Quantitative assessment and double prevention method of multi-dimensional coupling risk of historical and cultural tourism blocks

Abstract

The application discloses a historical and cultural tourism block multi-dimensional coupling risk quantification evaluation and double prevention method, establishes a unified risk unit around building conditions, facility states, personnel activities and environmental constraints in the historical and cultural tourism block, continuously collects and updates basic data in the block operation process, and forms a whole cycle operation method with the connection of risk identification, risk calculation, grade determination, governance execution and result feedback. The application can carry out dynamic evaluation around the block building conditions, facility states, personnel activities and environmental constraints, effectively connects risk grading control and hidden danger investigation and governance, and forms a closed-loop operation safety prevention mechanism.

Description

Technical Field

[0001] This invention belongs to the field of public safety risk assessment and prevention technology, specifically involving a multi-dimensional coupled risk quantification assessment and dual prevention method for historical and cultural tourist districts. Background Technology

[0002] Against the backdrop of the continuous advancement of cultural and tourism integration, the spiritual and cultural needs of the people are constantly upgrading. Historical and cultural tourism blocks have become important spatial carriers and popular destinations integrating cultural display, tourism consumption, residents' life, and commercial operations. These blocks differ from general scenic spots or ordinary commercial blocks. They are typically characterized by dense buildings with aging structures, insufficient modernization of infrastructure such as fire protection and electrical systems, frequent gatherings and flows of tourists during holidays, and the intertwining of modern business activities and heritage protection requirements. Their safety risks are complex, comprehensive, dynamic, and unpredictable.

[0003] The existing management methods mainly rely on safety inspections, expert assessments, static grading, and special rectification campaigns, but there are still obvious shortcomings: on the one hand, risk assessments are mostly based on static data, and different risk-inducing factors are often treated separately, lacking a systematic characterization of the coupling effect between buildings, facilities, people, and the environment; on the other hand, the risk assessment results are not closely linked to the investigation and management of hidden dangers, and a risk-driven investigation and management mechanism has not yet been formed that is oriented towards the characteristics of historical and cultural tourism blocks. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-dimensional coupled risk quantification assessment and dual prevention method for historical and cultural tourism blocks. This method can conduct dynamic assessments based on the block's building conditions, facility status, personnel activities, and environmental constraints, and effectively link risk classification and control with hidden danger investigation and management to form a closed-loop safety prevention mechanism.

[0005] To achieve the above objectives, this invention provides a method for multi-dimensional coupled risk quantification assessment and dual prevention in historical and cultural tourism districts, comprising the following steps: S1, Collect street data to construct risk units: Obtain multi-dimensional data on buildings, facilities, people and spaces within the street, divide the street and construct several risk units; S2, Multidimensional Risk Factor Extraction and Quantification: Extract building risk factors, facility risk factors, personnel risk factors and environmental operation risk factors for each risk unit, and calculate the risk value of each dimension in combination with the operation period; S3, Risk Coupling Calculation and Identification: Establish the coupling calculation relationship between buildings, facilities, people and environment within the same risk unit, identify the compound risk when multiple types of risks act together, and obtain the final risk value; S4, Risk Classification Assessment and Strategy Control: Based on the risk value range, each risk unit is classified into risk levels, resulting in risk assessment results including low risk, medium risk, relatively high risk and high risk. Executable risk classification control is configured for risk units with different risk assessment results. S5, Hazard Identification and Risk Management: Establish a database of related hazard identification items and management measures in advance, establish a correspondence between risk assessment results and hazard identification items, and form a dual prevention mechanism for street safety that combines risk classification and control with hazard identification and management; S6, Feedback on governance results and risk reassessment: Data is re-collected for risk units after governance by the dual safety prevention mechanism, and the street data in S1 is updated for risk reassessment to form a closed loop.

[0006] As a further aspect of the present invention: In S2: Building risk factors include the following indicators: fire resistance reduction value, component aging and cracking rate, protection operation restrictions, and equivalent combustible load; Facility risk factors include the following indicators: fire protection facility failure rate, electrical load per unit area, gas usage intensity per unit area, and proportion of monitoring blind spots; Personnel risk factors include the following indicators: passenger flow density, average stay time, node clustering degree, and flow direction disturbance degree; Environmental operation risk factors include the following indicators: effective street width constraints, path tortuosity coefficient, rescue arrival time, and temporary road occupancy ratio.

[0007] As a further aspect of the present invention: the risk coupling calculation process in S3 includes: Based on the risk values ​​of each dimension calculated by S2, the power average is used to form the dimension aggregate value, and the discrete terms of the indicators within the same dimension are measured. The aggregate value and the discrete terms are mapped to the dimension sub-risk value. Calculate the hazard closure rate, which reflects the degree of completion of risk unit governance in the previous governance cycle. When the hazard closure rate is higher than the threshold, no compensation item is triggered, and the coupling coefficient is restored to the set base value. When the hazard closure rate is lower than the threshold, the coupling coefficient is increased so that the governance lag results enter the next round of risk calculation. Introduce the entropy value of mixed business operations, and combine it with the coupling coefficient and the dimension sub-risk value to determine the coupling enhancement term; The dimensional sub-risk value and coupling enhancement term are compressed into an undiffused comprehensive risk value, and adjacent unit transmission term and boundary gradient term are introduced to obtain the spatially corrected final risk value.

[0008] As a further aspect of the present invention: the contribution ratio of each dimension is calculated based on the dimensional sub-risk value to identify the dominant risk dimension.

[0009] As a further aspect of the present invention: a priority is set for hazard elimination tasks in the hazard investigation database in S4.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) It can establish a unified risk identification unit for historical and cultural tourism blocks, and uniformly categorize buildings, facilities, personnel activities and environmental conditions to solve the problems of scattered risk objects, unclear boundaries and fragmented information in the blocks.

[0011] 2) It can realize dynamic risk quantification for the operation of historical and cultural tourism blocks, calculate the risk change results under different time states, and solve the problem that traditional static inspection methods are difficult to reflect the dynamic changes in the operation process.

[0012] 3) It can characterize the complex risks formed by the superposition of building, facility, personnel and environmental conditions, and identify complex risk areas that are difficult to reveal by single inspection by establishing the coupling calculation relationship of multiple risk factors.

[0013] 4) It can directly transform risk assessment results into hierarchical control actions, form dynamic risk levels based on changes in risk values, determine corresponding risk control requirements and measures, and make the risk classification results have a clear execution path.

[0014] 5) It can establish a correspondence between risk outcomes and hidden danger investigation and management, forming a hidden danger investigation and management mechanism driven by risk assessment results, and solving the problem of separation between risk assessment, hidden danger investigation and management.

[0015] 6) It can adapt to the governance requirements under the protection constraints of historical and cultural tourism blocks, fully consider the building protection boundaries, environmental constraints and the continuity of business activities, so that the governance measures are applicable to the specific object of historical and cultural tourism blocks.

[0016] 7) It can form a continuously updated closed-loop prevention mechanism, feeding back the investigation results, governance results and review results to the risk calculation process, forming a closed-loop operation mechanism that connects risk identification, quantitative classification, control and governance and result feedback. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the multi-dimensional coupled risk quantification assessment and dual prevention method for historical and cultural tourism districts according to the present invention. Detailed Implementation

[0018] The present invention will be further illustrated by the following examples.

[0019] like Figure 1 As shown, the multi-dimensional coupled risk quantification assessment and dual prevention method for historical and cultural tourism districts includes the following steps: S1, Collect street data to construct risk units: Obtain multi-dimensional data on buildings, facilities, people and spaces within the street, divide the street and construct several risk units.

[0020] A unified risk assessment unit is established for historical and cultural tourism districts, focusing on buildings, businesses, streets, open areas, evacuation routes, and infrastructure. Specifically, the district is divided into several basic grids, overlaid with data on building location, business distribution, fire safety facility placement, monitoring range, street accessibility, and visitor activity areas, forming an integrated risk unit that is actionable, traceable, and accountable. Each risk unit records basic data such as building structure type, building aging level, fire resistance, fire safety facility configuration, electrical wiring status, gas and other open flame usage, visitor density, number of visitors at key points, street width and accessibility, and emergency rescue accessibility.

[0021] S2, Multidimensional Risk Factor Extraction and Quantification: Extract building risk factors, facility risk factors, personnel risk factors and environmental operation risk factors for each risk unit, and calculate the risk value of each dimension in combination with the operation period; Building risk factors include the following indicators: fire resistance reduction value, component aging and cracking rate, protection operation restrictions, and equivalent combustible load; Facility risk factors include the following indicators: fire protection facility failure rate, electrical load per unit area, gas usage intensity per unit area, and proportion of monitoring blind spots; Personnel risk factors include the following indicators: passenger flow density, average stay time, node clustering degree, and flow direction disturbance degree; Environmental operation risk factors include the following indicators: effective street width constraints, path tortuosity coefficient, rescue arrival time, and temporary road occupancy ratio.

[0022] Based on changes in passenger flow, operational status, and environmental constraints at different times, the risk value of the risk unit is dynamically calculated so that the risk results can reflect the differences in peak and off-peak periods, holiday peak periods, night tour periods, and large-scale event periods.

[0023] S3, Risk Coupling Calculation and Identification: Establish the coupling calculation relationship between buildings, facilities, people and environment within the same risk unit, identify the compound risk when multiple types of risks act together, and obtain the final risk value; The risk coupling calculation process includes: Based on the risk values ​​of each dimension calculated by S2, the power average is used to form the dimension aggregate value, and the discrete terms of the indicators within the same dimension are measured. The aggregate value and the discrete terms are mapped to the dimension sub-risk value. Calculate the hazard closure rate, which reflects the degree of completion of risk unit governance in the previous governance cycle. When the hazard closure rate is higher than the threshold, no compensation item is triggered, and the coupling coefficient is restored to the set base value. When the hazard closure rate is lower than the threshold, the coupling coefficient is increased so that the governance lag results enter the next round of risk calculation. Introduce the entropy value of mixed business operations, and combine it with the coupling coefficient and the dimension sub-risk value to determine the coupling enhancement term; The dimensional sub-risk value and coupling enhancement term are compressed into an undiffused comprehensive risk value, and adjacent unit transmission term and boundary gradient term are introduced to obtain the spatially corrected final risk value.

[0024] Furthermore, the contribution ratio of each dimension is calculated based on the dimensional sub-risk values ​​to identify the dominant risk dimension.

[0025] S4, Risk Classification Assessment and Strategy Control: Based on the risk value range, each risk unit is classified into risk levels, resulting in risk assessment results including low risk, medium risk, relatively high risk and high risk. Executable risk classification control is configured for risk units with different risk assessment results. The risk assessment results can be dynamically adjusted according to changes in passenger flow, operating status, facility status and rectification results. For risk units of different levels, corresponding patrol frequencies, key duty requirements, control and constraint areas, business restrictions and personnel diversion measures are configured.

[0026] S5, Hazard Identification and Risk Management: Establish a database of related hazard identification items and management measures in advance, establish a correspondence between risk assessment results and hazard identification items, and form a dual prevention mechanism for street safety that combines risk classification and control with hazard identification and management; Prioritize the tasks for identifying and eliminating potential hazards in the hazard identification database.

[0027] The hazard investigation items include, but are not limited to, malfunctioning fire-fighting facilities, aging electrical wiring, illegal use of fire and gas, blocked evacuation routes, blind spots in monitoring, overloaded and congested nodes, and business operations that do not meet control requirements; the remediation measures include, but are not limited to, facility repair, line replacement, business restrictions, flow control and diversion, temporary duty, and special rectification of key nodes.

[0028] Once a risk unit is determined to be at the corresponding level, the system matches the corresponding investigation focus, investigation frequency, governance time limit, and review requirements according to the risk type.

[0029] S6, Feedback on governance results and risk reassessment: Data is re-collected for risk units after governance by the dual safety prevention mechanism, and the street data in S1 is updated for risk reassessment to form a closed loop.

[0030] Specifically, the following steps are taken: The status of rectified facilities, routes, traffic conditions, node capacity, and operational status will be re-entered into the street's basic risk database, and risk calculations will be recalculated for the corresponding risk units. If the risk value decreases to the control range after rectification, its risk level and control requirements will be adjusted; if the control requirements are still not met after rectification, review tasks and supplementary remediation tasks will continue to be generated; for units that fail to pass rectification consecutively, related business activities will be suspended and operational feasibility will be reassessed.

[0031] By integrating risk assessment, risk classification, hazard investigation, remediation implementation, and result review and feedback into a continuous operation process, a closed-loop operation method is formed that integrates risk identification, risk quantification, hierarchical control, hazard investigation, and feedback review.

[0032] Specific embodiments of the present invention are as follows: Step 1: Real-time Scene and Sample Unit A historical and cultural tourist district with an area of ​​0.86 km² was selected as the calculation object. This district includes 32 brick-and-wood structure buildings, 87 mixed-use businesses, 29 restaurants and guesthouses, 24 main streets and alleys, 18 node squares, 14 fire-fighting facilities, and 146 video surveillance points. Based on street layout, building boundaries, business density, and holiday visitor flow patterns, the district was divided into 26 risk units. Each risk unit can be independently assessed for different risk indicators.

[0033] The seventh risk unit was used as the calculation sample. This unit is located at the intersection of the main street and the side alley, where restaurants, guesthouses, retail and residential spaces are interspersed. During holidays from 19:00 to 21:00, the passenger flow density is in the high percentile range of the block.

[0034] Step 2: Input Variables and Preprocessing Building-side inputs include fire resistance reduction values, component aging and cracking rates, restrictions on protective operations, and equivalent combustible loads; facility-side inputs include fire protection facility failure rates, electrical load per unit area, gas usage intensity per unit area, and the proportion of monitoring blind spots; personnel-side inputs include passenger flow density, average dwell time, node aggregation, and flow disturbance; environmental-side inputs include effective street width constraints, path tortuosity coefficient, rescue arrival time, and the proportion of temporary road occupancy.

[0035] Passenger flow density is denoted as The unit is person / m²; the electrical load per unit area is denoted as The unit is kW / 100m²; the equivalent combustible load is denoted as... The unit is MJ / m²; the arrival time of the rescue is recorded as... The unit is seconds (s). The observation value of risk unit 7 at 19:00 on a holiday is: The average stay was 18.4 minutes. The gas usage intensity is 1.31. , The effective street width is 3.10 m.

[0036] Further normalization calculations are performed on the risk values ​​of different risk units, different times, and different indicators. When the larger the original value of an indicator, the higher the risk, Equation (1) is used for calculation; when the larger the original value of an indicator, the safer it is, Equation (2) is used to convert it into a risk quantity; when it is necessary to use three consecutive sampling windows to perform weighted smoothing on an indicator, Equation (3) is used for calculation.

[0037] ; ; ; in: Number the risk dimensions and take These represent building maintenance, facility maintenance, personnel maintenance, and environmental maintenance, respectively. Number the risk units; For dimension Indicator number within; For the first Each risk unit at time The Vidi Original observations; This corresponds to the normalized risk value; and The first Vidi The lower and upper limits of each indicator; To prevent tiny positive numbers with a denominator of zero; This is the smoothed, normalized risk value; This represents the sampling time interval.

[0038] Step 3: Mathematical Model and Derivation Chain Based on the above normalization results, Equation (4) uses the power average form to form the dimensional aggregate value, Equation (5) measures the discrete terms of the indicators within the same dimension, and Equation (6) maps the aggregate value and the discrete terms to the dimensional sub-risk value.

[0039] ; ; ; in: For the first A set of indicators for dimensions; For the first Dimensional aggregation value; For the first Vidi Each indicator has a weight, and within the same dimension ; The power-mean aggregation index; For the first Discrete terms within the dimension; For the first VIz risk value; This is a parameter to amplify the aggregation value; For discrete term amplification parameters; This is the threshold parameter.

[0040] Furthermore, the hazard closure rate of the previous governance cycle is calculated by formula (7) to reflect the degree of governance completion of the risk unit; when the hazard closure rate is lower than 0.80, the coupling coefficient is increased by formula (8) so that the governance lag results enter the next round of risk calculation.

[0041] ; ; in: For the first The hazard closure rate of each risk unit in the previous governance cycle; This refers to the number of potential hazards identified in the previous remediation cycle. This represents the number of potential hazards that were closed in the previous remediation cycle. For the adjusted number Class coupling coefficient; For the first The fundamental coefficients of class coupling terms; The factor for the delayed compensation in governance; Number the coupling items.

[0042] Equation (9) is used to characterize the degree of mixed operation of business formats. The more balanced the proportion of catering, homestay, retail and residential life, the higher the entropy value. Equation (10) introduces a third-order interaction term involving the entropy value of mixed operation of business formats, based on the four types of dual-factor coupling: building-personnel, facility-personnel, building-environment, and facility-environment.

[0043] ; Cᵢ ( t ) =β 1( i,t ) ·R B (i,t ) ·R P ( i,t ) +β 2( i,t ) ·R E ( i,t ) ·R P ( i,t ) +β 3( i,t ) ·R B ( i, t ) ·R_ S ( i,t ) +β 4( i,t ) ·R E ( i,t ) ·R S ( i,t ) + 5( i,t ) ·χ i ·R B ( i,t ) ·R E ( i,t ) ·R · ( i,t (10); in: For the first The entropy value of mixed business operations in each risk unit; For the first Within the risk unit, the first The proportion of similar business formats; For the first The number of business types within a risk unit; when At that time, it was agreed ; For the first Each risk unit at time Coupling enhancement terms; to These are the coefficients of various coupling terms; , , , These are the risk values ​​for building maintenance, facility maintenance, personnel maintenance, and environmental maintenance, respectively.

[0044] Equation (11) compresses the four-dimensional sub-risk value and coupling enhancement term into a non-diffused comprehensive risk value; Equation (12) introduces the adjacent unit transmission term and boundary gradient term to obtain the final risk value after spatial correction; Equation (13) calculates the dimensional contribution ratio; Equation (14) is used to generate the priority of hidden danger investigation tasks; Equation (15) is used to evaluate the risk reduction after treatment.

[0045] ; ; ; ; ; in: For the first The unspread composite risk value of each risk unit; , , , These are the combined weights for building maintenance, facility maintenance, personnel maintenance, and environmental maintenance, respectively. For the comprehensive risk compression slope parameter; The comprehensive risk compression threshold; This is the final risk value after spatial correction; To be with unit Adjacent risk unit numbers; For unit With adjacent units The adjacency weights between them, and ; This represents the unit's own risk weight in spatial correction. These are the boundary gradient correction coefficients; For the first The percentage of contribution of each dimension to overall risk; Index for summing dimensions; For the first Each risk unit at time The Priority of tasks involving hazard identification; The degree of alignment between the task and the dominant risk; For task timeliness factors; Historical cumulative factor; For the slope parameter of the task ranking model; to Weights of factors affecting task ranking; The threshold for triggering task priority; This represents the risk reduction after remediation; This represents the final risk value before remediation. This represents the final risk value after treatment.

[0046] Step 4: Variable Description and Parameter Setting The main variables and parameters involved in the above process are shown in Tables 1 and 2.

[0047] Table 1. Explanation of the meaning of main variables

[0048] Table 2 Parameter Value Setting Table

[0049] Step 5: Risk Assessment Sample Analysis After applying equations (1) to (3) to the 7th risk unit at 19:00 and the two 5-minute sampling windows prior to it, smoothed and normalized results were obtained. The business types of this unit accounted for 0.34% for catering, 0.21% for homestays, 0.27% for retail, and 0.18% for residential life.

[0050] Table 3 Normalized Risk Values ​​of Single Indicators in Different Dimensions

[0051] In the previous governance cycle, 11 hidden dangers in risk unit 7 were closed and 15 hidden dangers were issued, which can be obtained from equation (7). Substituting this result into equation (8), we can obtain the adjusted coupling coefficients as follows: , , , , .

[0052] The building dimension weights are set to [0.32, 0.26, 0.18, 0.24]. Substituting the building dimension data of the 7th unit into equation (4), we get... From equation (5), we obtain Substituting into equation (6) again, we obtain the result. .

[0053] With facility dimension weights set to [0.26, 0.29, 0.25, 0.20], we can obtain... , , The personnel dimension weights are set to [0.36, 0.24, 0.22, 0.18], which yields... , , The environmental dimension weights are set to [0.34, 0.18, 0.30, 0.18], which yields... , , .

[0054] Substituting the proportions of catering, homestays, retail, and residents' daily life into equation (9), we get... .Will , , , , and after compensation Substituting into equation (10), we obtain the coupling enhancement term. .

[0055] Will , , , , , Substituting into equation (11), we obtain the comprehensive risk value of non-diffusion. Assume the weighted average risk of adjacent units is 0.68, and the boundary adjacency weight matrix satisfies... ,Will , Substituting into equation (12), we obtain the final risk value. .

[0056] Based on the risk grading threshold, 0.7391 falls into the range. Within the range, the 7th risk unit is classified as having a higher risk.

[0057] Substituting the risk values ​​of the dimensions into equation (13), we obtain the contribution percentages of the building dimension (0.237), the facility dimension (0.223), the personnel dimension (0.305), and the environment dimension (0.234).

[0058] Step Six: Hazard Identification and Remediation The task list for hazard identification and the feedback results for remediation are shown in Tables 4 and 5. Table 4 Hazard Investigation Task Compilation Table

[0059] Table 5 Governance Feedback Results

[0060] Will , , Substituting the three types of tasks into equation (14) yields their corresponding priority values. The task is listed as "investigate immediately". The task was to be investigated within the same day. Therefore, the 7th risk unit prioritized the verification of electrical load and gas, followed by clearing obstacles in passages and diverting traffic at nodes, and then supplementing monitoring points and increasing the frequency of night patrols.

[0061] After completing the first round of remediation, the input data for the 7th risk unit was updated. The gas usage intensity decreased from 1.31 to 0.73, passenger flow density decreased from 2.86 to 1.94, and rescue arrival time decreased from 228 s to 176 s. Upon entering the next calculation cycle, the calculated hazard closure rate for this unit in the previous cycle increased to [missing value]. The compensation term in equation (8) is no longer triggered, and the coupling coefficient is restored to the base value.

[0062] Furthermore, substituting the treated input back into equations (4) to (12), we obtain... , , , , , , Substituting the risk values ​​before and after treatment into equation (15), we obtain... Based on the risk level threshold, the 7th risk unit has been adjusted from higher risk to medium risk. Daily reviews and nighttime spot checks will continue, but the frequency of increased inspections under the higher risk status will no longer be maintained.

Claims

1. A multi-dimensional coupled risk quantification assessment and dual prevention method for historical and cultural tourism districts, characterized by: Includes the following steps: S1, Collect street data to construct risk units: Obtain multi-dimensional data on buildings, facilities, people and spaces within the street, divide the street and construct several risk units; S2, Multidimensional Risk Factor Extraction and Quantification: Extract building risk factors, facility risk factors, personnel risk factors and environmental operation risk factors for each risk unit, and calculate the risk value of each dimension in combination with the operation period; S3, Risk Coupling Calculation and Identification: Establish the coupling calculation relationship between buildings, facilities, people and environment within the same risk unit, identify the compound risk when multiple types of risks act together, and obtain the final risk value; S4, Risk Classification Assessment and Strategy Control: Based on the risk value range, each risk unit is classified into risk levels, resulting in risk assessment results including low risk, medium risk, relatively high risk and high risk. Executable risk classification control is configured for risk units with different risk assessment results. S5, Hazard Identification and Risk Management: Establish a database of related hazard identification items and management measures in advance, establish a correspondence between risk assessment results and hazard identification items, and form a dual prevention mechanism for street safety that combines risk classification and control with hazard identification and management; S6, Feedback on governance results and risk reassessment: Data is re-collected for risk units after governance by the dual safety prevention mechanism, and the street data in S1 is updated for risk reassessment to form a closed loop.

2. The method for multi-dimensional coupled risk quantification assessment and dual prevention of historical and cultural tourism blocks according to claim 1, characterized in that, In S2: Building risk factors include the following indicators: fire resistance reduction value, component aging and cracking rate, protection operation restrictions, and equivalent combustible load; Facility risk factors include the following indicators: fire protection facility failure rate, electrical load per unit area, gas usage intensity per unit area, and proportion of monitoring blind spots; Personnel risk factors include the following indicators: passenger flow density, average stay time, node clustering degree, and flow direction disturbance degree; Environmental operation risk factors include the following indicators: effective street width constraints, path tortuosity coefficient, rescue arrival time, and temporary road occupancy ratio.

3. The method for multi-dimensional coupled risk quantification assessment and dual prevention of historical and cultural tourism blocks according to claim 1, characterized in that, The risk coupling calculation process in S3 includes: Based on the risk values ​​of each dimension calculated by S2, the power average is used to form the dimension aggregate value, and the discrete terms of the indicators within the same dimension are measured. The aggregate value and the discrete terms are mapped to the dimension sub-risk value. Calculate the hazard closure rate, which reflects the degree of completion of risk unit governance in the previous governance cycle. When the hazard closure rate is higher than the threshold, no compensation item is triggered, and the coupling coefficient is restored to the set base value. When the hazard closure rate is lower than the threshold, the coupling coefficient is increased so that the governance lag results enter the next round of risk calculation. Introduce the entropy value of mixed business operations, and combine it with the coupling coefficient and the dimension sub-risk value to determine the coupling enhancement term; The dimensional sub-risk value and coupling enhancement term are compressed into an undiffused comprehensive risk value, and adjacent unit transmission term and boundary gradient term are introduced to obtain the spatially corrected final risk value.

4. The method for multi-dimensional coupled risk quantification assessment and dual prevention of historical and cultural tourism blocks according to claim 3, characterized in that, The contribution percentage of each dimension is calculated based on the dimensional sub-risk value, which is used to identify the dominant risk dimension.

5. The method for multi-dimensional coupled risk quantification assessment and dual prevention of historical and cultural tourism blocks according to claim 1, characterized in that, Set priority for hazard elimination tasks in the hazard investigation database of S4.

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