Urban underground space flood control toughness evaluation method and system based on multi-level feature fusion

Abstract

According to the urban underground space flood control toughness evaluation method and system based on multi-level feature fusion provided by the invention, a multi-level urban underground space flood control toughness evaluation index system of'target layer-sub-target layer-criterion layer-index layer 'is established; and urban underground space flood control toughness grade division and a toughness grading standard of each evaluation index are determined. The index weight of each level is determined based on the analytic hierarchy process and the fuzzy comprehensive evaluation method, then fuzzy comprehensive evaluation is carried out step by step, a final toughness evaluation result is obtained, the urban underground space flood prevention capacity under the extreme flood condition can be comprehensively and reasonably evaluated, and reference is provided for urban underground space flood prevention toughness analysis in the operation period.

Description

Technical Field

[0001] This invention relates to the field of flood control assessment of urban underground space, and in particular to a multi-level feature fusion method and system for evaluating the flood resilience of urban underground space. Background Technology

[0002] With the widespread development of underground space, urban public underground space has become an important spatial carrier for urban life services. At the same time, underground space systems face an increasing number of risks and disaster challenges. For example, in recent years, extreme weather events have frequently triggered underground space flooding incidents across the country, causing serious loss of life and property. Therefore, it is urgent to improve the disaster response capabilities and disaster prevention resilience of existing and future underground space engineering projects.

[0003] Current methods for establishing flood control systems in underground spaces typically involve formulating defense standards based on risk assessments and implementing corresponding facilities and measures, emphasizing controlling disaster losses by enhancing the resilience and robustness of these facilities. This approach is limited by the understanding and accuracy of flood prediction, and it fails to achieve the desired results in the face of increasingly unpredictable extreme floods, such as "once-in-a-century" or "once-in-a-millennium" events. Given the severe consequences and complex situations caused by extreme weather, integrating resilience thinking into the construction of urban underground space flood control systems can effectively enhance their flood resistance capabilities, their ability to recover rapidly from flood impacts, and their adaptability to extreme weather. However, research on the flood resilience of urban underground spaces is still in its early stages, and how to scientifically and comprehensively evaluate the flood resilience of urban underground spaces has become an urgent issue.

[0004] The evaluation index system for the flood resistance resilience of urban underground space involves multiple levels and multiple indicators. Therefore, it is necessary to use a comprehensive evaluation method to determine the weight of each indicator and to conduct a comprehensive evaluation of all indicators to ultimately determine the flood resistance resilience result of urban underground space. Summary of the Invention

[0005] The purpose of this application is to provide a multi-level feature fusion method and system for evaluating the flood resilience of urban underground space, which can evaluate the flood resilience status of urban underground space under extreme flood conditions.

[0006] The present invention adopts the following technical solution:

[0007] A multi-level feature fusion method for evaluating the flood resilience of urban underground space includes the following steps:

[0008] (1) Based on the flood resilience characteristics of urban underground space and the whole process of flood development, the flood resilience evaluation index system of underground space is used as the target layer, and four aspects of absorption capacity, resistance capacity, recovery capacity and adaptability are selected as sub-target layers. The four dimensions of technology, organization, society and economy are used as the criteria layer. Multiple indicators are selected under each criteria layer to establish a multi-level urban underground space flood resilience evaluation index system of “target layer - sub-target layer - criteria layer - indicator layer”.

[0009] (2) The weights of the evaluation indicators at each level are determined by the analytic hierarchy process, and weight vectors are established for different levels of the sub-objective layer, criterion layer and indicator layer.

[0010] (3) Based on relevant engineering experience and actual research objectives, classify the flood control resilience level of urban underground space and the corresponding score, and establish a level quantification matrix;

[0011] (4) Based on the toughness level classification in step (3), and combined with expert engineering experience and relevant specifications, determine the toughness grading standards for each evaluation index;

[0012] (5) Based on the specific characteristics of the urban underground space to be evaluated and the resilience grading standard of step (4), the resilience level of the evaluation indicators in the urban underground space flood control resilience evaluation system is determined by the on-site scoring of the evaluation experts, and a fuzzy judgment matrix of the indicator layer is established.

[0013] (6) Based on the principle of fuzzy comprehensive evaluation, fuzzy comprehensive evaluation is carried out on the criteria layer, sub-target layer and target layer step by step according to the weight vector of step (2) and the fuzzy judgment matrix of the index layer of step (5);

[0014] (7) Obtain the flood resistance resilience value of the underground space of the city to be evaluated based on the target layer resilience level matrix in step (6) and the level quantification matrix in step (3), and determine the resilience rating result according to the principle of maximum membership.

[0015] Furthermore, the flood resilience characteristics of urban underground space include robustness, redundancy, resource availability, and speed. Based on these characteristics, the specific indicators for regional environmental stratification in the technical dimension criteria layer under the absorption capacity level include: the relationship between the vertical surface of underground engineering and the vertical surface of the region; the current capacity standards for regional flood control and urban waterlogging prevention; the drainage speed and the design return period for waterlogging prevention; the discharge channels and capacity of floodwater exceeding the standard; the relationship between groundwater volume, water level, and project verticality; and the relationship between functional water volume and the diversion and discharge capacity of underground engineering. The technical dimension criteria layer under the absorption capacity level also includes the stratification of physical defense (specific indicators include: the number of entrances and exits and wells of underground engineering; the elevation of the terrain of entrances and exits and wells; the elevation of the water-retaining hump of entrances and exits and wells; the construction type of entrances and exits of underground engineering; the allowable inundation depth of each subspace of underground engineering; the regulation and storage capacity of diversion trenches and collection wells; and the emergency regulation and storage capacity of underground engineering for floodwater exceeding the standard) and the early warning and prevention layer (specific indicators include: the effectiveness of early warning and monitoring equipment; and the scope of early warning and monitoring). A total of 15 indicators are set in the three layers.

[0016] The specific indicators in the organizational dimension criteria layer under the absorption capacity level include: the completeness of the monitoring and early warning mechanism; the completeness of the safety responsibility system; the facility and equipment maintenance system; and the completeness of the regular risk investigation mechanism.

[0017] The specific indicators in the social dimension criteria layer under the absorption capacity level include: underground engineering flood prevention and safety management policies; the public's level of education on flood prevention; and the level of flood safety awareness campaigns.

[0018] The specific indicators in the economic dimension criteria layer under the absorption capacity level include: investment in flood control and rescue personnel training; and investment in flood control monitoring and early warning equipment.

[0019] The specific indicators in the technical dimension criteria layer under the resistance capacity level include: resistance and defense layer (height of additional water barriers at entrances and exits, number of flood control sandbags; flood gates at entrances and exits, backflow prevention gates on drainage pipes; production and living facilities and personnel evacuation channels and convenience in emergency storage spaces exceeding standards; number of internal floor drains and flow capacity of diversion trenches; drainage capacity of water pumps in collection wells), escape and rescue layer (number, service area, and signage of flood escape and rescue channels; passability of safe escape channels; pressurized opening of waterproof doors in escape channels, status of civil defense doors; height of water barriers at the entrance of escape and rescue channels; independent drainage capacity of escape and rescue channels; uninterrupted ventilation system for escape and rescue channels), disaster relief and emergency response layer (rescue material reserves; emergency power equipment; emergency communication equipment), and disaster relief safety layer (electrical communication equipment exceeding the allowable flood depth; leakage prevention of electrical equipment).

[0020] The specific indicators in the organizational dimension criteria layer under the resilience level include: the completeness of flood disaster emergency plans; the rationality of emergency organizational structure; information processing and transmission capabilities (including scope and timeliness); and emergency rescue capabilities.

[0021] The specific indicators in the social dimension criteria layer under the resilience level include: the coordination of various levels of underground engineering for flood prevention; urban medical rescue capacity; and the public's self-rescue and mutual rescue capabilities.

[0022] The specific indicators in the economic dimension criteria layer under the resilience level include: the amount of emergency funds invested in underground engineering for flood relief and rescue; and the rationality of fund allocation and use.

[0023] The specific indicators in the technical dimension criteria layer under the recovery capacity level include: the rate and time of receding floodwaters exceeding the standard in the region; the overflow capacity of drainage pipes and channels and the pumping capacity of drainage pumps in collection wells; the pumping capacity of pumps to empty emergency rainwater storage spaces exceeding the standard; the pumping capacity of temporarily deployable emergency drainage pumps; the cleaning capacity of facilities that can be deployed in flooded areas; and the capacity and effectiveness of deployable disinfection facilities.

[0024] The specific indicators in the organizational dimension criteria layer under the recovery capability level include: emergency repair and restoration of post-disaster infrastructure and equipment; relocation of production and living facilities in emergency storage spaces exceeding standards; ability to assess flood damage and formulate recovery plans; and ability to restore work order and working conditions.

[0025] The specific indicators in the social dimension criteria layer under the recovery capacity level include: the degree of social discussion; the degree of participation of social welfare organizations; the efficiency of the recovery of the normal operation capacity of underground spaces; and psychological counseling for disaster victims.

[0026] The specific indicators in the economic dimension criteria layer under the resilience level include: investment in underground engineering flood recovery funds; and investment in underground engineering flood insurance.

[0027] The specific indicators in the technical dimension criteria layer under the adaptability level include: optimizing and revising relevant plans to improve flood control and waterlogging prevention standards in areas where underground projects are located; and studying ways to remedy and improve weak points in underground projects' flood prevention facilities to enhance flood prevention capabilities.

[0028] The specific indicators in the organizational dimension criteria layer under the adaptability level include: investigation, summary and learning of accident causes; optimization and rectification by relevant departments; and promotion of flood prevention experience and lessons learned to similar projects.

[0029] Specific indicators in the social dimension criteria layer under the adaptability level include: raising awareness of flood safety precautions; and actively carrying out flood safety escape drills.

[0030] The specific indicators in the economic dimension criteria layer under the adaptability level include: investment in publicity and education on flood prevention in underground engineering; and investment in related rectification and optimization.

[0031] The above absorption capacity level has a total of 24 specific indicators; the resistance capacity level has a total of 25 specific indicators; the recovery capacity level has a total of 16 specific indicators; and the adaptability level has a total of 9 specific indicators.

[0032] Furthermore, in step (3), the flood resistance levels and scores of urban underground space are as follows: low resistance: [0, 0.6] points, lower resistance: (0.6, 0.8] points, medium resistance: (0.8, 0.9] points, and high resistance: (0.9, 1] points.

[0033] Furthermore, the steps of the analytic hierarchy process in step (2) include:

[0034] (2.1) Set relative importance scale: including extremely important, very important, important, slightly important, equal, slightly less important, less important, very less important, with corresponding indicator evaluation values ​​of 9, 7, 5, 3, 1, 1 / 3, 1 / 5, 1 / 7 respectively. Compare the indicators in the evaluation system pairwise, assign each indicator the corresponding scale value, and obtain the importance comparison judgment matrix C.

[0035]

[0036] In the formula, r ij This represents the relative importance of indicator i compared to indicator j.

[0037] (2.2) By solving the largest eigenvalue lmax of the importance comparison judgment matrix C, calculate the normalized eigenvector W, and calculate the weights of its components (W1 W2···Wn) corresponding to the n elements respectively;

[0038] ;

[0039] (2.3) Check whether the consistency ratio CR of the judgment matrix is ​​less than 0.1. If CR < 0.1, it means that the consistency of the judgment matrix is ​​acceptable. If CR > 0.1, the judgment matrix needs to be adjusted.

[0040] Furthermore, the fuzzy comprehensive evaluation principle in step (6) includes the following steps:

[0041] (6.1) First-level fuzzy comprehensive evaluation: using the index-level fuzzy judgment matrix R established based on expert scoring ri and the index layer weight vector W ri The comprehensive evaluation matrix B of the criterion layer is calculated. ri ;

[0042]

[0043] In the formula, r represents the criterion layer number r=T, O, S, E, and i represents the sub-target layer number i=A, B, C, D;

[0044] The comprehensive evaluation matrix B of the four criteria layers under each sub-target layer i ri Together they constitute the fuzzy judgment matrix R of the criterion layer. i ;

[0045]

[0046] (6.2) Second-level fuzzy comprehensive evaluation: using the fuzzy judgment matrix R of the criterion layer i and the criterion layer weight vector W i The sub-target layer comprehensive evaluation matrix B is calculated. i ;

[0047]

[0048] The comprehensive evaluation matrix B of the four sub-target layers under the target layer i Together they constitute the fuzzy judgment matrix R of the sub-target layer;

[0049]

[0050] (6.3) Three-level fuzzy comprehensive evaluation: The toughness level matrix B of the target layer Re is calculated using the fuzzy judgment matrix R of the sub-target layer and the weight vector W of the sub-target layer;

[0051] .

[0052] A system that implements the multi-level feature fusion method for evaluating the flood resilience of urban underground space.

[0053] A computer software program that runs the system or the method for evaluating the flood resilience of urban underground space through multi-level feature fusion.

[0054] The Analytic Hierarchy Process (AHP) is a systematic, hierarchical analysis method that combines qualitative and quantitative approaches. It is primarily used to solve multi-factor comprehensive evaluation problems lacking statistical data. This method involves setting relative importance scales, comparing indicators in the evaluation system pairwise, and assigning each indicator a corresponding scale value. The pairwise comparison process often incorporates a quartile scale to determine weights, hence it is also known as the "1-9 scale method." This method quantifies decision-makers' experience-based judgments, expressing qualitative judgments while leveraging the precision of quantitative analysis, and is widely used in scientific research. Fuzzy comprehensive evaluation, based on the membership principle of fuzzy mathematics, quantifies qualitative evaluation indicators, intuitively reflecting the characteristics of the research objective. It can provide a comprehensive evaluation of systems constrained by multiple influencing factors. This method has the advantages of a clear evaluation process, strong systematicity, and clear evaluation results, and can effectively solve the problem of fuzzy indicators that are difficult to quantify in real-world evaluation work. Based on the characteristics of a multi-level urban underground space flood resilience evaluation index system, this paper combines the Analytic Hierarchy Process (AHP) with the fuzzy comprehensive evaluation method. The AHP establishes a multi-level structure of evaluation indicators, determines the weights of the indicators based on importance calculations, and then uses the fuzzy comprehensive evaluation method to evaluate each indicator. The evaluation level of each indicator is determined according to the principle of maximum membership combined with expert scoring. Finally, the resilience evaluation result is obtained by combining the indicator weights and evaluation levels. This method combines the advantages of both the AHP and fuzzy comprehensive evaluation methods to establish a comprehensive and integrated urban underground space flood resilience evaluation method.

[0055] This invention addresses urban underground space by employing a hierarchical analysis method combined with fuzzy comprehensive evaluation to propose a multi-level urban underground space flood resilience evaluation method. This method can scientifically, rationally, and more comprehensively evaluate the flood control capacity of urban underground space under extreme flood conditions, providing a reference for the flood resilience analysis of urban underground space during the operational phase. It is of great significance for the design and improvement of the flood resilience of urban underground space.

[0056] The method provided by this invention considers the flood resilience characteristics of urban underground space and the entire process of flood development. Combining the characteristics of the underground space system, it establishes a multi-level evaluation index system for the flood resilience of urban underground space, consisting of a "target layer - sub-target layer - criterion layer - index layer," and determines the classification of urban underground space flood resilience levels and the resilience grading standards for each evaluation index. Based on the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method, the weights of each level's indexes are determined, and then fuzzy comprehensive evaluation is performed level by level to obtain the final resilience evaluation result. This method can comprehensively and reasonably evaluate the flood control capacity of urban underground space under extreme flood conditions, providing a reference for the analysis of the flood resilience of urban underground space during the operational phase. Attached Figure Description

[0057] Figure 1 This is a flowchart of the method of the present invention.

[0058] Figure 2 A framework diagram for evaluating the flood resilience of multi-level urban underground spaces.

[0059] Figure 3 It serves as an indicator of the flood control resilience and absorption capacity of urban underground spaces.

[0060] Figure 4 It serves as an indicator of the flood resistance and resilience of urban underground spaces.

[0061] Figure 5 This serves as an indicator of the flood resilience and recovery capacity of urban underground spaces.

[0062] Figure 6 This serves as an indicator of the flood control resilience and adaptability of urban underground spaces. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Since the evaluation index system for flood control resilience of urban underground space involves numerous indicators, this embodiment only specifically introduces the relevant indicators involved in the technical dimension (TA) criterion layer of the absorption capacity (A) sub-target layer and the specific calculation process of the target layer resilience Re.

[0064] A certain existing public underground space has a planned area of ​​25 hectares. The project design scope includes plots B, E, and H. Plots B and E will house two-story underground public service facilities and parking garages, while plot H will be a two-story underground parking garage. According to project data, the current flood control status of this underground space is as follows: During the project planning and design phases and the operation phases, apart from the water-retaining humps and sandbags at the entrances and exits, no professional flood prevention systems, professional flood escape and rescue systems, or professional rainwater storage systems to improve the project's and the surrounding area's flood control standards have been installed. Externally, it relies solely on the city's flood control and flood prevention facilities.

[0065] like Figure 1 The steps shown are for evaluating the flood resistance resilience of this underground space:

[0066] (1) Based on the "4R" characteristics of urban underground space flood control resilience (robustness, redundancy, resourcefulness, and rapidity) and combined with the entire process of flood development (pre-disaster prevention, emergency response during disaster, and post-disaster recovery), the target layer is to establish an evaluation index system for the flood control resilience of underground space. The sub-target layers are selected from four aspects: absorption capacity (A), resistance capacity (B), recovery capacity (C), and adaptability capacity (D). On this basis, considering the characteristics of the underground space system, the criteria layers are established from four dimensions: technical, organizational, social, and economic. A total of 74 indicators are selected to establish a multi-level evaluation index system for the flood control resilience of urban underground space, consisting of a target layer, sub-target layers, criteria layers, and indicator layers. Figure 2 As shown; the specific indicators under absorption capacity (A), resistance capacity (B), recovery capacity (C), and adaptability (D) are as follows: Figures 3-6 As shown.

[0067] (2) The weights of the evaluation indicators at each level are determined by the analytic hierarchy process, and the weight vectors of different levels of the sub-objective layer, the criterion layer, and the indicator layer are obtained.

[0068] (2.1) Set the relative importance ratio scale (Table 1), compare the indicators in the system to be evaluated pairwise, assign the corresponding scale value to each indicator, and obtain the importance comparison judgment matrix C;

[0069] Table 1. Relative Importance Ratio Scale

[0070] Indicator A compared to Indicator B Extremely important Very important important Slightly important Equal Slightly less important secondary Very minor Indicator Evaluation Value 9 7 5 3 1 1 / 3 1 / 5 1 / 7

[0071]

[0072] Where, r ij This represents the relative importance of indicator i compared to indicator j.

[0073] Taking the six indicators under the sub-target layer of absorption capacity (A) - technology dimension (TA) criterion layer - regional environment stratification indicators as an example, the importance comparison judgment matrix C is obtained according to the relative importance ratio scale:

[0074]

[0075] (2.2) By solving the largest eigenvalue lmax of the importance comparison judgment matrix C, calculate the normalized eigenvector W, and calculate the weights of its components (W1 W2···Wn) corresponding to the n elements respectively;

[0076]

[0077] (2.3) Consistency check: Ensure that the importance of each element corroborates each other. The consistency ratio (CR) of the judgment matrix needs to be checked to see if it is less than 0.1. If CR < 0.1, the consistency of the judgment matrix is ​​acceptable; if CR > 0.1, the judgment matrix needs to be adjusted. CR can be calculated using the following formula:

[0078]

[0079]

[0080] In the formula, RI is the evaluation index for random consistency, and its values ​​are shown in Table 2. lmax is the largest eigenvalue of the judgment matrix C, and n is the number of elements.

[0081] Table 2 Average Random Consistency Index (RI)

[0082] Matrix order 2 3 4 5 6 7 RI 0 0.52 0.89 1.12 1.26 1.36

[0083] The results are shown in Table 3. The consistency ratio (CR) is less than 0.1, indicating that the consistency of the judgment matrix is ​​acceptable.

[0084] Table 3 Consistency Test Results

[0085] Judgment Matrix <![CDATA[λ max ]]> CI RI CR C 6.072 0.014 1.26 0.011

[0086] The calculated absorption capacity (A) sub-target layer - technology dimension (TA) criterion layer - regional environment stratification index weight vector W is obtained. TA1 for:

[0087]

[0088] Similarly, we can derive the weight vector W of each indicator layer under the layered indicators of absorption capacity (A) sub-target layer - technology dimension (TA) criterion layer - ontological defense, early warning and prevention. TA2 W TA3 They are respectively:

[0089]

[0090]

[0091] Absorption Capacity (A) Sub-goal Layer - Weight Vector W of Indicators under the Criteria Layer of Technology Dimension (TA), Organizational Dimension (OA), Social Dimension (SA), and Economic Dimension (EA) TA W OA W SA W EA They are respectively:

[0092]

[0093]

[0094]

[0095]

[0096] Resistance Capability (B) Sub-goal Layer - Weight Vector W of Indicator Layers under the Criterion Layer of Technological Dimension (TB), Organizational Dimension (OB), Social Dimension (SB), and Economic Dimension (EB) TB W OB W SB W EB They are respectively:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105] The weight vector W of each indicator layer under the criteria layer of the resilience (C) sub-objective layer - technology dimension (TC), organization dimension (OC), social dimension (SC), and economic dimension (EC) TC W OC W SC W EC They are respectively:

[0106]

[0107]

[0108]

[0109]

[0110] The weight vector W of each indicator layer under the criteria layer of the adaptability (D) sub-goal layer - technology dimension (TD), organization dimension (OD), social dimension (SD), and economic dimension (ED) TD W OD WSD W ED They are respectively:

[0111]

[0112]

[0113]

[0114]

[0115] Absorption capacity (A), resistance capacity (B), recovery capacity (C), and adaptability (D) are the weight vectors W of each criterion layer under the sub-target layer. A W B W C W D They are respectively:

[0116]

[0117]

[0118]

[0119]

[0120] The sub-target layer weight vector W under the target layer is:

[0121]

[0122] (3) Based on relevant engineering experience and actual research objectives, the flood resistance levels of urban underground space are classified (Table 4), and a level quantification matrix is ​​established. .

[0123] Table 4 Classification of Structural Comprehensive Safety Evaluation Levels

[0124] Toughness level Specific score High toughness (0.9, 1] Medium toughness (0.8, 0.9] Lower toughness (0.6, 0.8] low toughness [0, 0.6]

[0125] (4) Based on the toughness level classification in step (3), combined with expert engineering experience and relevant specifications, determine the toughness grading standards for each evaluation index.

[0126] Taking the six indicators under the sub-target layer of absorption capacity (A) - technology dimension (TA) criterion layer - regional environment stratification indicators as an example, the resilience grading standards of the evaluation indicators are determined based on expert engineering experience and relevant specifications, as shown in Tables 5 to 10.

[0127] Table 5. Vertical Relationship Between Ground Surface and Regional Directions in Underground Space

[0128] Toughness level Judgment conditions High toughness h≥H1 Medium toughness H1>h≥H2 Lower toughness H2>h≥H3 low toughness h < H3

[0129] Where h represents the vertical elevation of the ground at the project location; H1 represents the average elevation of the high zone of the drainage zone; H2 represents the average vertical elevation of the drainage zone area; and H3 represents the average elevation of the low zone of the drainage zone.

[0130] Table 6 Current Status Standards for Regional Flood Control and Urban Waterlogging Prevention

[0131] Toughness level Judgment conditions High toughness α≥α3 Medium toughness α3＞α≥α2 Lower toughness α2＞α≥α1 low toughness α＜α1

[0132] Among them, the current standard that the underground space can actually reach is α once a year; according to the city size, regional positioning and other conditions, the standard is α1 to α2 once a year, which are specified in the "Outdoor Drainage Design Standard" (GB50014-2021); and the standard that the facilities such as the rainwater drainage channels that exceed the standard can improve the regional flood control and waterlogging prevention and control to a high standard of α3 once a year.

[0133] Table 7 Drainage rate and receding time of standard internal drainage facilities

[0134] Toughness level Judgment conditions High toughness hr≥0 Medium toughness hr1≥hr>0 Lower toughness hr2≥hr>hr1 low toughness hr > hr2

[0135] Among them, the design return period for waterlogging prevention is hr; the maximum allowable waterlogging time in the project area is hr1 to hr2, according to the "Outdoor Drainage Design Standard" (GB50014-2021); the waterlogging prevention design return period is 0.

[0136] Table 8. Drainage channels and capacity for floodwaters exceeding standards

[0137] Toughness level Judgment conditions High toughness With well-designed drainage channels and strong drainage capacity Medium toughness Imperfect drainage channels, strong discharge capacity Lower toughness Inadequate drainage channels and weak drainage capacity low toughness No drainage channel provided

[0138] Table 9. Relationship between groundwater volume, water level, and project verticality.

[0139] Toughness level Judgment conditions High toughness <![CDATA[h 顶 ≥H 底 ]]> Medium toughness <![CDATA[H 底 >h 顶 ≥H 雨 ]]> Lower toughness <![CDATA[H 雨 >h 顶 ≥H 常 ]]> low toughness <![CDATA[h 顶 <H 常 ]]>

[0140] Among them, h 顶 Indicates the elevation of the top of the underground space; h 底 Indicates the bottom elevation of the underground space; H 雨 Indicates the groundwater level during the rainy season; H 常 This indicates the groundwater level during the rainy season.

[0141] Table 10 Relationship between Functional Water Volume and Underground Space Diversion and Discharge Capacity

[0142] Toughness level Judgment conditions High toughness The functional water volume and intrusion rate are less than the size and speed of the underground space's diversion and discharge capacity. Medium toughness The functional water volume or intrusion rate is less than the underground space's diversion and discharge capacity or rate. Lower toughness Functional water volume and intrusion rate are equal to the size and speed of underground space diversion and discharge capacity. low toughness The functional water volume and intrusion rate exceed the size and speed of the underground space's diversion and discharge capacity.

[0143] (5) Based on the specific characteristics of the urban underground space to be evaluated and the resilience grading standard of step (4), the resilience level of the 74 evaluation indicators included in the urban underground space flood control resilience evaluation system is determined by the on-site scoring of the evaluation experts, and a fuzzy judgment matrix of the indicator layer is established.

[0144] Taking the six indicators under the sub-objective layer of absorption capacity (A) - technology dimension (TA) criterion layer - regional environment stratification indicators as an example, the results of the expert scoring by 10 evaluation experts are shown in Table 11:

[0145] Table 11 Expert Scoring Sheet (10 questionnaires in total)

[0146] Establish a fuzzy judgment matrix R for the indicator layer under the regional environmental stratification indicators. TA1 for:

[0147]

[0148] Similarly, we can obtain the fuzzy judgment matrix R of each indicator layer under the layered indicators of absorption capacity (A) sub-target layer - technology dimension (TA) criterion layer - ontology defense, early warning and prevention. TA2 R TA3 They are respectively:

[0149] ,

[0150] Similarly, the fuzzy judgment matrix R of each indicator layer under the criteria layer of the absorptive capacity (A) sub-target layer - organizational dimension (OA), social dimension (SA), and economic dimension (EA) OA R SA R EA They are respectively:

[0151] , ,

[0152] Resistance Capability (B) Sub-goal Layer - Fuzzy Judgment Matrix R of Indicator Layers under the Criterion Layer of Technological Dimension (TB), Organizational Dimension (OB), Social Dimension (SB), and Economic Dimension (EB). TB R OB R SB R EB They are respectively:

[0153] , , ,

[0154] , ,

[0155] The fuzzy judgment matrix R of each indicator layer under the criteria layer of the recovery capability (C) sub-target layer - technology dimension (TC), organization dimension (OC), social dimension (SC), and economic dimension (EC)TC R OC R SC R EC They are respectively:

[0156] , , ,

[0157] Adaptability (D) sub-goal layer - fuzzy judgment matrix R of each indicator layer under the criteria layer of the technology dimension (TD), organization dimension (OD), social dimension (SD), and economic dimension (ED). TD R OD R SD R ED They are respectively:

[0158] , , ,

[0159] (6) Based on the principle of fuzzy comprehensive evaluation, fuzzy comprehensive evaluation is carried out on the criteria layer, sub-target layer and target layer step by step according to the weight vector of step (2) and the fuzzy judgment matrix of the index layer of step (5);

[0160] ① First-level fuzzy comprehensive evaluation: Taking the six indicators under the sub-objective layer of absorption capacity (A) - technology dimension (TA) criterion layer - regional environment stratification indicators as an example, the fuzzy judgment matrix R of the indicator layer established based on expert scoring is used. TA1 and the index layer weight vector W TA1 Calculate the comprehensive evaluation matrix B TA1 for:

[0161]

[0162] Absorption Capacity (A) Sub-target Layer - Technology Dimension (TA) Criteria Layer - Comprehensive Evaluation Matrix under Layered Indicators for Ontological Defense, Early Warning and Prevention B TA2 B TA3 They are respectively:

[0163]

[0164]

[0165] Comprehensive evaluation matrix B under each stratified indicator TA1 B TA2 B TA3 Together they form the fuzzy judgment matrix R TA ;

[0166]

[0167] Using fuzzy judgment matrix R TA and weight vector W TA Calculate the comprehensive evaluation matrix B of the criterion layer. TA for:

[0168]

[0169] Similarly, we can derive the comprehensive evaluation matrix B of the criteria layer for the absorptive capacity (A) sub-target layer – organizational dimension (OA), social dimension (SA), and economic dimension (EA). OA B SA B EA They are respectively:

[0170]

[0171]

[0172]

[0173] Absorption Capacity (A) Sub-target Layer Four Criterion Layer Comprehensive Evaluation Matrix B TA B OA B SA B EA Together they constitute the fuzzy judgment matrix R of the criterion layer. A for:

[0174]

[0175] Similarly, we can derive the comprehensive evaluation matrix B of the criteria layer for the resistance capability (B) sub-target layer – including the technological dimension (TB), organizational dimension (OB), social dimension (SB), and economic dimension (EB). TB B OB B SB B EB They are respectively:

[0176]

[0177]

[0178]

[0179]

[0180] Resilience (C) Sub-goal Layer - Comprehensive Evaluation Matrix B of Criteria Layer for Technological Dimension (TC), Organizational Dimension (OC), Social Dimension (SC), and Economic Dimension (EC) TC B OC B SC B ECThey are respectively:

[0181]

[0182]

[0183]

[0184]

[0185] Adaptability (D) Sub-goal Layer - Comprehensive Evaluation Matrix B of Criteria Layer for Technological Dimension (TD), Organizational Dimension (OD), Social Dimension (SD), and Economic Dimension (ED) TD B OD B SD B ED They are respectively:

[0186]

[0187]

[0188]

[0189]

[0190] The four criterion-level comprehensive evaluation matrices under the sub-target layers of resistance (B), recovery ability (C), and adaptability (D) together constitute the fuzzy judgment matrix R of the criterion layer. B R C R D They are respectively:

[0191]

[0192]

[0193]

[0194] ② Second-level fuzzy comprehensive evaluation: Taking the absorption capacity (A) sub-target layer as an example, the comprehensive evaluation matrix B of the absorption capacity (A) sub-target layer is calculated using the fuzzy judgment matrix RA of the criterion layer and the weight vector WA of the criterion layer. A for:

[0195]

[0196] Similarly, we can derive the comprehensive evaluation matrix B for the sub-target layers of resistance (B), recovery ability (C), and adaptability (D). B B C B D They are respectively:

[0197]

[0198]

[0199]

[0200] The comprehensive evaluation matrix B of the four sub-target layers under the target layer A B B B C B D Together they constitute the fuzzy judgment matrix R of the sub-target layer;

[0201]

[0202] ③ Three-level fuzzy comprehensive evaluation: The resilience level matrix B of the target layer Re is calculated using the fuzzy judgment matrix R of the sub-target layer and the weight vector W of the sub-target layer.

[0203]

[0204] (7) The flood resistance toughness value Re of this embodiment is calculated based on the target layer toughness level matrix B in step (6) and the level quantification matrix H in step (3):

[0205]

[0206] Based on the principle of maximum membership, and referring to Table 4, the flood resistance level of this embodiment is determined to be medium resistance.

[0207] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and not restrictive.

Claims

1. A multi-level feature fusion method for evaluating the flood resilience of urban underground space, characterized in that, Includes the following steps: (1) Based on the flood resilience characteristics of urban underground space and the whole process of flood development, the flood resilience evaluation index system of underground space is used as the target layer, and four aspects of absorption capacity, resistance capacity, recovery capacity and adaptability are selected as sub-target layers. The four dimensions of technology, organization, society and economy are used as the criteria layer. Multiple indicators are selected under each criteria layer to establish a multi-level urban underground space flood resilience evaluation index system of "target layer - sub-target layer - criteria layer - indicator layer". (2) The weights of the evaluation indicators at each level are determined by the analytic hierarchy process, and weight vectors are established for different levels of the sub-objective layer, criterion layer and indicator layer. (3) Based on relevant engineering experience and actual research objectives, classify the flood control resilience level of urban underground space and the corresponding score, and establish a level quantification matrix; (4) Based on the toughness level classification in step (3), and combined with expert engineering experience and relevant specifications, determine the toughness grading standards for each evaluation index; (5) Based on the specific characteristics of the urban underground space to be evaluated and the resilience grading standard of step (4), the resilience level of the evaluation indicators in the urban underground space flood control resilience evaluation system is determined by the on-site scoring of the evaluation experts, and a fuzzy judgment matrix of the indicator layer is established. (6) Based on the principle of fuzzy comprehensive evaluation, fuzzy comprehensive evaluation is carried out on the criteria layer, sub-target layer and target layer step by step according to the weight vector of step (2) and the fuzzy judgment matrix of the index layer of step (5); (7) Obtain the flood resistance resilience value of the underground space of the city to be evaluated based on the target layer resilience level matrix in step (6) and the level quantification matrix in step (3), and determine the resilience rating result according to the principle of maximum membership.

2. The method for evaluating the flood resilience of urban underground space through multi-level feature fusion according to claim 1, characterized in that, The flood resilience characteristics of urban underground space include robustness, redundancy, resource availability, and speed. Based on these characteristics, the specific indicators of the regional environmental stratification in the technical dimension criteria layer under the absorption capacity level include the relationship between the vertical surface of underground engineering and the vertical surface of the region, the current capacity standards of regional flood control and waterlogging prevention, the drainage speed and the water receding time of the waterlogging prevention design return period, the discharge channels and capacity of floodwater exceeding the standard, the relationship between groundwater volume, water level and project verticality, and the relationship between functional water volume and the diversion and discharge capacity of underground engineering. The technical dimension criteria layer under the absorption capacity level also includes the stratification of physical defense and the early warning and prevention layer, with a total of 15 indicators in the three layers.

3. The method for evaluating the flood resilience of urban underground space through multi-level feature fusion according to claim 2, characterized in that, There are 24 specific indicators under the absorption capacity level; 25 specific indicators under the resistance capacity level; 16 specific indicators under the recovery capacity level; and 9 specific indicators under the adaptability level.

4. The method for evaluating the flood resilience of urban underground space through multi-level feature fusion according to claim 1, characterized in that, In step (3), the flood control resilience levels and scores of urban underground space are as follows: low resilience: [0, 0.6] points, lower resilience: (0.6, 0.8] points, medium resilience: (0.8, 0.9] points, and high resilience: (0.9, 1] points.

5. The method for evaluating the flood resilience of urban underground space through multi-level feature fusion according to claim 1, characterized in that, The steps of the analytic hierarchy process in step (2) include: (2.1) Set relative importance scale: including extremely important, very important, important, slightly important, equal, slightly less important, less important, very less important, with corresponding indicator evaluation values ​​of 9, 7, 5, 3, 1, 1 / 3, 1 / 5, 1 / 7 respectively. Compare the indicators in the evaluation system pairwise, assign each indicator the corresponding scale value, and obtain the importance comparison judgment matrix C. In the formula, r ij This represents the relative importance of indicator i compared to indicator j. (2.2) The largest eigenvalue of matrix C is determined by solving the importance comparison. lmax Calculate the normalized eigenvectors W And calculate its components ( W1 W2···Wn The weights of the n elements are respectively represented by ). ； (2.3) Check whether the consistency ratio CR of the judgment matrix is ​​less than 0.

1. If CR < 0.1, it means that the consistency of the judgment matrix is ​​acceptable. If CR > 0.1, the judgment matrix needs to be adjusted.

6. The method for evaluating the flood resilience of urban underground space through multi-level feature fusion according to claim 1, characterized in that, The fuzzy comprehensive evaluation principle in step (6) includes the following steps: (6.1) First-level fuzzy comprehensive evaluation: using the index-level fuzzy judgment matrix established based on expert scoring. R ri and indicator layer weight vector W ri The comprehensive evaluation matrix of the criterion layer is calculated. B ri ; In the formula, r This indicates the criterion layer number r = T, O, S, E. i Indicate the sub-target layer index i = A, B, C, D; Each sub-target layer i The four criteria layer comprehensive evaluation matrix B ri Together they constitute the fuzzy judgment matrix of the criterion layer. R i ; (6.2) Second-level fuzzy comprehensive evaluation: using the fuzzy judgment matrix of the criterion layer R i and criterion layer weight vector W i The sub-target layer comprehensive evaluation matrix is ​​calculated. B i ; The comprehensive evaluation matrix of the four sub-target layers under the target layer B i Together they constitute the fuzzy judgment matrix of the sub-target layer. R ; (6.3) Three-level fuzzy comprehensive evaluation: using the fuzzy judgment matrix of the sub-target layer R and sub-target layer weight vector W Calculate the target layer Re Resilience level matrix B ; 。 7. A system, characterized in that, The system operates the urban underground space flood resilience evaluation method as described in claim 1, which involves multi-level feature fusion.

8. A computer software, characterized in that, The software runs the system as described in claim 7 or the urban underground space flood resilience evaluation method as described in claim 1, which involves multi-level feature fusion.

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