index, the positive ideal solution is... The interval number evaluation index is the negative ideal solution; The positive ideal solution for the triangular fuzzy number evaluation index. The negative ideal solution is the triangular fuzzy number evaluation index.

[0050] Step 6.1 Obtaining the ideal solution with precise numerical indices:

[0051] The positive ideal solution of the precise numerical index With negative ideal solution Specifically, it includes:

[0052] in, The evaluation indicators within the weighted decision matrix are precise numerical values. The number of targets to be evaluated. The number of evaluation indicators;

[0053] Step 6.2 Obtaining the ideal solution for the interval number index:

[0054] Positive ideal solution of interval number index With negative ideal solution Specifically, it includes:

[0055] in, The evaluation index within the weighted decision matrix is ​​the lower bound of the interval number. The evaluation index within the weighted decision matrix is ​​the upper bound of the interval number;

[0056] Step 6.3 Obtaining the ideal solution for the triangular fuzzy number index:

[0057] Positive ideal solution of triangular fuzzy number index With negative ideal solution Specifically, it includes:

[0058]

[0059] in, The evaluation index within the weighted decision matrix is ​​the lower bound of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the median of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the upper bound of the triangular fuzzy number;

[0060] In some embodiments of the first aspect, in step S6, the Euclidean distance of each evaluation index of the evaluation object and the closeness of the evaluation object to the ideal solution are obtained, and the magnitude of the closeness to the target is compared with the closeness to the evaluation level to obtain the evaluation result of the ecological restoration effect of the steep bare rock mine slope: specifically including the following:

[0061] Step 7.1 Calculate the Euclidean distance between each evaluation index of the evaluation object:

[0062] Euclidean distances of various evaluation objects from the positive ideal solution in the ecological restoration of steep, exposed rock slopes and the Euclidean distance from the negative ideal solution :

[0063] in, The exact numerical evaluation index is the Euclidean distance from the positive ideal solution. The exact numerical evaluation index is the Euclidean distance from the negative ideal solution; The interval number evaluation index is the Euclidean distance from the positive ideal solution. The interval number evaluation index is the Euclidean distance from the negative ideal solution; The triangular fuzzy number evaluation index is the Euclidean distance from the positive ideal solution. The triangular fuzzy number evaluation index is the Euclidean distance from the negative ideal solution; The total number of evaluation indicators for the precise number type. The total number of evaluation indicators of the interval number type. The total number of evaluation indicators for the triangular fuzzy number type;

[0064] Step 7.1.1 Calculation of the exact numerical Euclidean distance:

[0065] The exact numerical index of the Euclidean distance to the positive ideal solution Euclidean distance to the negative ideal solution :

[0066] ; ;

[0067] in, To evaluate the distance of the indicator from the ideal solution of the indicator Euclidean distance, To evaluate the distance of the index from the negative ideal solution of the index The Euclidean distance;

[0068] Step 7.1.2 Calculation of Euclidean distance for the interval index:

[0069] Euclidean distance from the interval number index to the positive ideal solution Euclidean distance to the negative ideal solution :

[0070] ;

[0071] in, This is the upper bound of the positive ideal solution evaluation index for the interval number. This is the lower bound of the positive ideal solution for the interval number evaluation index. This represents the upper bound of the negative ideal solution for the interval number evaluation index. This is the lower bound of the positive ideal solution for the interval number evaluation index;

[0072] 7.1.3 Calculation of Euclidean distance for the triangular fuzzy number index:

[0073] Euclidean distance from the triangular fuzzy number index to the positive ideal solution Euclidean distance to the negative ideal solution :

[0074] in, This represents the upper bound of the positive ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index; This represents the upper bound of the negative ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index;

[0075] Step 7.2 Obtain the closeness between the evaluation object and the ideal solution :

[0076] in, To determine the approximation between the ecological restoration effect and the ideal solution for steep, exposed rock slopes. The Euclidean distance between the ecological restoration of steep, exposed rock slopes and the negative ideal solution. Euclidean distance for ecological restoration of steep, exposed rock slopes and positive ideal solution;

[0077] Step 7.3 Determine the final evaluation result:

[0078] The approximation thresholds corresponding to five evaluation levels—Excellent, Good, Fair, and Poor—are preset, and the calculated... Compare with a threshold, based on The threshold range in which it falls corresponds to the evaluation level of the ecological restoration effect of steep bare rock mine slopes, which is the final evaluation result.

[0079] Secondly, this application provides an apparatus for evaluating the ecological restoration effect of steep bare rock mine slopes. This apparatus is used to implement a method for evaluating the ecological restoration effect of steep bare rock mine slopes, including:

[0080] The restoration module is used to obtain the restoration status data of the indicator layer evaluation indicators of the ecological restoration effect of steep exposed rock mine slopes after ecological restoration.

[0081] The rating module is used to determine the rating level of each rating indicator based on the current restoration status of the rating indicators in the rating layer and the rating range of the rating indicators for the ecological restoration effect of steep exposed rock mine slopes.

[0082] The weighting module is used to divide the hierarchical relationship between the evaluation indicators of the criterion layer and the indicator layer, set the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer, and perform a consistency check on the discrimination matrix: if the consistency ratio of the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer both meet the set parameters, then the corresponding weights of each evaluation indicator of the criterion layer and the indicator layer are obtained.

[0083] The matrix module is used to normalize the current status data of the evaluation indicators at the indicator layer to obtain a normalized data matrix; combined with the weights output by the weight calculation module, a weighted decision matrix is ​​constructed.

[0084] The calculation module is used to obtain the ideal solution of the evaluation index, the Euclidean distance from the ideal solution, and the closeness to the ideal solution based on the weighted decision matrix of the evaluation index.

[0085] The evaluation module is used to calculate the Euclidean distance and proximity of the evaluation object based on the positive and negative ideal solutions, compare the proximity with a preset threshold, and output the final evaluation result of the ecological restoration effect of steep bare rock mine slope.

[0086] Thirdly, this application provides a system for evaluating the ecological restoration effect of steep bare rock mine slopes, comprising:

[0087] Memory is used to store computer programs and instructions;

[0088] The processor is used to call and execute computer programs and instructions stored in memory to implement all the steps of the method for evaluating the ecological restoration effect of steep bare rock mine slopes.

[0089] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0090] (1) This invention establishes an evaluation model for the ecological restoration effect of repaired steep exposed rock slopes, determines the evaluation indicators affecting the evaluation of the ecological restoration effect of repaired steep exposed rock slopes, clarifies the quantitative conversion standard and weight calculation method of linguistic evaluation indicators, determines the importance of each evaluation indicator, and realizes the transformation of evaluation indicator data from qualitative evaluation to quantitative data by combining the normalization methods of precise numbers, interval numbers and triangular fuzzy numbers. Based on the calculation of ideal solutions of different evaluation indicators, the calculation of Euclidean distance from the ideal solution and the corresponding closeness calculation, the qualitative analysis and quantitative evaluation of the ecological restoration effect of repaired steep exposed rock slopes are combined, and the evaluation model is specifically applied to the evaluation of the ecological restoration effect of actual repaired steep exposed rock slopes. This method can not only realize the rapid evaluation of the ecological restoration effect of repaired steep exposed rock slopes, but also make evaluation judgments on the ecological restoration effect of mines within and outside different ecological restoration effect levels;

[0091] (2) Based on field investigation, this invention has determined a method for collecting data on vegetation communities, soil, and slope system stability of restored steep exposed rock slopes. In this way, a multi-level evaluation system for the ecological restoration effect of restored steep exposed rock slopes is established. This system can quickly evaluate the ecological restoration effect of restored steep exposed rock slopes, has strong adaptability, and is suitable for large-scale application. Attached Figure Description

[0092] Figure 1 A flowchart illustrating the method for evaluating the ecological restoration effect of steep bare rock slopes provided in the embodiments of this application;

[0093] Figure 2 A schematic diagram of a five-point soil sampling method provided for embodiments of this application;

[0094] Figure 3 A schematic diagram of the evaluation model for the method of evaluating the ecological restoration effect of steep bare rock slopes provided in the embodiments of this application; Detailed Implementation

[0095] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0096] The term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0097] Please see Figure 1 and Figure 2 , Figure 1 A flowchart illustrating the method for evaluating the ecological restoration effect of steep bare rock slopes provided in the embodiments of this application. Figure 2 A schematic diagram of the five-point soil sampling method provided in the embodiments of this application. Embodiments of this application provide a method for evaluating the ecological restoration effect of a repaired steep, exposed rock slope, including:

[0098] Step S1: Based on the results of the on-site investigation of the restored steep exposed rock slopes, clarify the current stability status, soil status, and vegetation restoration status of different restored steep exposed rock slope systems, and obtain relevant data for the mine restoration area, including:

[0099] Step S11: Obtain the current status of stability restoration of the repaired steep exposed rock slope system, including: slope instability area, damage to the maintenance system, slope landscape harmony, and restoration period;

[0100] The slope instability area C1 is the ratio of the area of ​​local unstable failure of the slope to the total area of ​​the slope.

[0101] C2 refers to the damage to the slope ecological maintenance system;

[0102] Slope landscape harmony C3 refers to the degree of harmony between the ecological restoration of the slope and the surrounding environment.

[0103] The restoration period C4 is the difference between the present time and the time when the ecological restoration of the steep bare rock slope was completed;

[0104] Step S12: Obtain the current status of the soil layer on the repaired steep exposed rock slope, including soil type, and collect soil samples;

[0105] Soil types include gravelly, sandy, sandy loam, loam, and clayey;

[0106] Please see Figure 2 Soil sampling requirements include: collecting samples at depths of 0-10cm and 10-20cm within the quadrat using the five-point sampling method, with each sample weighing approximately 500-1000g;

[0107] The soil pH value C5 was obtained by potentiometric method (HJ962-2018).

[0108] Soil organic matter content (C6) was determined using the potassium dichromate-concentrated sulfuric acid external heating method.

[0109] The total nitrogen content (C7) of the soil was determined using a fully automated Kjeldahl nitrogen analyzer.

[0110] The available phosphorus content (C8) in the soil was determined by ultraviolet spectrophotometry.

[0111] The available potassium content (C9) in the soil was determined using a flame photometer.

[0112] Soil moisture content C 10 The determination was performed using the drying method;

[0113] Step S13: Obtain the current status of vegetation restoration on steep, bare rock slopes, including: vegetation coverage per unit area, vegetation slope connectivity, number of vegetation species, and vegetation community uniformity.

[0114] Vegetation coverage per unit area C 11 The ratio of the vertical projection area S1 of vegetation per unit area of ​​the restored mine to the unit area S2 of the restored mine slope is obtained as follows:

[0115] Vegetated slope connectivity C 12 The ratio of the vegetation cover area S3 to the restored mine slope area S4 is obtained as follows:

[0116] Number of vegetation species C 13 The number of vegetation species on the restored steep bare rock slope;

[0117] vegetation community evenness C 14 This indicates the uniformity of vegetation community distribution on the restored steep bare rock slope.

[0118] Please see Figure 1 and Figure 3 , Figure 3 A schematic diagram of the evaluation model for the method of evaluating the ecological restoration effect of steep bare rock slopes provided in the embodiments of this application.

[0119] S2: Based on the evaluation objectives and the current state of restoration, determine the evaluation indicators corresponding to different evaluation levels within the evaluation objective system, specifically including:

[0120] S21: The evaluation levels are divided into: target level, quasi-measurement level, and indicator level;

[0121] Based on the obtained restoration status data, the evaluation index for the target layer is: the ecological restoration effect of the restored steep exposed rock slope;

[0122] The slope system stability evaluation index, soil evaluation index, and vegetation community evaluation index were determined as the criterion layer evaluation indexes.

[0123] The evaluation indicators for the indicator layer are determined as follows: slope instability area, damage to the maintenance system, slope landscape harmony, restoration period, soil pH value, soil organic matter content, soil total nitrogen content, soil available phosphorus content, soil available potassium content, soil moisture content, vegetation coverage per unit area, vegetation slope connectivity, number of vegetation species, and vegetation community evenness.

[0124] S22: Establish a set of evaluation indicators: ; ; ; ;

[0125] in, B1, B2, and B3 are the evaluation index sets for the target layer, respectively, representing the slope system stability evaluation index set, soil evaluation index set, and vegetation community evaluation index set. B1, B2, and B3 are also the evaluation index sets for the criterion layer. C1 represents the slope instability area, C2 represents the damage status of the maintenance system, C3 represents the slope landscape harmony, C4 represents the restoration period, C5 represents the soil pH value, C6 represents the soil organic matter content, C7 represents the soil total nitrogen content, C8 represents the soil available phosphorus content, and C9 represents the soil available potassium content. 10 For soil moisture content, C 11 For vegetation cover per unit area, C 12 For vegetation slope connectivity, C 13 For the number of vegetation species, C 14 To represent the evenness of the vegetation community, C1-C 14 For evaluation indicators at the indicator level;

[0126] S3: Obtain the corresponding weight values ​​for each of the evaluation indicators of the ecological restoration effect of steep exposed rock slopes, specifically including:

[0127] S31: Determine the evaluation level of the evaluation indicators at the indicator layer based on the current restoration status of the evaluation indicators at the indicator layer and the evaluation level range of the ecological restoration effect evaluation indicators.

[0128] Based on the current restoration status of the indicator layer evaluation indicators, the corresponding ecological restoration effect evaluation indicator level range is defined, and the evaluation level of each indicator layer evaluation indicator is determined. The evaluation levels include: excellent, good, fair, average, and poor.

[0129] The evaluation index levels for the ecological restoration effect of steep, exposed rock slopes are shown in Table 1 below:

[0130] Table 1 Evaluation Index Ranges for Ecological Restoration Effects of Steep, Exposed Rock Slopes

[0131] Note: When the slope instability area C1 is the area without slope instability, the value is taken as 1% for ease of calculation.

[0132] S32: Set the importance discrimination matrix of the criterion-level evaluation indicators and the indicator-level evaluation indicators, and obtain the corresponding weights of each criterion-level evaluation indicator and the indicator-level evaluation indicator;

[0133] The importance judgment matrix of the criterion-level evaluation indicators is used to obtain the weights of each evaluation indicator in the criterion-level layer. ; ;

[0134] in: This is a matrix for judging the importance of evaluation indicators at the criterion level. The order of the importance judgment matrix for the evaluation indicators at the criterion level; The number of evaluation indicators corresponding to the criterion layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the criteria layer when calculating the weights of the evaluation indicators; Evaluation indicators for the criteria layer Relative Quasi-Layer Evaluation Index The importance of pairwise comparison values; , , The number of evaluation indicators at the criteria level;

[0135] The importance judgment matrix of the indicator layer is used to obtain the weights of each indicator in the indicator layer: ;

[0136] in, This is a matrix for judging the importance of indicators at the indicator level. The order of the matrix used to determine the importance of indicators at the indicator level; This represents the number of evaluation indicators at the corresponding indicator layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the indicator layer when calculating the weight of the evaluation indicators; Evaluation indicators for the indicator layer relative indicator layer evaluation indicators The importance of pairwise comparison values; , , The number of evaluation indicators at the indicator layer;

[0137] The determination matrix scale and its meaning are shown in Table 2 below:

[0138] Table 2. Judgment Matrix Scale and Its Meaning

[0139] The above factors are judged by using two indicator-level evaluation indicators or criterion-level evaluation indicators of the same evaluation level.

[0140] S34: Determine whether the consistency ratio of the importance judgment matrix for the criterion-level evaluation indicators and the indicator-level evaluation indicators both meet the set parameters, specifically including:

[0141] Consistency index of the importance judgment matrix of the criterion-level evaluation indicators : ;

[0142] in, This serves as a consistency index for the importance judgment matrix of each evaluation indicator at the criterion level. The largest eigenvalue of the evaluation index importance discrimination matrix of the criterion layer. The order of the evaluation index importance judgment matrix for the criterion layer;

[0143] The consistency ratio of the importance discrimination matrix of the evaluation indicators of the criterion layer is obtained. :

[0144] in, The consistency ratio of the importance judgment matrix of the criteria layer evaluation indicators; The average consistency index of the importance judgment matrix of the criteria layer evaluation indicators, when When the importance discrimination matrix is ​​consistent, then the importance discrimination matrix is ​​consistent; if In such cases, the importance discrimination matrix needs to be reset;

[0145] Consistency index of the importance judgment matrix of indicator layer evaluation indicators : ;

[0146] in, As a consistency indicator, The largest eigenvalue of the evaluation index importance discrimination matrix of the index layer. The order of the judgment matrix for evaluating the importance of indicators at the indicator level;

[0147] Obtain the consistency ratio of the importance discrimination matrix of each evaluation indicator in the indicator layer. : ;

[0148] in, The consistency ratio of the importance judgment matrix of each evaluation indicator in the indicator layer; The average consistency index of the indicator importance discrimination matrix is ​​used to evaluate the indicator layer. When the importance discrimination matrix is ​​consistent, then the importance discrimination matrix is ​​consistent; if In such cases, the importance discrimination matrix needs to be reset;

[0149] S4: Transform the data, interval numbers, and triangular fuzzy numbers of the evaluation indicators at the criterion layer to obtain the initial data matrix of the evaluation indicators and perform normalization processing. The specific steps to obtain the normalized data matrix include:

[0150] S41: Transformation of linguistic evaluation indicators into triangular fuzzy numbers. The transformation of linguistic evaluation indicators into triangular fuzzy numbers is shown in Table 3, specifically including:

[0151] Table 3. Language-based evaluation indicators and their corresponding triangular fuzzy number transformations.

[0152]

[0153] S42: Normalization of initial data for evaluation metrics to obtain the normalization matrix, specifically including:

[0154] Obtain the initial data matrix of evaluation indicators :

[0155] in, For the initial data matrix, The evaluation index data are for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. This represents the number of steep, bare rock mine slopes that have been repaired.

[0156] Obtain the normalized matrix of evaluation indicators : ;

[0157] in, For normalized data matrices, This is the normalized evaluation index data for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. This represents the number of steep, bare rock mine slopes that have been repaired.

[0158] Normalization of initial data for obtaining precise numerical evaluation metrics:

[0159] The normalized expression for extremely large evaluation index data is: ;

[0160] The normalized expression for extremely small evaluation index data is:

[0161] The normalized expression for intermediate evaluation index data is: ; ; in, For precise numerical indicators, the values ​​have been normalized. For precise numerical values, The intermediate evaluation index data is the optimal value that the intermediate evaluation index data approaches. When normalizing the intermediate evaluation index data, the intermediate data is first converted into a very large type, and then the very large type normalization method is applied.

[0162] Normalization of initial data for the interval number evaluation index: ;

[0163] in, This is the normalized value of the lower bound of the interval number. This is the normalized value of the upper bound of the interval number; The lower bound of the interval number. This is the upper bound of the interval number;

[0164] Normalization of initial data for the triangular fuzzy number evaluation index: ;

[0165] in, This is the normalized value of the lower bound of the triangular fuzzy number. This represents the normalized value in the triangular fuzzy number. This is the normalized value of the upper bound of the triangular fuzzy number; This is the lower bound of the triangular fuzzy number. The median of the triangular fuzzy number. This is the upper bound of the triangular fuzzy number;

[0166] S5: Set the weights of each evaluation indicator and the normalized data matrix to obtain the weighted decision matrix of the evaluation indicators. This specifically includes:

[0167] Obtain the weighted decision matrix of evaluation index data : ; ;

[0168] in, For a weighted decision matrix, The overall weight of each evaluation indicator, For normalized matrix data, ;

[0169] S6: Based on the weighted decision matrix of the evaluation indicators, obtain the ideal solution of the evaluation indicators and the Euclidean distance from the ideal solution, specifically including:

[0170] S61: Obtaining the ideal solution for the evaluation indicators based on the weighted decision matrix of the evaluation indicators specifically includes:

[0171] Obtaining the positive and negative ideal solutions for the evaluation indicators specifically includes: ;

[0172] in, For the precise numerical evaluation index, the positive ideal solution is... For precise numerical evaluation indicators, the negative ideal solution is used. For interval number evaluation index, the positive ideal solution is... The interval number evaluation index is the negative ideal solution; The positive ideal solution for the triangular fuzzy number evaluation index. The negative ideal solution is the triangular fuzzy number evaluation index.

[0173] Positive ideal solution of precise numerical index With negative ideal solution Specifically, it includes: ;

[0174] in, The evaluation indicators within the weighted decision matrix are precise numerical values. The number of targets to be evaluated. The number of evaluation indicators;

[0175] Positive ideal solution of interval number index With negative ideal solution Specifically, it includes: ;

[0176] in, The evaluation index within the weighted decision matrix is ​​the lower bound of the interval number. The evaluation index within the weighted decision matrix is ​​the upper bound of the interval number;

[0177] Positive ideal solution of triangular fuzzy number index With negative ideal solution Specifically, it includes: ;

[0178] in, The evaluation index within the weighted decision matrix is ​​the lower bound of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the median of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the upper bound of the triangular fuzzy number;

[0179] S62: Based on the weighted decision matrix of the evaluation indicators, the Euclidean distance from the evaluation indicators to the ideal solution is obtained, specifically including:

[0180] Obtain the Euclidean distances from the positive ideal solution to each evaluation object in the ecological restoration of steep, exposed rock slopes. and the Euclidean distance from the negative ideal solution : ;

[0181] in, The evaluation index is the Euclidean distance from the positive ideal solution. The evaluation index is the Euclidean distance from the negative ideal solution. The total number of evaluation indicators for the precise number type. The total number of evaluation indicators of the interval number type. The total number of evaluation indicators for the triangular fuzzy number type;

[0182] The exact numerical index of the Euclidean distance to the positive ideal solution Euclidean distance to the negative ideal solution : ; ;

[0183] in, To evaluate the distance of the indicator from the ideal solution of the indicator Euclidean distance, To evaluate the distance of the index from the negative ideal solution of the index The Euclidean distance;

[0184] Euclidean distance from the interval number index to the positive ideal solution Euclidean distance to the negative ideal solution : ;

[0185] in, This is the upper bound of the positive ideal solution evaluation index for the interval number. This is the lower bound of the positive ideal solution for the interval number evaluation index. This represents the upper bound of the negative ideal solution for the interval number evaluation index. This is the lower bound of the positive ideal solution for the interval number evaluation index;

[0186] Euclidean distance from the triangular fuzzy number index to the positive ideal solution Euclidean distance to the negative ideal solution : ;

[0187] in, This represents the upper bound of the positive ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index; This represents the upper bound of the negative ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index;

[0188] S7: Based on the ideal solutions of each evaluation index and their Euclidean distances from the ideal solutions, obtain the degree of closeness of the evaluation target to the ideal solution. Specifically, it includes: ;

[0189] in, To determine the approximation between the ecological restoration effect and the ideal solution for steep, exposed rock slopes. The Euclidean distance between the ecological restoration of steep, exposed rock slopes and the negative ideal solution. Euclidean distance for ecological restoration of steep, exposed rock slopes and positive ideal solution;

[0190] The following section uses some restored steep bare rock mine slopes as examples to illustrate the above process in detail: Based on the results of field investigations and indoor tests, the evaluation indicators for the ecological restoration effect of restored steep bare rock mine slopes were determined. The specific data are shown in Table 4.

[0191] Table 4. Evaluation Indicators for the Ecological Restoration Effect of Repaired Steep Bare Rock Mine Slopes

[0192] Note: When the slope instability area C1 is the area without slope instability, the value is taken as 1% for ease of calculation.

[0193] The judgment matrix and index weights of evaluation indicators at different levels within the model were calculated, and consistency checks were performed. The specific calculation results are shown in Table 5.

[0194] Table 5 Judgment Matrix and Consistency Test

[0195] The comprehensive weight of each evaluation indicator is obtained by combining the weights of the evaluation indicators in the criterion layer above. The comprehensive weights of the evaluation indicators are shown in Table 6.

[0196] Table 6. Overall Weight of Evaluation Indicators

[0197] Each evaluation level and the evaluated mine are grouped into evaluation objects, and the evaluation indicators are weighted according to the criteria layer and the indicator layer. and Calculate the overall weight The normalized data matrix and the evaluation index are combined to obtain the weighted decision matrix, which is shown in Table 7.

[0198] Table 7 Weighted Decision Matrix of Ecological Restoration Effect Evaluation Indicators for Steep Exposed Rock Slopes

[0199] The ideal solutions for each evaluation indicator are calculated using the weighted decision matrix of the evaluation indicators. The results are as follows:

[0200] The ideal solution A * =[0.006, (0.032, 0.050, 0.073), (0.012, 0.019, 0.029), 0.058, 0.008, 0.021, 0.010, 0.027, 0.017, 0.006, (0.042, 0.067), 0.021, (0.012, 0.018, 0.027) 0.069];

[0201] Negative ideal solution A - =[0.000, (0.000, 0.006, 0.022), (0.000, 0.002, 0.009), 0.000, 0.000, 0.000, 0.003, 0.000, 0.003, 0.001, (0.000, 0.020), 0.000, (0.000, 0.002, 0.008) 0.014];

[0202] The corresponding Euclidean distance and proximity were calculated by combining the weighted decision matrix of the evaluation indicators and the ideal solution. The calculation results are shown in Table 8.

[0203] Table 8. Calculation Results of the Proximity of Ecological Restoration Effects on Steep Bare Rock Mine Slopes

[0204] According to the closeness calculation results, the ecological restoration effect of steep bare rock slopes M4 and M6 is between excellent and very excellent, while the ecological restoration effect of steep bare rock slopes M2, M3, M1, and M5 is between good and excellent.

[0205] Embodiments of this application provide an evaluation device for evaluating the ecological restoration effect of steep, exposed rock mine slopes. The evaluation device includes:

[0206] The restoration module is used to obtain the restoration status data of the indicator layer evaluation indicators for the ecological restoration effect of steep exposed rock mine slopes after ecological restoration.

[0207] The rating module is used to determine the rating level corresponding to each rating indicator based on the current restoration status of the rating indicators in the rating layer and the rating range of the rating indicators for the ecological restoration effect of steep exposed rock mine slopes.

[0208] The weighting module is used to define the hierarchical relationship between the evaluation indicators of the criterion layer and the indicator layer, set the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer, and perform a consistency check on the discrimination matrix: if the consistency ratio of the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer both meet the set parameters, then the corresponding weights of each evaluation indicator of the criterion layer and the indicator layer are obtained.

[0209] The matrix module is used to normalize the current status data of the evaluation indicators at the indicator level to obtain a normalized data matrix; combined with the weights output by the weight calculation module, a weighted decision matrix is ​​constructed.

[0210] The calculation module is used to obtain the ideal solution of the evaluation index, the Euclidean distance from the ideal solution, and the closeness to the ideal solution based on the weighted decision matrix of the evaluation index.

[0211] The evaluation module is used to calculate the Euclidean distance and proximity of the evaluation object based on the positive and negative ideal solutions, compare the proximity with a preset threshold, and output the final evaluation result of the ecological restoration effect of steep bare rock mine slope.

[0212] Embodiments of this application provide a system for evaluating the ecological restoration effect of steep bare rock mine slopes, comprising:

[0213] Memory is used to store computer programs and instructions.

[0214] A processor is used to execute computer programs / instructions to implement the steps of the above-described method for evaluating the effectiveness of ecological restoration of steep, exposed rock mine slopes.

[0215] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0216] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0217] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0218] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0219] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for evaluating the ecological restoration effect of steep bare rock mine slopes, characterized in that, include: Step S1. Obtain restoration status data: Obtain restoration status data of the indicator layer evaluation indicators for the ecological restoration effect of steep bare rock mine slopes, and establish an evaluation model including the target layer, criterion layer and indicator layer. Step S2. Determine the evaluation level of the indicators: Based on the restoration status data of the evaluation indicators of the indicator layer, and combined with the preset evaluation index level range of the ecological restoration effect of steep bare rock mine slopes, determine the evaluation level corresponding to each indicator layer. Step S3. Calculate the weights of the evaluation indicators: Divide the hierarchical relationship between the evaluation indicators of the criterion layer and the evaluation indicators of the indicator layer, set the importance discrimination matrix between the evaluation indicators of the criterion layer and between the evaluation indicators of the indicator layer corresponding to each criterion layer, and perform a consistency test on the importance discrimination matrix. If the consistency ratio meets the set parameter requirements, then determine the weights of the evaluation indicators of the criterion layer and the weights corresponding to the evaluation indicators of each indicator layer. Step S4. Constructing a normalization and weighted matrix: Based on the repair status data of the evaluation indicators of the indicator layer, a preset normalization method is used to perform normalization processing to obtain the normalized data matrix of the evaluation indicators; combined with the weights of each evaluation indicator layer determined in step S3, the weighted decision matrix is ​​calculated. Step S5. Obtain the ideal solution of the index: Based on the weighted decision matrix, obtain the positive and negative ideal solutions corresponding to the precise number index, the interval number index, and the triangular fuzzy number index in the index layer evaluation index respectively; Step S6. Determine the final evaluation result: Based on the positive ideal solution and the negative ideal solution, calculate the Euclidean distance from each indicator layer of the evaluation object to the positive ideal solution and the negative ideal solution respectively; calculate the closeness of the evaluation object to the ideal solution based on the Euclidean distance, compare the closeness with the closeness threshold corresponding to the preset evaluation level, and determine the final evaluation result of the ecological restoration effect of the steep bare rock mine slope.

2. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 1, characterized in that, In step S2, the evaluation level is divided into five levels, namely, excellent, good, average, and poor. The evaluation level is determined by judging the preset evaluation index level range in which the restoration status data of each index layer is located, and then determining the evaluation level of that index layer.

3. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 1, characterized in that, In step S3, the hierarchical relationship between the criterion-level evaluation indicators and the indicator-level evaluation indicators is as follows: each criterion-level evaluation indicator corresponds to several indicator-level evaluation indicators with the same characteristics, and all indicator-level evaluation indicators belong to a unique corresponding criterion-level evaluation indicator.

4. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 3, characterized in that, In step S3, the setting, consistency check, and weight determination of the importance discrimination matrix specifically include the following: Step 4.1 Determining the weights of evaluation indicators at the criterion level: Define the importance judgment matrix of the evaluation indicators at the criterion level. : ； in: This is a matrix for judging the importance of evaluation indicators at the criterion level. The importance judgment matrix of the evaluation indicators at the criterion level Order; Evaluation indicators for the criteria layer Relative Quasi-Layer Evaluation Index The importance of each pair of values ​​is compared, and the following conditions are met: , , The number of evaluation indicators at the criteria level; based on Calculate the weight vector of evaluation indicators at the criterion level. and normalized weights : ； ； in, The number of evaluation indicators corresponding to the criterion layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the criteria layer when calculating the weights of the evaluation indicators; Step 4.2 Consistency check of the importance judgment matrix of the criterion layer evaluation indicators: calculate The largest eigenvalue : ； Calculate the consistency index : ； Calculate the consistency ratio : ； in, This serves as a consistency index for the importance judgment matrix of each evaluation indicator at the criterion level. The largest eigenvalue of the evaluation index importance discrimination matrix of the criterion layer. The order of the evaluation index importance judgment matrix for the criterion layer; This is a matrix for judging the importance of evaluation indicators at the criterion level. The consistency ratio of the importance judgment matrix of the criteria layer evaluation indicators; The average consistency index of the importance judgment matrix of the criteria layer evaluation indicators, when When the importance discrimination matrix is ​​consistent, then the importance discrimination matrix is ​​consistent; if In such cases, the importance discrimination matrix needs to be reset; Step 4.3 Determining the weights of evaluation indicators at the indicator layer: Set up an indicator layer to evaluate the importance of the indicators. : ； based on Calculate the weight vector of evaluation indicators at the indicator layer. and normalized weights : ； ； in: This is a matrix for judging the importance of indicators at the indicator level. The order of the matrix used to determine the importance of indicators at the indicator level; This represents the number of evaluation indicators at the corresponding indicator layer when calculating the evaluation indicator weight vector. This refers to the number of evaluation indicators corresponding to the indicator layer when calculating the weight of the evaluation indicators; Evaluation indicators for the indicator layer relative indicator layer evaluation indicators The importance of pairwise comparison values; , , The number of evaluation indicators at the indicator level; Step 4.4 Consistency check of the importance judgment matrix of the indicator layer: calculate The largest eigenvalue : ； Calculate the consistency index : ； Calculate the consistency ratio : ； in, As a consistency indicator, The largest eigenvalue of the evaluation index importance discrimination matrix of the index layer. The order of the judgment matrix for evaluating the importance of indicators at the indicator level; The consistency ratio of the importance judgment matrix of each evaluation indicator in the indicator layer; The average consistency index of the indicator importance discrimination matrix is ​​used to evaluate the indicator layer. when When this is the case, the importance discrimination matrix is ​​consistent; like In such cases, the importance discrimination matrix needs to be reset.

5. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 4, characterized in that, In step S4, the evaluation index normalization data matrix and weighted decision matrix are obtained based on the evaluation index data, normalization method, and corresponding weights at the index layer. Specifically, this includes: Step 5.1 Obtain the initial data matrix of evaluation indicators : ； in, For the initial data matrix, The evaluation index data are for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. This represents the number of steep, bare rock mine slopes that have been repaired. Step 5.2 Initial data matrix Perform normalization processing to obtain the evaluation index normalization matrix. : ； in, For normalized data matrices, This is the normalized evaluation index data for the repaired steep bare rock mine slopes. The number of evaluation indicators at the indicator level. The number of steep, bare rock mine slopes that have been repaired; based on the type of evaluation index in the index layer, the corresponding normalization method is adopted, specifically including: The evaluation index mentioned in step 5.2.1 is a precise numerical index ( Normalization of ) The normalized expression for extremely large data metrics is: ； The normalized expression for extremely small data metrics is: ； The normalized expression for intermediate data metrics is: ； ； in, For precise numerical indicators, the values ​​have been normalized. For precise numerical values, The intermediate evaluation index data approaches the optimal value; The number of targets to be evaluated; The evaluation index mentioned in step 5.2.2 is the interval number index ( The normalized expression for ) is: ； in, The value is the normalized lower bound of the interval number. This is the normalized value of the upper bound of the interval number; The lower bound of the interval number. This is the upper bound of the interval number; The evaluation index is the triangular fuzzy number index (denoted as ). The normalized expression for ) is: ； in, This is the normalized value of the lower bound of the triangular fuzzy number. This represents the normalized value in the triangular fuzzy number. This is the normalized value of the upper bound of the triangular fuzzy number; This is the lower bound of the triangular fuzzy number. The median of the triangular fuzzy number. This is the upper bound of the triangular fuzzy number; The number of evaluation indicators; Step 5.3 Obtain the weighted decision matrix of evaluation index data : ； ； in, For a weighted decision matrix, The overall weight of each evaluation indicator, For normalized matrix data, .

6. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 5, characterized in that, In step S5, the ideal solution for the evaluation indicators at the indicator level is obtained based on the weighted decision matrix of the evaluation indicators at the indicator level, specifically including: ； ； in, For the positive ideal solution of the evaluation index, The negative ideal solution for the evaluation index; For the precise numerical evaluation index, the positive ideal solution is... For precise numerical evaluation indicators, the negative ideal solution is used. For interval number evaluation index, the positive ideal solution is... The interval number evaluation index is the negative ideal solution; The positive ideal solution for the triangular fuzzy number evaluation index. The negative ideal solution is the triangular fuzzy number evaluation index. Step 6.1 Obtaining the ideal solution with precise numerical indices: The positive ideal solution of the aforementioned precise numerical index With negative ideal solution Specifically, it includes: ； in, The evaluation indicators within the weighted decision matrix are precise numerical values. The number of targets to be evaluated; Step 6.2 Obtaining the ideal solution for the interval number index: The positive ideal solution of the interval number index With negative ideal solution Specifically, it includes: ； in, The evaluation index within the weighted decision matrix is ​​the lower bound of the interval number. The evaluation index within the weighted decision matrix is ​​the upper bound of the interval number; Step 6.3 Obtaining the ideal solution for the triangular fuzzy number index: The positive ideal solution of the triangular fuzzy number index With negative ideal solution Specifically, it includes: ； in, The evaluation index within the weighted decision matrix is ​​the lower bound of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the median of the triangular fuzzy number. The evaluation index within the weighted decision matrix is ​​the upper bound of the triangular fuzzy number.

7. The method for evaluating the ecological restoration effect of steep bare rock mine slopes according to claim 6, characterized in that, In step S6, the Euclidean distance of each evaluation index of the evaluation object and the closeness of the evaluation object to the ideal solution are obtained. The magnitude of the closeness to the target is compared with the closeness to the evaluation level to obtain the evaluation result of the ecological restoration effect of the steep bare rock mine slope. Specifically, it includes the following: Step 7.1 Calculate the Euclidean distance between each evaluation index of the evaluation object: Euclidean distances of various evaluation objects from the positive ideal solution in the ecological restoration of steep, exposed rock slopes and the Euclidean distance from the negative ideal solution : ； in, The exact numerical evaluation index is the Euclidean distance from the positive ideal solution. The exact numerical evaluation index is the Euclidean distance from the negative ideal solution; The interval number evaluation index is the Euclidean distance from the positive ideal solution. The interval number evaluation index is the Euclidean distance from the negative ideal solution; The triangular fuzzy number evaluation index is the Euclidean distance from the positive ideal solution. The triangular fuzzy number evaluation index is the Euclidean distance from the negative ideal solution; The total number of evaluation indicators for the precise number type. The total number of evaluation indicators of the interval number type. The total number of evaluation indicators for the triangular fuzzy number type; Step 7.1.1 Calculation of the exact numerical Euclidean distance: The exact numerical index of the Euclidean distance to the positive ideal solution Euclidean distance to the negative ideal solution : ； ； in, To evaluate the distance of the indicator from the ideal solution of the indicator Euclidean distance, To evaluate the distance of the index from the negative ideal solution of the index The Euclidean distance; Step 7.1.2 Calculation of Euclidean distance for the interval index: Euclidean distance from the interval number index to the positive ideal solution Euclidean distance to the negative ideal solution : ； in, This is the upper bound of the positive ideal solution evaluation index for the interval number. This is the lower bound of the positive ideal solution for the interval number evaluation index. This represents the upper bound of the negative ideal solution for the interval number evaluation index. This is the lower bound of the positive ideal solution for the interval number evaluation index; 7.1.3 Calculation of Euclidean distance for the triangular fuzzy number index: Euclidean distance from the triangular fuzzy number index to the positive ideal solution Euclidean distance to the negative ideal solution : ； in, This represents the upper bound of the positive ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index; This represents the upper bound of the negative ideal solution for the triangular fuzzy number evaluation index. The median of the positive ideal solution for the triangular fuzzy number evaluation index is given. This is the lower bound of the positive ideal solution for the triangular fuzzy number evaluation index; Step 7.2 Obtain the closeness between the evaluation object and the ideal solution : ； in, To determine the approximation between the ecological restoration effect and the ideal solution for steep, exposed rock slopes. The Euclidean distance between the ecological restoration of steep, exposed rock slopes and the negative ideal solution. Euclidean distance for ecological restoration of steep, exposed rock slopes and positive ideal solution; Step 7.3 Determine the final evaluation result: The approximation thresholds corresponding to five evaluation levels—Excellent, Good, Fair, and Poor—are preset, and the calculated... Compare with the threshold, according to The threshold range in which it falls corresponds to the evaluation level of the ecological restoration effect of steep bare rock mine slopes, which is the final evaluation result.

8. A device for evaluating the ecological restoration effect of steep bare rock mine slopes, characterized in that, The method for evaluating the ecological restoration effect of steep bare rock mine slopes as described in claim 7 includes: The restoration module is used to obtain the restoration status data of the indicator layer evaluation indicators of the ecological restoration effect of steep exposed rock mine slopes after ecological restoration. The rating module is used to determine the rating level of each rating indicator based on the current restoration status of the rating indicators in the rating layer and the rating range of the rating indicators for the ecological restoration effect of steep exposed rock mine slopes. The weighting module is used to define the hierarchical relationship between the evaluation indicators of the criterion layer and the indicator layer, set the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer, and perform a consistency check on the discrimination matrix: if the consistency ratio of the importance discrimination matrix of the evaluation indicators of the criterion layer and the indicator layer both meet the set parameters, then the corresponding weights of each evaluation indicator of the criterion layer and the indicator layer are obtained. The matrix module is used to normalize the current status data of the evaluation indicators at the indicator layer to obtain a normalized data matrix; and to construct a weighted decision matrix by combining the weights output by the weight calculation module. The calculation module is used to obtain the ideal solution of the evaluation index, the Euclidean distance from the ideal solution, and the closeness to the ideal solution based on the weighted decision matrix of the evaluation index. The evaluation module is used to calculate the Euclidean distance and proximity of the evaluation object based on the positive ideal solution and the negative ideal solution, compare the proximity with a preset threshold, and output the final evaluation result of the ecological restoration effect of the steep bare rock mine slope.

9. A system for evaluating the ecological restoration effect of steep bare rock mine slopes, applied to the evaluation device described in claim 8, characterized in that, include: Memory is used to store computer programs and instructions; The processor is used to call and execute the computer programs and instructions stored in the memory to implement the steps of the method for evaluating the ecological restoration effect of steep bare rock mine slopes.

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