Digital twinborn-based tourist attraction disaster experiment deduction method and system

Abstract

The invention relates to the technical field of digital twinning, in particular to a tourist attraction disaster experiment deduction method and system based on digital twinning, and the method comprises the steps: obtaining the geological basic data of a tourist attraction, carrying out the evaluation of the geological basic data of the tourist attraction based on an analytic hierarchy process, dividing the disaster risk regions of the tourist attraction according to the risk degree, and selecting the zone with the highest risk degree to construct a tourist attraction physical model and construct a tourist attraction three-dimensional geological digital model of the zone corresponding to the physical model, and performing mapping matching and data synchronization on the tourist attraction physical model and the tourist attraction three-dimensional geological digital model to form a digital twin system. The disaster scene is subjected to experimental deduction through a digital twin system, and accurate prediction of the tourist attraction disaster evolution process is completed. Through the construction of the digital twin system, the real-time mapping and synchronization of the tourist attraction geological model and the three-dimensional digital model are realized, and the accuracy and timeliness of disaster risk assessment are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a method and system for conducting a disaster experiment simulation in a tourist attraction based on digital twins. Background Art

[0002] With the rapid development of tourism, the prevention and control of geological disasters in scenic spots has become an important part of ensuring the safety of tourists and the sustainable development of scenic spots. Obtaining accurate basic geological data is a prerequisite for disaster risk assessment. At present, traditional geological disaster prevention and control technologies in tourist attractions mainly rely on regular on-site surveys and static data analysis. Not only is the data collection cycle long, it is difficult to reflect the dynamic changes of the geological environment in a timely manner, resulting in risk assessment lagging behind the actual situation, and its ability in disaster simulation and evolution prediction is limited, and it is unable to provide comprehensive disaster scenario simulation, which limits the foresight and pertinence of prevention and control measures. In addition, due to the lack of effective real-time monitoring and feedback mechanisms, traditional geological disaster prevention and control technologies in tourist attractions are difficult to respond to sudden disasters in a timely manner, which weakens the efficiency and effectiveness of disaster emergency management. Therefore, in order to overcome the obvious deficiencies of traditional geological disaster prevention and control technologies in tourist attractions in terms of data real-time, comprehensive analysis capabilities and disaster prediction accuracy, we designed a tourist scenic area disaster experiment simulation method and system based on digital twins. Summary of the invention

[0003] The purpose of the present invention is to provide a tourist attraction disaster experiment simulation method and system based on digital twins, which realizes the real-time mapping and synchronization of the geological model of the tourist attraction and the three-dimensional digital model through the construction of a digital twin system, significantly improving the accuracy and timeliness of disaster risk assessment.

[0004] The present invention is achieved through the following technical solutions: A tourist scenic spot disaster experimental simulation method based on digital twins, the method comprises the following steps: Obtain basic geological data of tourist attractions, evaluate them based on the analytic hierarchy process, and divide the disaster risk zones of tourist attractions according to the degree of risk; Based on the basic geological data of the tourist attraction, the most dangerous sub-area is selected to construct the physical model of the tourist attraction; Based on the basic geological data of the tourist scenic area, a three-dimensional geological digital model of the tourist scenic area corresponding to the physical model is constructed through GIS; Mapping and matching the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; Real-time monitoring data is collected by sensor units installed in tourist attractions, and disaster scenarios are experimentally simulated through the digital twin system to accurately predict the evolution process of disasters in tourist attractions.

[0005] Optionally, the evaluation of the geological basic data of the tourist attraction based on the hierarchical analysis method is specifically as follows: Acquire topographic data, stratigraphic lithology data and geological structure data of tourist attractions, and integrate them into the basic geological data of the tourist attractions; Construct a judgment matrix based on the geological basic data of the tourist attraction, calculate the weight vector of each layer of the judgment matrix, and calculate the maximum eigenvalue of the judgment matrix based on the weight vector; The consistency test of the judgment matrix is ​​carried out through the maximum eigenvalue root to solve the geological disaster risk degree of the tourist attraction.

[0006] Optionally, the selection of the most dangerous sub-area based on the basic geological data of the tourist attraction to construct a physical model of the tourist attraction is specifically as follows: According to the geological disaster risk level of tourist attractions, they are divided into the highest risk zone, the medium risk zone and the lowest risk zone from high to low; Select the zone with the highest risk, obtain basic data of the zone with the highest risk, and determine the similarity ratio of the physical model of the tourist attraction according to the basic data of the zone with the highest risk; The similarity ratio of the physical model of the tourist attraction is converted into mechanical parameters, and the mechanical parameters are combined to complete the construction of the physical model of the tourist attraction.

[0007] Optionally, the similarity ratio of the physical model of the tourist attraction includes: geometric similarity ratio, weight similarity ratio, intensity similarity ratio and coupling similarity ratio; Wherein, the geometric similarity ratio is calculated as follows:

[0008] in, is the geometric similarity ratio, is the linear size of the most dangerous zone, is the linear size of the physical model of the tourist attraction; The calculation formula of the severe similarity ratio is:

[0009] in, is the heavy similarity ratio, The material weight of the most dangerous zone is The material weight of the physical model of the tourist attraction; The intensity similarity ratio is calculated as follows:

[0010] in, is the intensity similarity ratio; The coupling similarity ratio is calculated as follows:

[0011] in, is the coupling similarity ratio, , are the adjustment coefficients, , , .

[0012] Optionally, based on the basic geological data of the tourist attraction, a three-dimensional geological digital model of the tourist attraction divided into zones corresponding to the physical model is constructed through GIS, which is specifically: Obtain basic data of the most dangerous zone; In the GIS system, a digital elevation model is constructed based on the basic data of the most dangerous zone, and a grid model of the tourist attraction is formed through three-dimensional discretization; The similarity ratio of the grid model of the tourist attraction is mapped with the physical model of the tourist attraction, the grid model of the tourist attraction is rendered in three dimensions, and the maximization of comprehensive fitness is defined as the optimization goal to complete the construction of the three-dimensional geological digital model of the tourist attraction.

[0013] Optionally, the optimization goal is to maximize the comprehensive fitness, and the calculation formula is:

[0014] in, is the objective function, is the comprehensive fitness function, ranging from (0,1], is the measured value, is the predicted value, M is the total number of measurement points, is a positive number, is the change of the kth parameter between the nth iteration and the n−1th iteration, , is the kth parameter, is the weight of the kth parameter, and K is the total number of parameters.

[0015] Optionally, the mapping and matching of the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization are specifically: mapping and data synchronization of the similarity ratio of the three-dimensional geological digital model of the tourist attraction with the physical model of the tourist attraction, and the calculation formula is:

[0016]

[0017]

[0018] in, is the parameter of the three-dimensional geological digital model of the tourist attraction, C is the total similarity ratio scaling factor, are the parameters of the physical model of the tourist attraction, are the geometric scaling exponent, weight scaling exponent, intensity scaling exponent and coupling scaling exponent of parameter k, is the real-time measurement data of the three-dimensional geological digital model of the tourist attraction, S is the data synchronization scaling factor, Real-time measurement data for the physical model of tourist attractions.

[0019] The tourist scenic area disaster experiment simulation system based on digital twin includes: The data collection unit obtains the basic geological data of the tourist attractions, evaluates the basic geological data of the tourist attractions based on the analytic hierarchy process, and divides the disaster risk zones of the tourist attractions according to the risk level; The physical model building unit selects the most dangerous zone based on the basic geological data of the tourist attraction to build the physical model of the tourist attraction; The digital model building unit, based on the basic geological data of the tourist scenic area, constructs a three-dimensional geological digital model of the tourist scenic area corresponding to the physical model through GIS; The data twin unit maps and matches the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and synchronizes the data to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; The simulation unit collects real-time monitoring data based on the sensor units deployed in the tourist scenic area, and conducts experimental simulation of disaster scenarios through the digital twin system to accurately predict the evolution process of disasters in the tourist scenic area.

[0020] The technical solution of the present invention has at least the following advantages and beneficial effects: On the one hand, the present invention realizes the real-time mapping and synchronization of the geological model of the tourist scenic spot and the three-dimensional digital model through the construction of the digital twin system, which significantly improves the accuracy and timeliness of disaster risk assessment; on the other hand, through the hierarchical analysis method and GIS system, it comprehensively evaluates and accurately divides the disaster risk zones to ensure the key monitoring of key areas. The real-time data of the integrated sensors supports dynamic updates and disaster scenario simulation, and enhances the ability to predict the evolution of disasters. In addition, the digital twin system designed by the present invention can effectively reduce the frequency and cost of on-site surveys, improve data processing efficiency, promote the scientific formulation and implementation of disaster prevention and control measures, and comprehensively improve the safety management level and emergency response capabilities of the scenic area. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A logical schematic diagram of the tourist attraction disaster experimental simulation method based on digital twins provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, what is described is only a part of the present invention, not all of it. Generally, the components of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0023] Reference Figure 1 As shown, Figure 1 A logical schematic diagram of the tourist attraction disaster experimental simulation method based on digital twins provided by the present invention.

[0024] In one embodiment, the present invention provides a tourist attraction disaster experimental simulation method based on digital twins, the method comprising the following steps: Obtain basic geological data of tourist attractions, evaluate them based on the analytic hierarchy process, and divide the disaster risk zones of tourist attractions according to the degree of risk; Based on the basic geological data of the tourist attraction, the most dangerous sub-area is selected to construct the physical model of the tourist attraction; Based on the basic geological data of the tourist scenic area, a three-dimensional geological digital model of the tourist scenic area corresponding to the physical model is constructed through GIS; Mapping and matching the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; Real-time monitoring data is collected by sensor units installed in tourist attractions, and disaster scenarios are experimentally simulated through the digital twin system to accurately predict the evolution process of disasters in tourist attractions.

[0025] In the specific implementation of the above-mentioned embodiment, in order to effectively construct and implement the geological disaster prevention and control system of tourist attractions, this embodiment uses a variety of means to collect data comprehensively, including comprehensive on-site surveys by professional geological teams, detailed records of key data such as geological structure, rock and soil layers and fault distribution; using satellite remote sensing and drone aerial photography technology to obtain high-resolution topographic maps and geological feature maps to supplement and enrich on-site data; and collecting historical geological disaster records, meteorological data and hydrological data of tourist attractions to form the geological basic data of tourist attractions. After pre-processing, the comprehensive score of the danger degree of tourist attractions is calculated based on the hierarchical analysis method, divided into three levels of high, medium and low disaster danger zones, and marked on the geological map to provide a basis for the selection of high-risk areas and the construction of physical models. After selecting the high-risk zone, simulate the stratigraphic structure, fault plane and hydrological conditions, construct a physical model, and test the stability and accuracy of the model. At the same time, a three-dimensional geological digital model is constructed using a geographic information system (GIS), and the organized geological data is imported. The three-dimensional terrain and geological layer distribution are established by combining the digital elevation model (DEM) and the digital surface model (DSM), and the geological fault and other structures are accurately modeled. The model details are optimized and the visualization effect is enhanced. After the three-dimensional geological digital model is completed, a digital twin system is constructed, and the key parameters of the physical model and the digital model are aligned by mapping and matching, and a real-time data connection is established. Finally, real-time monitoring and disaster prediction are carried out based on the digital twin system. Sensors such as stress and strain sensors, piezometers and seismometers are selected and deployed in high-risk areas, and a data acquisition and transmission system is established. The data of different sensors are cleaned, filtered and integrated to build a comprehensive geological parameter database. Based on the processed data, the disaster scenario parameters are set, the disaster scenario is simulated through the digital twin system, the risk points are identified and early warning information is issued, management and emergency response are guided, and the system is continuously optimized. The model parameters are adjusted through feedback to ensure that the system accurately reflects the dynamic changes of the geology. This embodiment achieves a high degree of consistency and real-time interaction between physical and digital models through digital twin technology, which significantly enhances the scientificity and timeliness of disaster prediction, ensures the safety of tourists, and promotes the sustainable development of the tourism industry.

[0026] Furthermore, the evaluation of the geological basic data of the tourist attraction based on the hierarchical analysis method is specifically as follows: Acquire topographic data, stratigraphic lithology data and geological structure data of tourist attractions, and integrate them into the basic geological data of the tourist attractions; Construct a judgment matrix based on the geological basic data of the tourist attraction, calculate the weight vector of each layer of the judgment matrix, and calculate the maximum eigenvalue of the judgment matrix based on the weight vector; The consistency test of the judgment matrix is ​​carried out through the maximum eigenvalue root to solve the geological disaster risk degree of the tourist attraction.

[0027] In the implementation, this embodiment first constructs an evaluation index hierarchy structure, subdividing the risk-related factors (such as geological structure, lithology, terrain slope, hydrological characteristics, etc.) into multi-level indicators to form an AHP hierarchy. Constructing a judgment matrix , for each level of indicators, two-to-two comparisons are made, among which, Represents the importance score of the i-th indicator relative to the j-th indicator, and calculates the weight vector , the weight vector is specifically the eigenvector of the judgment matrix, satisfying the characteristic equation: ,in, is the maximum characteristic root of the judgment matrix. And perform consistency test and solve the consistency index and consistency ratio , where n is the dimension of the judgment matrix, is the random consistency indicator. Calculate the relative weight of each indicator again : ,in, is the normalized weight vector, satisfying , and finally solve the comprehensive score of geological disaster risk in tourist attractions: ,in, is the standardized score of the jth area on the i-th indicator. According to the hazard threshold, the tourist attractions are divided into three levels of disaster hazard zones: high, medium, and low, and marked on the GIS.

[0028] In this embodiment, the construction of the physical model of the tourist attraction is carried out by selecting the most dangerous zone based on the geological basic data of the tourist attraction, which is specifically: According to the geological disaster risk level of tourist attractions, they are divided into the highest risk zone, the medium risk zone and the lowest risk zone from high to low; Select the zone with the highest risk, obtain basic data of the zone with the highest risk, and determine the similarity ratio of the physical model of the tourist attraction according to the basic data of the zone with the highest risk; The similarity ratios of the physical model of tourist attractions include: geometric similarity ratio, weight similarity ratio, intensity similarity ratio and coupling similarity ratio; Wherein, the geometric similarity ratio is calculated as follows:

[0029] in, is the geometric similarity ratio, is the linear size of the most dangerous zone, is the linear size of the physical model of the tourist attraction; The calculation formula of the severe similarity ratio is:

[0030] in, is the heavy similarity ratio, The material weight of the most dangerous zone is The material weight of the physical model of the tourist attraction; The intensity similarity ratio is calculated as follows:

[0031] in, is the intensity similarity ratio; The coupling similarity ratio is calculated as follows:

[0032] in, is the coupling similarity ratio, , are the adjustment coefficients, Used to control the weight and nonlinear penalty of each similarity ratio in the logarithmic term, It is used to determine the amplification or attenuation effect of the comprehensive results of each similarity comparison in the exponential term. , , ; The similarity ratio of the physical model of the tourist attraction is converted into mechanical parameters, and the mechanical parameters are combined to complete the construction of the physical model of the tourist attraction.

[0033] In the specific implementation, after completing the hazard assessment and zoning, the zoning with the highest hazard is selected as the basis for constructing the physical model, and the key indicators such as the core geology, topography and lithology of the high-risk zoning are extracted. In combination with the experimental purpose and site conditions, the boundary size, geometric shape and sensor layout of the physical model are determined. Based on the coupled similarity ratio formula of this embodiment, the nonlinear relationship between multiple similarity ratios is comprehensively considered to achieve fine adjustment of the parameters of the physical model of the tourist attraction. This embodiment converts the mechanical parameters of the prototype rock mass of the tourist attraction into the corresponding parameters of the physical model of the tourist attraction based on the coupled similarity ratio:

[0034]

[0035]

[0036]

[0037]

[0038] in, They are the compressive stress, cohesion, internal friction angle, elastic modulus and Poisson's ratio mechanical parameters of the prototype rock mass in the tourist area. They are respectively the compressive stress, cohesion, internal friction angle, elastic modulus and Poisson’s ratio mechanical parameters corresponding to the physical model of the tourist attraction.

[0039] In this embodiment, based on the geological basic data of the tourist attraction, a three-dimensional geological digital model of the tourist attraction corresponding to the physical model is constructed through GIS, which is specifically: Obtain basic data of the most dangerous zone; In the GIS system, a digital elevation model is constructed based on the basic data of the most dangerous zone, and a grid model of the tourist attraction is formed through three-dimensional discretization;

[0040]

[0041] in, is the elevation value of the i-th known sampling point, is the distance from the i-th sampling point to the interpolation point (x, y), p is the distance weight index, is the grid index, corresponding to the three-dimensional coordinate ( ), For Grid The set of geological properties at the location, such as density, strength, permeability, etc.; The similarity ratio of the grid model of the tourist attraction is mapped with the physical model of the tourist attraction, the grid model of the tourist attraction is rendered in three dimensions, and the maximization of comprehensive fitness is defined as the optimization goal to complete the construction of the three-dimensional geological digital model of the tourist attraction.

[0042] During implementation, the digital model construction generates a digital elevation model through an interpolation algorithm, determines the depth of each rock layer based on the drilling data, and draws the stratigraphic profile and vertical stratification in GIS in combination with the digital elevation model data. The grid is divided by a three-dimensional discretization method, and the geological attributes (such as density, strength, permeability, etc.) are assigned to the corresponding grid. Finally, the similarity ratio mapping of geometric and mechanical parameters is used to ensure the consistency of the digital model with the physical model in terms of spatial size and material properties, and realize digital twin or synchronous analysis.

[0043] Specifically, the optimization goal is to maximize the comprehensive fitness, and the calculation formula is:

[0044] in, is the objective function, is the comprehensive fitness function, ranging from (0,1], is the measured value, is the predicted value, M is the total number of measurement points, is a positive number, is the change of the kth parameter between the nth iteration and the n−1th iteration, , is the kth parameter, such as elastic modulus, cohesion, internal friction angle, permeability coefficient, etc., is the weight of the kth parameter, and K is the total number of parameters.

[0045] The objective function of this embodiment aims to optimize the digital model so that it achieves the best balance between matching and stability. The comprehensive fitness function is composed of the weighted sum of matching and stability. The matching measures the degree of agreement between the model prediction value and the measured value. The smaller the error, the higher the matching degree; the stability evaluates the change range of the model parameters during the iteration process. The smaller the change, the higher the stability. By maximizing the objective function, the model is prompted to accurately reflect the actual geological conditions while maintaining the stability of the numerical calculation, thereby improving the accuracy and reliability of the model.

[0046] More specifically, the mapping and matching of the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization are specifically as follows: the similarity ratio of the three-dimensional geological digital model of the tourist attraction is mapped and data synchronized with the physical model of the tourist attraction, and the calculation formula is:

[0047]

[0048]

[0049] in, is the parameter of the three-dimensional geological digital model of the tourist attraction, C is the total similarity ratio scaling factor, are the parameters of the physical model of the tourist attraction, are the geometric scaling exponent, weight scaling exponent, intensity scaling exponent and coupling scaling exponent of parameter k, is the real-time measurement data of the three-dimensional geological digital model of the tourist attraction, S is the data synchronization scaling factor, Real-time measurement data for the physical model of tourist attractions.

[0050] In the specific application of this embodiment, this embodiment collects geological parameter data in real time by deploying sensors (such as stress strain sensors and piezometers), and constructs a three-dimensional geological digital model based on the initial geological data to set key parameters. The physical model parameters are mapped to the digital model using the similarity ratio to ensure the correspondence between scale and material properties, and the real-time monitoring data of the physical model is converted and synchronized to the digital model to maintain the consistency of the data of the two, and the comprehensive fitness function is calculated. The geological parameters are adjusted by the optimization algorithm to maximize the matching degree and stability. After the parameter optimization is completed, the disaster simulation is performed in the digital model according to the set disaster scenario (such as earthquake, landslide, mudslide), and the changes in parameters such as stress, strain, displacement and water flow are calculated using finite element analysis or other numerical simulation tools. Finally, the simulation results are analyzed to identify the trend and impact area of ​​the disaster development, predict key events and time nodes, and feed the results back to the model correction and continuous optimization link to ensure the accuracy of the prediction and the dynamic update of the model.

[0051] In another embodiment, the present invention provides a tourist attraction disaster experiment simulation system based on digital twins, including: The data collection unit obtains the basic geological data of the tourist attractions, evaluates the basic geological data of the tourist attractions based on the analytic hierarchy process, and divides the disaster risk zones of the tourist attractions according to the risk level; The physical model building unit selects the most dangerous zone based on the basic geological data of the tourist attraction to build the physical model of the tourist attraction; The digital model building unit, based on the basic geological data of the tourist scenic area, constructs a three-dimensional geological digital model of the tourist scenic area corresponding to the physical model through GIS; The data twin unit maps and matches the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and synchronizes the data to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; The simulation unit collects real-time monitoring data based on the sensor units deployed in the tourist scenic area, and conducts experimental simulation of disaster scenarios through the digital twin system to accurately predict the evolution process of disasters in the tourist scenic area.

[0052] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A tourist scenic area disaster experimental simulation method based on digital twins, characterized in that: The steps of the method include: Obtain basic geological data of tourist attractions, evaluate them based on the analytic hierarchy process, and divide the disaster risk zones of tourist attractions according to the degree of risk; Based on the basic geological data of the tourist attraction, the most dangerous sub-area is selected to construct the physical model of the tourist attraction; Based on the basic geological data of the tourist attraction, a three-dimensional geological digital model of the tourist attraction corresponding to the physical model is constructed through GIS; Mapping and matching the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; Real-time monitoring data is collected by sensor units installed in tourist attractions, and disaster scenarios are experimentally simulated through the digital twin system to accurately predict the evolution process of disasters in tourist attractions.

2. The tourist attraction disaster experimental simulation method based on digital twin according to claim 1 is characterized in that: The evaluation of the geological basic data of the tourist attraction based on the hierarchical analysis method is specifically as follows: Acquire topographic data, stratigraphic lithology data and geological structure data of tourist attractions, and integrate them into the basic geological data of the tourist attractions; Construct a judgment matrix based on the geological basic data of the tourist attraction, calculate the weight vector of each layer of the judgment matrix, and calculate the maximum eigenvalue of the judgment matrix based on the weight vector; The consistency test of the judgment matrix is ​​carried out through the maximum eigenvalue root to solve the geological disaster risk degree of the tourist attraction.

3. The tourist scenic area disaster experimental simulation method based on digital twin according to claim 2 is characterized in that: The method of selecting the most dangerous zone based on the basic geological data of the tourist attraction to construct the physical model of the tourist attraction is as follows: According to the geological disaster risk level of tourist attractions, they are divided into the highest risk zone, the medium risk zone and the lowest risk zone from high to low; Select the zone with the highest risk, obtain basic data of the zone with the highest risk, and determine the similarity ratio of the physical model of the tourist attraction according to the basic data of the zone with the highest risk; The similarity ratio of the physical model of the tourist attraction is converted into mechanical parameters, and the mechanical parameters are combined to complete the construction of the physical model of the tourist attraction.

4. The tourist scenic area disaster experimental simulation method based on digital twin according to claim 3 is characterized in that: The similarity ratios of the physical model of the tourist attraction include: geometric similarity ratio, weight similarity ratio, intensity similarity ratio and coupling similarity ratio; Wherein, the geometric similarity ratio is calculated as follows: in, is the geometric similarity ratio, is the linear size of the most dangerous zone, is the linear size of the physical model of the tourist attraction; The calculation formula of the severe similarity ratio is: in, is a heavy similarity ratio, The material weight of the most dangerous zone is The material weight of the physical model of the tourist attraction; The intensity similarity ratio is calculated as follows: in, is the intensity similarity ratio; The coupling similarity ratio is calculated as follows: in, is the coupling similarity ratio, , are the adjustment coefficients, , , .

5. The tourist scenic area disaster experimental simulation method based on digital twin according to claim 4 is characterized in that: The three-dimensional geological digital model of the tourist attraction corresponding to the physical model is constructed by GIS based on the geological basic data of the tourist attraction, which is specifically: Obtain basic data of the most dangerous zone; In the GIS system, a digital elevation model is constructed based on the basic data of the most dangerous zone, and a grid model of the tourist attraction is formed through three-dimensional discretization; The similarity ratio of the grid model of the tourist attraction is mapped with the physical model of the tourist attraction, the grid model of the tourist attraction is rendered in three dimensions, and the maximization of comprehensive fitness is defined as the optimization goal to complete the construction of the three-dimensional geological digital model of the tourist attraction.

6. The tourist attraction disaster experimental simulation method based on digital twin according to claim 5 is characterized in that: The optimization goal is to maximize the comprehensive fitness, and the calculation formula is: in, is the objective function, is the comprehensive fitness function, ranging from (0,1], is the measured value, is the predicted value, M is the total number of measurement points, is a positive number, is the change of the kth parameter between the nth iteration and the n−1th iteration, , is the kth parameter, is the weight of the kth parameter, and K is the total number of parameters.

7. The tourist attraction disaster experimental simulation method based on digital twin according to claim 6 is characterized in that: The mapping and matching of the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and data synchronization are specifically: mapping and data synchronization of the similarity ratio of the three-dimensional geological digital model of the tourist attraction with the physical model of the tourist attraction, and the calculation formula is: in, is the parameter of the three-dimensional geological digital model of the tourist attraction, C is the total similarity ratio scaling factor, are the parameters of the physical model of the tourist attraction, are the geometric scaling exponent, weight scaling exponent, intensity scaling exponent and coupling scaling exponent of parameter k, is the real-time measurement data of the three-dimensional geological digital model of the tourist attraction, S is the data synchronization scaling factor, Real-time measurement data for the physical model of tourist attractions.

8. The tourist scenic area disaster experiment simulation system based on digital twin is characterized by: include: The data collection unit obtains the basic geological data of the tourist attractions, evaluates the basic geological data of the tourist attractions based on the analytic hierarchy process, and divides the disaster risk zones of the tourist attractions according to the risk level; The physical model building unit selects the most dangerous zone based on the basic geological data of the tourist attraction to build the physical model of the tourist attraction; The digital model building unit, based on the basic geological data of the tourist scenic area, constructs a three-dimensional geological digital model of the tourist scenic area corresponding to the physical model through GIS; The data twin unit maps and matches the physical model of the tourist attraction with the three-dimensional geological digital model of the tourist attraction and synchronizes the data to form a digital twin system of the physical model of the tourist attraction and the three-dimensional geological digital model of the tourist attraction; The simulation unit collects real-time monitoring data based on the sensor units deployed in the tourist scenic area, and conducts experimental simulations of disaster scenarios through the digital twin system to accurately predict the evolution process of disasters in the tourist scenic area.

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