Granite soil slope stability evaluation method based on combination weighting

Abstract

The invention relates to the technical field of rock and soil, and particularly discloses a granite soil slope stability evaluation method based on combined weighting, which comprises the following steps: selecting evaluation indexes influencing the stability of a granite soil slope, and establishing an evaluation index system for evaluating the stability of the granite soil slope; determining the stability classification of the granite soil slope and the classification standard of each index; calculating the subjective weight of each evaluation index by using an improved order relation method; calculating objective weights of the evaluation indexes by using an improved entropy weight method; calculating the combined weight of the indexes by a linear weighting method; calculating the membership degree of the slope instance at each level of stability; and judging the slope stability grade according to a maximum membership degree principle. According to the granite soil slope stability evaluation method based on combination weighting, the granite soil slope stability can be comprehensively, rapidly and objectively evaluated, and the accuracy and convenience of granite soil slope stability evaluation are improved.

Description

Technical Field

[0001] The invention relates to the field of rock and soil technology, and in particular to a granite soil slope stability evaluation method based on combined weighting. Background Art

[0002] With the rapid development of engineering construction in my country, engineering activities are increasingly expanding to areas with complex geological conditions. Especially in the development and construction of mountainous areas, the problem of slope stability has become a key factor restricting engineering safety and economic benefits. Especially in South China, due to the widespread distribution of granite, accounting for 30% to 40% of the total area of ​​Guangdong Province and about 40% in Fujian Province, due to the humid and rainy South China, the mountains in these areas have a thick granite weathering layer. The special properties of the weathering layer and slope residual layer have brought severe challenges to the stability of the slope. This kind of special rock and soil will soften and disintegrate after encountering water, and will crack after losing water, showing multiple characteristics such as high permeability, high porosity, loose structure and susceptibility to disturbance, which seriously affects the stability of granite soil slopes.

[0003] Granite soil slope refers to a type of slope composed of fully to moderately weathered granite residual soil, with some original rock structural surfaces still retained in the slope. The properties of this type of slope are between sandy soil and clay soil, but due to the existence of weak structural surfaces inherited from the parent rock or discontinuous surfaces that make it anisotropic, its stability problem is more complex and changeable. Therefore, timely and effective evaluation of the stability of granite residual soil slopes and exploration of an accurate, reliable, scientific and convenient evaluation method are of great significance to ensure engineering safety and improve engineering benefits.

[0004] At present, the methods for slope stability analysis can be divided into two categories: deterministic analysis and non-deterministic analysis. The first is qualitative analysis, including engineering analogy and graphic method. When faced with complex engineering geological conditions and lack of geological data, the engineering analogy method is often used to predict the stability of the current slope with reference to existing similar slope projects; in the stability analysis of rock slopes, the stereographic projection graphic method has its unique advantages. The second is quantitative analysis, which mainly includes limit equilibrium method, finite element method, finite difference method and fuzzy mathematics method. Among them, the limit equilibrium method is more commonly used because of its wide application and clear principle. This method is to make assumptions about the relationship between the shear resistance and shear force between the strips of slope soil, and use the static equilibrium equation to construct a safety factor calculation model, which provides strong support for the accurate evaluation of slope stability. In recent years, the comprehensive methods of multidisciplinary integration and application such as neural networks, fuzzy theory, and TOPSIS method have made the means of slope stability evaluation increasingly diversified, bringing new breakthroughs to slope stability analysis. Among them, the fuzzy hierarchical analysis method has been widely used in slope stability evaluation due to its simple method, clear principle and strong applicability, and has achieved remarkable results.

[0005] As two mainstream methods, qualitative analysis and quantitative analysis both include a variety of specific technical means, but each has its own limitations. Qualitative analysis methods, such as engineering analogy and graphic method, can provide an intuitive evaluation perspective, but their defects cannot be ignored. The engineering analogy method is highly dependent on historical similar slope engineering data. The scarcity or lack of accuracy of the data will directly weaken the reliability of the evaluation results. At the same time, this method has limitations in comprehensively considering complex factors such as geological conditions and hydrological conditions, which may lead to incomplete evaluation results. The graphic method places high demands on the user's professional knowledge and experience. If it is not understood or applied properly, it is easy to introduce errors. In addition, the graphic method usually stops at intuitive evaluation results and it is difficult to further carry out in-depth quantitative analysis and prediction. Quantitative analysis methods, such as limit equilibrium method, finite element method, and finite difference method, can provide more accurate evaluation results, but they also have limitations. The limit equilibrium method is based on a series of assumptions and simplified conditions, which may lead to inaccurate evaluation results, especially limited applicability under complex geological conditions. The finite element method and the finite difference method require a lot of calculations and data processing. Under certain complex geological conditions, it may be difficult to accurately simulate the true stress-strain relationship, resulting in evaluation deviations.

[0006] In addition, there are some comprehensive methods, such as neural network, fuzzy theory, TOPSIS method, etc. Although they have achieved certain results in slope stability evaluation, they also have some shortcomings. For example, the neural network algorithm requires a large amount of training data and appropriate model parameters. If the data is insufficient or the parameter settings are unreasonable, the model accuracy may be poor; the TOPSIS rule may be affected by factors such as the selection of evaluation indicators and weight distribution, resulting in subjective evaluation results; when the information entropy approaches 1, the traditional entropy weight method will cause a multiple change in the weight, which seriously affects the objectivity of the evaluation results.

[0007] Therefore, the current slope stability evaluation method still faces many challenges when applied to the stability evaluation of granite soil slopes. There is an urgent need for a simple, accurate and reliable granite soil slope stability analysis method to obtain the slope stability grade and provide certain theoretical guidance and data support for the stability analysis of granite soil slopes. Summary of the invention

[0008] In order to solve the problem that the existing slope stability evaluation method is not suitable for the stability evaluation of granite soil slopes, the present invention provides a granite soil slope stability evaluation method based on combined weighting. Based on the theoretical analysis and on-site investigation of granite soil slopes, reasonable evaluation indicators are selected to construct a set of granite soil slope stability evaluation index system to achieve specific quantification of the characteristics of the evaluation object. The selected structural surface type, maximum daily rainfall, groundwater impact, support strength and other evaluation indicators accurately reflect the key characteristics of granite soil slopes such as easy softening and disintegration when exposed to water, loose structure, and susceptibility to disturbance, simplifying the evaluation process and improving the evaluation efficiency. In order to overcome the limitations of a single weighting method and ensure the objectivity and rationality of the evaluation results, a combined weighting method based on a linear weighting method is proposed, which comprehensively improves the advantages of the entropy weight method and the improved order relationship method, improves the reliability and accuracy of weight distribution, and realizes a comprehensive, rapid and objective evaluation of the stability of granite soil slopes. The present invention can provide a reasonable and effective evaluation method for the stability evaluation of granite soil slopes, and solves the problems mentioned in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: a granite soil slope stability evaluation method based on combined weighting, comprising the following steps:

[0010] S1. Select the evaluation indexes that affect the stability of granite soil slopes and establish an evaluation index system for the stability of granite soil slopes;

[0011] S2. Determine the stability classification of granite soil slopes and the classification standards of various indicators;

[0012] S3. Use the improved ordinal relationship method to calculate the subjective weight of each evaluation index;

[0013] S4. Use the improved entropy weight method to calculate the objective weights of the evaluation indicators;

[0014] S5. Calculate the combined weight of the indicators using the linear weighting method;

[0015] S6. Calculate the membership of the slope instance in each stability level;

[0016] S7. Determine the slope stability grade based on the maximum membership principle.

[0017] Preferably, in step S1, the evaluation indexes of the stability of the granite soil slope include: slope morphology and geological factors U 1 , rock and soil characteristics 2 、Environmental factors 3 and engineering activity factor U 4 ; The slope morphology and geological factors U 1 Including slope height u 11, slope u 12 and geological structures 13 ; The rock and soil characteristics U 2 Including internal friction angle u 21 , cohesion u 22 , bulk density u 23 and structure surface type u 24 The environmental factor U 3 Including the maximum daily rainfall u 31 , groundwater impact 32 and vegetation coverage u 33 ; The engineering activity factor U 4 Including human disturbance u 41 , support strength u 42 and interception and drainage conditions 43 .

[0018] Preferably, in step S2, the stability of the slope is divided into the following four levels: level I, i.e. good stability; level II, i.e. relatively good stability; level III, i.e. relatively poor stability; and level IV, i.e. poor stability.

[0019] Preferably, in step S3, the following steps are specifically included:

[0020] S31. Determine the order relationship: for n evaluation indicators x 1 ,x 2 ,x 3 ,…,x n , the order of evaluation objects is determined according to the importance of each indicator to the evaluation indicator and objective facts. The more important the evaluation indicator is, the higher the evaluation order will be. The first one is set as followed by And so on, the last digit is Finally, these evaluation indicators are used Method sorting, that is, determining the order relationship of indicators;

[0021] S32. Determine the importance of adjacent indicators: Use the ratio to measure the importance of the sequential relationship indicators. Set the determination indicator and The importance ratio is r t :

[0022]

[0023] Where: r t for and Importance ratio, r t ∈[1.0,1.8]; m is the number of evaluation indicators; w' t 、w' t-1They are the subjective weights of the t-th and (t - 1)-th indicators respectively;

[0024] S33. Calculate the weights:

[0025]

[0026] Due to the complexity of the slope stability problem and the limitations of cognition, it is generally impossible to accurately judge the value of r, t but an interval value of r can be given. If an interval value of the ratio r of the importance degrees of the evaluation indicators t and is given, then r is called an uncertain ratio judgment, denoted as t Let t and Let r and Let r' t be an uncertain ratio judgment which is a random variable subject to a continuous uniform distribution on the interval, then the weight is:

[0027]

[0028] Preferably, in step S4, it specifically includes the following steps:

[0029] S41. Based on the parameter values corresponding to multiple groups of evaluation indicators, determine the initial interactive evaluation matrix A;

[0030]

[0031] In the formula, A is the initial interactive evaluation matrix, and a ij represents the parameter value corresponding to the j-th indicator of the i-th sample data;

[0032] S42. Normalize the matrix A to obtain the matrix A':

[0033]

[0034] In the formula, A' is the normalized evaluation matrix;

[0035] S43. Calculate the proportion P ij of the i-th sample index value under the j-th indicator;

[0036]

[0037] S44. Calculate the information entropy value e j (e > 0) and redundancy g j of the j-th indicator;

[0038]

[0039] g j =1-e j (j=1,2,3,...m)

[0040] S45. In order to overcome the problem that when the information entropy approaches 1, a small change in the traditional entropy weight method will cause the weight to change exponentially, the following formula is used to improve the entropy weight method to calculate the weight w of the jth indicator: j ;

[0041]

[0042] Preferably, in step S5, it specifically includes: using a linear weighting method to calculate the combined weight of each indicator, and the formula is expressed as follows:

[0043]

[0044] d(W t ,W j ) 2 =(α-β) 2 (α+β=1α>0,β>0)

[0045] W=αW t +βW j

[0046] In the formula, α is the subjective weighting coefficient; β is the objective weighting coefficient, W t To improve the subjective weight obtained by the order relation method, W j Objective weights obtained to improve the entropy weight method.

[0047] Preferably, in step S6, a descending semi-trapezoidal membership function is used to calculate the membership of each indicator, and the formula is expressed as follows:

[0048]

[0049] In the formula, u 1 ,u 2 ,u 3 ,u 4 is the membership function; x is the actual value of each evaluation index; a~d are the standard values ​​of each evaluation index under four kinds of stability.

[0050] Preferably, in step S7, the following steps are specifically included:

[0051] S71, constructing a fuzzy matrix R according to the calculated membership degree;

[0052]

[0053] S72, calculating the fuzzy comprehensive evaluation matrix B by using the fuzzy matrix R and the weights W obtained by the linear weighting method;

[0054]

[0055] In the formula, w i is the weight of each evaluation index, u ij is the membership degree of the j-th evaluation level of the i-th indicator of the evaluation object;

[0056] S73, according to the maximum membership principle, take B = max(b 1 , b 2 , …, b n ) is taken as the final evaluation level of the evaluation object.

[0057] The beneficial effect of the present invention is that: based on the analysis of the factors affecting the stability of granite soil slopes, the method of the present invention comprehensively considers the influence of subjective and objective factors on the slope stability, and combines the actual situation to construct a complete granite soil slope stability evaluation index system. In view of the key characteristics of granite soil slopes such as susceptibility to rainfall erosion, easy softening and disintegration when encountering water, loose structure, and susceptibility to disturbance, the structural surface type, maximum daily rainfall, groundwater influence, support strength and other evaluation indicators are selected to comprehensively reflect the characteristics and stability status of granite soil slopes. The established evaluation index system simplifies the evaluation process and improves the evaluation efficiency. Based on the linear weighting method, the subjective and objective weights obtained by the improved order relationship method and the improved entropy weight method are reasonably combined and weighted, so that the combined weights can more accurately reflect the influence of various influencing factors on slope stability, significantly improve the accuracy and comprehensiveness of the weight distribution of evaluation indicators, avoid the deviation caused by a single weighting method, not only give play to the objectivity of data analysis, but also give full play to the professional quality of the judges, make the evaluation results more comprehensive, realize the complementary advantages of subjective and objective weighting methods, effectively solve the limitations of a single weighting method and the problem of excessive deviation of weight values, and improve the accuracy and feasibility of the stability grade evaluation of granite soil slopes. At the same time, this method is easy to operate, widely applicable, and has high practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The flowchart of the granite soil slope stability evaluation method based on combined weighting is shown in the figure.

[0059] Figure 2 Schematic diagram of the system structure of the granite soil slope stability evaluation index system. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] The present invention aims to solve the problem that the current slope stability evaluation method is not suitable for the stability evaluation of granite soil slopes. Through in-depth research on the characteristics of granite soil slope rock and soil, combined with on-site investigation, on the basis of comprehensive analysis of the current status and influencing factors of granite soil slope diseases, comprehensive consideration of geological conditions, environmental conditions and other factors, analysis of the influence of different factors on the stability of granite soil slopes, selection of granite soil slope stability evaluation indicators, and construction of a granite soil slope stability evaluation indicator system. The scientificity and accuracy of the selection of evaluation indicators are achieved, and the dynamic changes and characteristics of the stability of granite soil slopes can be reflected, thereby ensuring the objectivity and accuracy of the evaluation results. The subjective weight and objective weight of each indicator are calculated respectively by the improved order relationship method and the improved entropy weight method, and the obtained subjective weight and objective weight are combined and weighted by the linear weighting method to obtain a more accurate combined weight. This method effectively overcomes the problems of subjective weights being highly arbitrary, lacking objectivity, and being highly dependent on the professional quality of the evaluator. It also solves the problem that objective weights have high requirements for data quality and are prone to ignoring the experience of the evaluator, and overcomes the problem that when the information entropy approaches 1, a small change in the traditional entropy weight method will cause the weight to change exponentially. The present invention provides a new idea and reference for the stability evaluation of granite soil slopes, which has far-reaching significance for ensuring the safety and stability of such slopes.

[0062] The present invention provides a technical solution: a method for evaluating the stability of granite soil slopes based on combined weighting, such as Figure 1 As shown, the following steps are included:

[0063] S1. Select the evaluation indexes that affect the stability of granite soil slopes and establish an evaluation index system for the stability of granite soil slopes.

[0064] like Figure 2 As shown in Figure 2, the evaluation indicators of granite soil slope stability include: slope morphology and geological factors U 1 , rock and soil characteristics 2 、Environmental factors 3 and engineering activity factor U 4 ; The slope morphology and geological factors U 1 Including slope height u 11 , slope u 12 and geological structures13 ; The characteristics U of the rock and soil mass 2 include the internal friction angle u 21 , the cohesion u 22 , the unit weight u 23 and the type of structural plane u 24 ; The environmental factors U 3 include the maximum daily rainfall u 31 , the influence of groundwater 32 and the vegetation coverage rate u 33 ; The engineering activity factors U 4 include human disturbance u 41 , the support strength u 42 and the drainage condition u 43 .

[0065] S2. Determine the stability classification of granite soil slopes and the classification criteria for each index.

[0066] Refer to the relevant standards for the stability classification of roadbed slopes, and classify the slope stability into the following four grades: Grade I (good stability), Grade II (relatively good stability), Grade III (relatively poor stability), and Grade IV (poor stability).

[0067] The classification criteria for each index are shown in Table 1:

[0068] Table 1 Classification Criteria for the Stability Evaluation Index of Granite Soil Slopes

[0069]

[0070]

[0071] S3. Calculate the subjective weights of each evaluation index using the improved order relation method.

[0072] Furthermore, it specifically includes the following steps:

[0073] S31. Determine the order relation: For n evaluation indices x 1 , x 2 , x 3 , …, x n , determine the order of the evaluation objects according to the importance of each index to the evaluation index and objective facts. The more important the evaluation index, the higher the evaluation order; set the one ranked first as followed by and so on, and the last one is Finally, sort these evaluation indices in the way, that is, determine the order relation of the indices;

[0074] S32. Judge the importance degree of adjacent indices: Measure the importance degree of the front and back order relation indices with a ratio. Let the judgment index and The importance ratio is r t :

[0075]

[0076] Where: r t for and Importance ratio, r t ∈[1.0,1.8]; m is the number of evaluation indicators; w' t 、w' t-1 are the subjective weights of the tth and t-1th indicators respectively;

[0077] S33. Calculate weight:

[0078]

[0079] Due to the complexity of slope stability and cognitive limitations, it is generally impossible to accurately determine r t , but can give r t If the interval value of the evaluation index is given and The importance ratio r t The interval value of r t It is called uncertain ratio judgment and is denoted by set up and Assume r t ' is an uncertain ratio judgment The random variable that follows a continuous uniform distribution on the interval, the weight is:

[0080]

[0081] The subjective weights of each evaluation index are shown in Table 2:

[0082] Table 2 Subjective weights

[0083]

[0084] S4. Calculate the objective weight of the evaluation index using the improved entropy weight method; specifically, the following steps are included:

[0085] S41, determining an initial interactive evaluation matrix A based on parameter values ​​corresponding to multiple groups of evaluation indicators;

[0086]

[0087] Where A is the initial interaction evaluation matrix, a ij Indicates the parameter value corresponding to the jth indicator of the i-th sample data;

[0088] S42. Normalize matrix A to obtain matrix A':

[0089]

[0090] In the formula, A' is the normalized evaluation matrix;

[0091] S43. Calculate the proportion P of the index value of the i-th sample under the j-th index ij ;

[0092]

[0093] S44. Calculate the information entropy value e of the j-th index j (e > 0) and redundancy g j ;

[0094]

[0095] g j = 1 - e j (j = 1, 2, 3,... m)

[0096] S45. To overcome the problem that in the traditional entropy weight method, when the information entropy approaches 1, a small change will cause the weight to change exponentially, use the improved entropy weight method to calculate the weight w of the j-th index j ;

[0097]

[0098] In the formula, w 1j is the weight calculated by the traditional entropy weight method, is the average value of all information entropies that are not 1.

[0099] The objective weights of each evaluation index are shown in Table 3:

[0100] Table 3 Objective weights

[0101]

[0102] S5. Calculate the combined weight of the index by the linear weighting method;

[0103] Furthermore, it specifically includes: calculating the combined weight of each index by the linear weighting method, and the formula is expressed as follows:

[0104]

[0105] d(W t ,W j ) 2 =(α - β) 2(α+β=1α>0,β>0)

[0106] W=αW t +βW j

[0107] In the formula, α is the subjective weighting coefficient; β is the objective weighting coefficient, W t To improve the subjective weight obtained by the order relation method, W j Objective weights obtained to improve the entropy weight method.

[0108] The objective weights of each evaluation index are shown in Table 4:

[0109] Table 4 Combination weights

[0110]

[0111] S6. Calculate the membership of the slope instance in each stability level;

[0112] Furthermore, the membership function of the descending semi-trapezoidal shape is used to calculate the membership of each indicator, and the formula is expressed as follows:

[0113]

[0114]

[0115] In the formula, u 1 ,u 2 ,u 3 ,u 4 is the membership function; x is the actual value of each evaluation index; a~d are the standard values ​​of each evaluation index under four kinds of stability.

[0116] S7. Determine the slope stability level according to the maximum membership principle. This includes the following steps:

[0117] S71, constructing a fuzzy matrix R according to the calculated membership degree;

[0118]

[0119] S72, calculating the fuzzy comprehensive evaluation matrix B by using the fuzzy matrix R and the weights W obtained by the linear weighting method;

[0120]

[0121] In the formula, w i is the weight of each evaluation index, u ij is the membership degree of the j-th evaluation level of the i-th indicator of the evaluation object;

[0122] S73, according to the maximum membership principle, take B = max(b 1 , b2 , …, b n ) is taken as the final evaluation level of the evaluation object.

[0123] Embodiment 1:

[0124] The stability of a typical highway granite soil slope in western Guangdong Province was evaluated. The maximum slope height is 31.0m, the first-level slope ratio is 1:0.75, and the second and third-level slope ratios are 1:1.0. Anchor frame beams are used for reinforcement. The stratum lithology is mainly medium to fully weathered granite, with developed joints and fissures, and a density of ρ = 2360kg / m 3 , cohesion C = 25 kPa, internal friction angle The drainage facilities of the slope were severely damaged and greatly affected by groundwater. The rear edge of the top of the slope was cracked and shifted, the frame beam was partially broken, and part of the slope collapsed. Tensile cracks were visible on the rear edge of the top of the slope. The cracks were about 70m long, 20 to 30cm wide, and about 90cm high.

[0125] According to the actual engineering situation of the slope, the membership of all influencing factors is determined, and then the membership of 13 evaluation indicators is obtained, see Table 5:

[0126] Table 5 Evaluation index membership

[0127]

[0128] The membership of 13 evaluation indicators is combined to construct the fuzzy matrix R:

[0129]

[0130] The fuzzy comprehensive evaluation set is calculated by combining the weight W and the fuzzy matrix R:

[0131] B=(0.0170,0.2668,0.3510,0.3652)

[0132] According to the principle of maximum membership, the stability level of the granite soil slope is the fourth level, which is in a poor stability state.

[0133] Embodiment 2:

[0134] In order to verify the accuracy of the stability evaluation model, based on a highway project in western Guangdong, 25 typical granite soil slopes were selected for fuzzy comprehensive evaluation in combination with relevant geological data and slope field investigation data. The slope profile is shown in Table 6. Among them, the first 10 slopes have obvious diseases and are in an unstable state; the last 15 slopes have no signs of deformation and hidden dangers and are basically in a stable state. The evaluation results of the improved order relationship method, the improved entropy weight method and the combined weighting method are shown in Table 7.

[0135] Table 6 Slope overview

[0136]

[0137]

[0138] Table 7 Evaluation results

[0139]

[0140]

[0141] Combined with Table 7, it can be seen that 3 evaluation results of the improved ordinal relationship method are inconsistent with the actual situation, and 4 evaluation results of the improved entropy weight method are inconsistent with the actual situation. Both methods have deviations to varying degrees. The accuracy of the method of the present invention is 8% and 12% higher than that of the improved ordinal relationship method and the improved entropy weight method, respectively. It proves that the selection of evaluation indicators such as structural surface type, maximum daily rainfall, groundwater influence, and support strength truly and accurately reflects the characteristics and stability status of granite soil slopes, and the combined weighting method gives full play to the advantages of subjective and objective weighting methods through reasonable weight distribution, while avoiding the deviation caused by a single weighting method, improving the accuracy of the evaluation results, and can objectively and truly reflect the actual situation of granite soil slopes.

[0142] The present invention comprehensively considers the influence of subjective and objective factors on the basis of comprehensive consideration of various influencing factors of granite soil slopes, combined with actual conditions, and selects evaluation indicators such as structural surface type, maximum daily rainfall, groundwater influence, and support strength to accurately reflect the characteristics of granite, such as being susceptible to rainfall erosion, being easily softened and disintegrated when exposed to water, being loose in structure, and being susceptible to disturbance, to comprehensively and accurately reflect its stability status, and to construct a stability evaluation index system for granite soil slopes, to ensure the scientificity and reliability of the evaluation results, and to improve the evaluation efficiency and accuracy of the evaluation results. Based on the linear weighted method, the subjective and objective weights obtained by the improved order relationship method and the improved entropy weight method are combined and weighted, giving full play to the advantages of the two methods, significantly improving the accuracy and comprehensiveness of the weight distribution of the evaluation indicators, providing a more scientific basis for the evaluation results, and effectively solving the limitations of the single weighting method and the problem of excessive deviation of the weight value.

[0143] It should be noted that, in the present invention, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0144] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0145] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0146] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0147] The "first\second" mentioned in the embodiments is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0148] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the stability of granite soil slopes based on combined weighting, characterized in that: The steps include: S1. Selecting evaluation indicators that affect the stability of granite soil slopes, wherein the evaluation indicators that affect the stability of granite soil slopes are divided into primary indicators and secondary indicators according to their levels, and establishing an evaluation indicator system for evaluating the stability of granite soil slopes; S2. Determine the stability classification of granite soil slopes and the classification standards of various indicators; S3. Use the improved ordinal relationship method to calculate the subjective weight of each evaluation index; S4. Use the improved entropy weight method to calculate the objective weights of the evaluation indicators; S5. Calculate the combined weight of the indicators using the linear weighting method; S6. Calculate the membership of the slope instance in each stability level; S7. Determine the slope stability grade based on the maximum membership principle.

2. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S1, the evaluation indexes of the stability of the granite soil slope include: slope morphology and geological factors U1, rock and soil characteristics U2, environmental factors U3 and engineering activity factors U4; the slope morphology and geological factors U1 include slope height u 11 , slope u 12 and geological structures 13 The rock mass characteristics U2 include the internal friction angle u 21 , cohesion u 22 , bulk density u 23 and structure surface type u 24 ; The environmental factor U3 includes the maximum daily rainfall u 31 , groundwater impact 32 and vegetation coverage u 33 ; The engineering activity factor U4 includes human disturbance u 41 , support strength u 42 And interception and drainage conditions 43 .

3. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S2, the stability of the slope is divided into the following four levels: level I, i.e. good stability; level II, i.e. relatively good stability; level III, i.e. relatively poor stability; and level IV, i.e. poor stability.

4. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S3, the following steps are specifically included: S31. Determine the order relationship: for n evaluation indicators x1, x2, x3, ..., x n , the order of evaluation objects is determined according to the importance of each indicator to the evaluation indicator and objective facts. The more important the evaluation indicator is, the higher the evaluation order will be. The first one is set as followed by And so on, the last digit is Finally, these evaluation indicators are used Method sorting, that is, determining the order relationship of indicators; S32. Determine the importance of adjacent indicators: Use the ratio to measure the importance of the sequential relationship indicators. Set the determination indicator and The importance ratio is r t : Where: r t for and Importance ratio, r t ∈[1.0,1.8]; m is the number of evaluation indicators; w' t 、w' t-1 are the subjective weights of the tth and t-1th indicators respectively; S33. Calculate weight: Due to the complexity of slope stability problems and cognitive limitations, it is generally impossible to accurately give r t , but can give r t If the interval value of the evaluation index is given and The importance ratio r t The interval value of r t It is called uncertain ratio judgment and is denoted by set up and Assume r t ' is an uncertain ratio judgment The random variable that follows a continuous uniform distribution on the interval, the weight is:

5. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S4, the following steps are specifically included: S41, determining an initial interactive evaluation matrix A based on parameter values ​​corresponding to multiple groups of evaluation indicators; Where A is the initial interaction evaluation matrix, a ij Indicates the parameter value corresponding to the jth indicator of the i-th sample data; S42, normalize the matrix A to obtain the matrix A': In the formula, A' is the normalized evaluation matrix; S43. Calculate the proportion P of the i-th sample index value under the j-th index ij ; S44. Calculate the information entropy value e of the j-th indicator j (e>0) and redundancy g j ; g j =1-e j (j=1,2,3,...m) S45. In order to overcome the problem that when the information entropy approaches 1, a small change in the traditional entropy weight method will cause the weight to change exponentially, the following formula is used to improve the entropy weight method to calculate the weight w of the jth indicator: j ; 6. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S5, it specifically includes: using the linear weighting method to calculate the combined weight of each indicator, the formula is expressed as follows: d(W t ,W j ) 2 =(a-b) 2 (α+β=1α>0,β>0) W=αW t +βW j In the formula, α is the subjective weighting coefficient; β is the objective weighting coefficient, W t To improve the subjective weight obtained by the order relation method, W j Objective weights obtained to improve the entropy weight method.

7. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S6, the membership degree of each index is calculated using a descending semi-trapezoidal membership function, and the formula is as follows: Where u1, u2, u3, u4 are membership functions; x is the actual value of each evaluation index; a~d are the standard values ​​of each evaluation index under four kinds of stability.

8. The granite soil slope stability evaluation method based on combined weighting according to claim 1 is characterized by: In step S7, the following steps are specifically included: S71, constructing a fuzzy matrix R according to the calculated membership degree; S72, calculating the fuzzy comprehensive evaluation matrix B by using the fuzzy matrix R and the weights W obtained by the linear weighting method; In the formula, w i is the weight of each evaluation index, u ij is the membership degree of the j-th evaluation level of the i-th indicator of the evaluation object; S73, according to the maximum membership principle, take B = max(b1, b2, ..., b n ) is taken as the final evaluation level of the evaluation object.

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