Fire evacuation optimization method and device based on texture protection of historical block

Abstract

The present invention provides a method and device for optimizing fire evacuation in historical blocks based on texture preservation, comprising: step S1 extracting architectural data of a target historical block from a floor plan; step S2 calculating an initial renovation plan based on the architectural data; step S3 randomly selecting a batch of buildings from the target historical block and deleting the data corresponding to these buildings from the architectural data to obtain architectural data for the current iteration; step S4 calculating a renovation plan for the current iteration based on the architectural data; step S5 determining whether to terminate the iteration based on the renovation plan for the current iteration, the renovation plan for the previous iteration, the initial renovation plan, and a preset termination condition; if so, executing step S6; if not, executing step S3; and step S6 calculating the optimal renovation plan based on all renovation plans. In summary, this method can generate an optimal renovation plan for a historical block that takes into account both fire evacuation and traditional texture preservation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of urban planning, urban disaster prevention planning and fire protection technology, and particularly relates to a historical block fire evacuation optimization method and device based on texture protection. BACKGROUND

[0002] Under the background of urban cultural heritage protection and modern urban development, the renewal and development of historical blocks bring about business format adjustment and large flow, which may cause fire safety problems. As an important carrier of urban culture, the unique architectural style and historical value of historical blocks require us to consider both the protection of historical style and the safe evacuation of personnel in emergency situations when planning fire evacuation.

[0003] In the existing process of historical block fire evacuation reconstruction, the following problems have appeared: 1) the narrow streets and complex building layout hinder emergency evacuation, resulting in too long evacuation time; 2) the streets are widened and buildings are demolished, causing great damage to the traditional texture of the block.

[0004] Currently, existing research either starts from the fire safety of historical blocks, proposes corresponding fire reconstruction strategies by establishing a fire risk assessment model, or starts from the evacuation capacity, optimizes evacuation routes and time through simulation by GIS, spatial syntax, FDS and other software. However, these researches lack a comprehensive optimization method that combines protection and disaster prevention from the perspective of traditional texture protection.

[0005] Traditional texture is the most core element in the protection of historical blocks, but most of the current measurement and quantification of traditional texture are focused on qualitative research. For example, from the perspective of typology, the physical characteristics such as building form and street pattern are used to identify and classify urban texture. This method helps to understand the historical development and cultural characteristics of the city, but it is limited to specific plots, lacks a standard paradigm, and is difficult to generalize. Some scholars regard urban texture as a complex network and use network percolation theory to identify and measure urban texture, but this method is currently only applied to large-scale research and ignores the influence of building orientation and building form on texture connection, so it is not suitable for small-scale research. Therefore, there is currently a lack of a paradigm method that can measure texture at a small-scale block.

[0006] In summary, the existing historical block fire evacuation still has the following problems: (1) how to quantitatively measure the traditional texture of the block at a small scale; (2) how to provide an optimal solution that takes into account fire evacuation and traditional texture protection. SUMMARY

[0007] The present application is made to solve the above problems, and aims to provide a historical block fire evacuation optimization method and device based on texture protection.

[0008] The present invention provides a fire evacuation optimization method for a historical block based on texture protection, which is used to obtain an optimal renovation plan based on the floor plan and evacuation data of a target historical block. The method has the following characteristics: step S1, extracting the building data of the target historical block from the floor plan; step S2, calculating and obtaining a corresponding renovation plan based on the building data as an initial renovation plan; step S3, randomly selecting a group of buildings from the target historical block, and deleting the data corresponding to the group of buildings from the building data to obtain the building data of the current iteration round; step S4, calculating and obtaining a renovation plan of the current iteration round based on the building data of the current iteration round; step S5, calculating and obtaining a renovation plan of the current iteration round based on the renovation plan of the previous iteration round and the renovation plan of the current iteration round. The transformation plan, the initial transformation plan and the preset termination condition are used to determine whether to terminate the iteration. If so, step S6 is executed, and if not, step S3 is executed; in step S6, the most balanced transformation plan is calculated as the optimal transformation plan based on all the transformation plans, wherein the transformation plan includes building data, average texture robustness and the evacuation time of the entire population. The specific process of calculating the transformation plan based on the building data includes the following steps: step T1, constructing a nearest neighbor building texture network based on the building data; step T2, calculating the average texture robustness based on the nearest neighbor building texture network by the urban texture multi-scale resilience measurement method; step T3, calculating the evacuation time of the entire population based on the evacuation data and the building data.

[0009] The historical block fire evacuation optimization method based on texture protection provided by the present invention may also have the following characteristics: wherein, the nearest neighbor building texture network includes multiple nodes, edges between nodes and weights corresponding to the edges, the nodes are building particles in the building data, and the edges are connections between buildings in the building data.

[0010] The fire evacuation optimization method for historical blocks based on texture protection provided by the present invention may also have the following features: wherein the building data includes the perimeter, azimuth and area of ​​the building, and the weight calculation expression is: W ij =S ij +D ij +DI i , S ij =|S j -S i |, D ij =|D j -D i |, where W ij is the weight between building i and building j, S ij is the shape difference between building i and building j, S i is the shape index of building i, Pi is the perimeter of the building i, A i is the area of the building i, D ij is the orientation difference between the building i and the building j, D i is the azimuth angle of the building i, DI i is the nearest neighbor distance.

[0011] In the historical block fire evacuation optimization method based on texture protection provided by the application, the step T2 can further have the following characteristics: the step T2 includes the following sub-steps: step T2-1, removing edges in the nearest neighbor building texture network that are greater than a selected threshold value to obtain a plurality of mutually unconnected texture clusters; step T2-2, obtaining a plurality of key threshold values according to the largest texture cluster and the second largest texture cluster; and step T2-3, calculating the average texture robustness by the urban texture multi-scale robustness measurement method according to all the key threshold values and the nearest neighbor building texture network.

[0012] In the historical block fire evacuation optimization method based on texture protection provided by the application, the average texture robustness can be calculated according to the following expression: In the formula, R ij is the robustness strength of the texture connection between the building i and the building j in the building data of the current iteration round, D is the number of key threshold values, is the size of the texture cluster to which the texture connection between the building i and the building j belongs under the tth key threshold value, is the size of the largest texture cluster under the tth key threshold value, and n is the number of edges in the nearest neighbor building texture network.

[0013] In the historical block fire evacuation optimization method based on texture protection provided by the application, the evacuation data can include the number of evacuees, the speed of evacuees, and the evacuation entrance, and in the step T3, the evacuees are evenly distributed in each street and alley corresponding to the building data of the current iteration round, and the shortest path algorithm is used to calculate the total population evacuation time.

[0014] In the historical block fire evacuation optimization method based on texture protection provided by the application, the preset termination condition can be that the average texture robustness corresponding to the current iteration round is greater than the average texture robustness corresponding to the initial modification scheme, and the improvement value of the total population evacuation time corresponding to the current iteration round compared to the total population evacuation time corresponding to the last iteration round is greater than a preset improvement threshold value.

[0015] In the historical block fire evacuation optimization method based on texture protection provided by the application, the improvement value can be calculated according to the following expression: In the formula, a is a promotion value, b is the evacuation time of the entire population corresponding to the previous iteration round, c is the evacuation time of the entire population corresponding to the current iteration round, and the preset promotion threshold is 3%.

[0016] The application also provides a historical block fire evacuation optimization device based on texture protection, which is used to obtain an optimal reconstruction scheme according to the plan and evacuation data of a target historical block, and has the characteristics that it comprises a building data extraction module, a scheme calculation module, a building removal module, an iteration judgment module, an iteration control module and a balanced solution calculation module, wherein the building data extraction module is used to extract the building data of the target historical block from the plan, the scheme calculation module is used to calculate the corresponding reconstruction scheme according to the building data, the building removal module is used to randomly select a batch of buildings from the target historical block and delete the data corresponding to the batch of buildings from the building data to obtain the building data of the current iteration round, the iteration judgment module stores a preset termination condition and is used to judge whether to terminate the iteration according to the reconstruction scheme of the current iteration round, the reconstruction scheme of the previous iteration round, the initial reconstruction scheme and the preset termination condition, and the iteration control module is used to control the scheme calculation module to calculate the corresponding reconstruction scheme according to the building data as the initial reconstruction scheme and control the building removal module, the scheme calculation module and the iteration judgment module to perform multiple iterations to calculate the reconstruction scheme of each iteration round, and the balanced solution calculation module is used to calculate the most balanced reconstruction scheme as the optimal reconstruction scheme according to all the reconstruction schemes, wherein the reconstruction scheme comprises the building data, the average texture robustness and the evacuation time of the entire population, and the scheme calculation module comprises a nearest neighbor building texture network generation unit, which is used to construct a nearest neighbor building texture network according to the building data of the current iteration round, a texture measure unit, which is used to calculate the average texture robustness by a city texture multi-scale robustness measure method according to the nearest neighbor building texture network, and an evacuation time simulation unit, which is used to calculate the evacuation time of the entire population according to the evacuation data and the building data of the current iteration round.

[0017] Effects of the application

[0018] According to the historical block fire evacuation optimization method and device based on texture protection, on the one hand, the internal shape elements and the orientation elements are considered to affect the texture measure, so that the measure result of the historical block texture is more accurate; on the other hand, the preset termination condition and the random building removal are used to obtain the optimal reconstruction scheme after multiple iterations and save manpower. Therefore, the historical block fire evacuation optimization method and device based on texture protection can generate the optimal reconstruction scheme that takes into account the fire evacuation and the traditional texture protection. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a block diagram of the texture protection based historical block fire evacuation optimization device in the embodiment of the present application;

[0020] Figure 2 is a schematic diagram of the nearest neighbor building texture network of Tianzifang in the embodiment of the present application;

[0021] Figure 3 is a flowchart of the texture measure unit calculating the texture average robustness in the embodiment of the present application;

[0022] Figure 4 is a schematic diagram of the key threshold in the embodiment of the present application;

[0023] Figure 5 is a schematic diagram of the Tianzifang evacuation exit setting in the embodiment of the present application;

[0024] Figure 6 is a flowchart of the texture protection based historical block fire evacuation optimization method in the embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the technical means, creative features, purposes and effects of the present application easy to understand, the following embodiments combine the drawings to specifically describe the texture protection based historical block fire evacuation optimization method and device of the present application.

[0026] In the embodiment, a texture protection based historical block fire evacuation optimization device is provided, which is used to obtain an optimal reconstruction scheme according to a plan and evacuation data of a target historical block. The evacuation data includes the number of evacuees, the speed of evacuees and the evacuation entrance and exit. In the embodiment, the target historical block is Tianzifang.

[0027] Figure 1 is a block diagram of the texture protection based historical block fire evacuation optimization device in the embodiment of the present application.

[0028] As shown in Figure 1 , the texture protection based historical block fire evacuation optimization device 100 includes a building data extraction module 10, a scheme calculation module 20, a building demolition module 30, an iteration judgment module 40, an iteration control module 50, a balanced solution calculation module 60 and a general control module 70 for controlling the operation of the above modules.

[0029] The building data extraction module 10 is used to extract the building data of the target historical block from the plan. The building data includes the perimeter, azimuth angle and area of the building.

[0030] The scheme calculation module 20 is configured to calculate the corresponding reconstruction scheme according to the building data. The reconstruction scheme includes the building data, the average robustness of the texture and the total population evacuation time.

[0031] The scheme calculation module 20 includes a nearest neighbor building texture network generation unit 201, a texture measure unit 202 and an evacuation time simulation unit 203.

[0032] The nearest neighbor building texture network generation unit 201 is configured to construct a nearest neighbor building texture network according to the building data of the current iteration round.

[0033] Figure 2 FIG. 1 is a schematic diagram of the nearest neighbor building texture network of Tianzifang in an embodiment of the present application.

[0034] As shown in FIG. 1, the nearest neighbor building texture network includes a plurality of nodes, edges between the nodes and weights corresponding to the edges. The nodes are building particles in the building data, and each building particle represents a corresponding building unit. The edges, i.e., the building nearest neighbor connections, are the connections between the buildings in the building data. The building particles are generated by the building contour information, and the nearest neighbor building texture network is generated by using the Delaunay triangle network. The weight of the edge represents the connection strength between the adjacent buildings. The building plan is a roof plan of the Tianzifang region, which expresses the orientation, position and basic situation of the surrounding environment of each building.

[0035] The calculation expression of the weight is as follows:

[0036] W ij = S ij + D ij + DI i ,

[0037] S ij = |S j - S i |,

[0038]

[0039] D ij = |D j - D i |,

[0040] wherein W ij is the weight between the building i and the building j, S ij is the shape difference between the building i and the building j, S i is the shape index of the building i, P i is the perimeter of the building i, A i is the area of the building i, D ij is the orientation difference between the building i and the building j, and D i is the orientation index of the building i.i is the azimuth of building i, DI i is the nearest neighbor distance. This embodiment uses the minimum bounding rectangle method, also known as the minimum MBR method. With true north as zero degrees, the angle obtained by rotating clockwise to the longest side of the minimum bounding rectangle is used as the azimuth value. Sampling points are generated based on the building outlines. The building complex is then spatially segmented using the TIN triangulation network, establishing proximity relationships between buildings. The shortest distance is then screened and calculated, serving as the distance between points adjacent to the building outlines, or the nearest neighbor distance.

[0041] The texture measurement unit 202 is used to calculate the average robustness of the texture based on the nearest neighbor building texture network through the urban texture multi-scale resilience measurement method.

[0042] Figure 3 4 is a flow chart of the texture measurement unit calculating the average robustness of the texture in an embodiment of the present invention.

[0043] like Figure 3 As shown, the process of calculating the average robustness of the texture by the texture measurement unit 202 includes the following steps:

[0044] In step T2-1, edges greater than a selected threshold are removed from the nearest neighbor building texture network to obtain multiple unconnected texture clusters.

[0045] Step T2-2: obtaining multiple key thresholds based on the largest texture cluster and the second largest texture cluster.

[0046] Figure 4 Schematic diagram of key thresholds in an embodiment of the present invention.

[0047] like Figure 4 As shown in the figure, the horizontal axis is the threshold value, and the vertical axis is the cluster size, i.e., the number of nodes in the texture cluster. By observing the size characteristics of the largest and second largest texture clusters at different thresholds, the point with the most obvious fluctuation is identified. This point represents the threshold at which the texture structure has undergone a significant change, and this threshold is the critical threshold. In this example, a total of six thresholds were obtained as critical thresholds: 0.067, 0.21, 0.44, 0.68, 0.73, and 1.5.

[0048] In step T2-3, the average robustness of the texture is calculated based on all key thresholds and the nearest neighbor building texture network using the urban texture multi-scale resilience measurement method.

[0049] Among them, the calculation expression of the average robustness of the texture is:

[0050]

[0051]

[0052] R is a building data of the current iteration round, and the texture connection between buildings i and j, D is the number of key thresholds, ij is the toughness strength of the texture connection between buildings i and j in the building data of the current iteration round, D is the number of key thresholds, is the size of the texture cluster to which the texture connection between buildings i and j belongs at the tth key threshold, is the size of the largest texture cluster at the tth key threshold, and n is the number of edges in the nearest neighbor building texture network.

[0053] The evacuation time simulation unit 203 is used to calculate the total population evacuation time according to the evacuation data and the building data of the current iteration round.

[0054] Wherein, the evacuation time simulation unit 203 sets the evacuation population to be evenly distributed in each street and alley corresponding to the building data of the current iteration round, and uses the shortest path algorithm to calculate the total population evacuation time. In this embodiment, the evacuation data further includes that the number of evacuation population is 2300, the number of evacuation exits is 7, and the speed of evacuation population is 1.2 m / s.

[0055] Figure 5 is a schematic diagram of the evacuation exit setting of Tianzifang in the embodiment of the present application.

[0056] As shown in Figure 5 , the positions marked by 7 white circles are the preset 7 evacuation exits of Tianzifang.

[0057] The building removal module 30 is used to randomly select a batch of buildings from the target historical block, and delete the data corresponding to the batch of buildings from the building data to obtain the building data of the current iteration round.

[0058] The iteration judgment module 40 stores a preset termination condition, which is used to judge whether to terminate iteration according to the modification scheme of the current iteration round, the modification scheme of the last iteration round, the initial modification scheme and the preset termination condition.

[0059] Wherein, when the average texture robustness corresponding to the current iteration round is greater than the average texture robustness corresponding to the initial modification scheme, and the improvement value of the total population evacuation time corresponding to the current iteration round compared with the total population evacuation time corresponding to the last iteration round is greater than a preset improvement threshold, the iteration is continued, otherwise the iteration is terminated.

[0060] Wherein, the calculation expression of the improvement value is:

[0061]

[0062] Wherein, a is the improvement value, b is the total population evacuation time corresponding to the last iteration round, and c is the total population evacuation time corresponding to the current iteration round.

[0063] The iteration control module 50 is configured to control the scheme calculation module 10 to calculate a corresponding reconstruction scheme as an initial reconstruction scheme according to the building data, and control the building demolition module 30, the scheme calculation module 20 and the iteration judgment module 40 to perform multiple iterations to calculate reconstruction schemes of each iteration round.

[0064] In this embodiment, the iteration control module 50 controls the scheme calculation module 10, the building demolition module 30 and the iteration judgment module 40 to perform three iterations, and the iteration is terminated when the preset termination condition is not met. The specific data of the initial reconstruction scheme and the iteration reconstruction schemes are as follows:

[0065]

[0066] The first column in the above table is the initial reconstruction scheme and the reconstruction schemes of each iteration round, and the second to fourth columns are the total number of demolished buildings, the total population evacuation time and the average robustness of the texture corresponding to each reconstruction scheme. For example, the cell in the third column of the second row indicates that the total population evacuation time of the initial reconstruction scheme is 137.8 seconds.

[0067] The balanced solution calculation module 60 is configured to calculate the most balanced reconstruction scheme as the optimal reconstruction scheme according to all reconstruction schemes.

[0068] In this embodiment, the reconstruction scheme generated in the last iteration round is selected as the most balanced reconstruction scheme, that is, the reconstruction scheme corresponding to the third iteration round, that is, 13 buildings are demolished to improve the evacuation effect by 12.2%. In other embodiments, a comprehensive score can be calculated according to the number of demolished buildings and the evacuation effect to obtain the most balanced reconstruction scheme.

[0069] The total control module 70 stores a control program for controlling the operation of each module.

[0070] The process of the historical block fire evacuation optimization method based on texture protection will be described below with reference to the accompanying drawings.

[0071] Figure 6 is a flowchart of the historical block fire evacuation optimization method based on texture protection in the embodiments of the present application.

[0072] As shown in Figure 6 , the historical block fire evacuation optimization method based on texture protection includes the following steps:

[0073] In step S1, the building data extraction module 10 extracts the building data of the target historical block from the plan.

[0074] In step S2, the scheme calculation module 20 calculates a corresponding reconstruction scheme as an initial reconstruction scheme according to the building data.

[0075] Step S3, a building removal module 30 is used to randomly select a batch of buildings from the target historical block, and the data corresponding to the batch of buildings is deleted from the building data to obtain the building data of the current iteration round.

[0076] Step S4, a scheme calculation module 20 is used to calculate the reconstruction scheme of the current iteration round according to the building data of the current iteration round.

[0077] Step S5, an iteration judgment module 40 is used to judge whether to terminate the iteration according to the reconstruction scheme of the current iteration round, the reconstruction scheme of the last iteration round, the initial reconstruction scheme and the preset termination condition, if yes, step S6 is executed, and if no, step S3 is executed.

[0078] Step S6, the most balanced reconstruction scheme is calculated according to all the reconstruction schemes as the optimal reconstruction scheme.

[0079] In the embodiment, an iteration control module 50 controls the scheme calculation module 20, the building removal module 30 and the iteration judgment module 40 to execute steps S2 to S5, and the reconstruction scheme of the last iteration round corresponding to the first iteration round is the initial reconstruction scheme.

[0080] Effects of the embodiment

[0081] According to the historical block fire evacuation optimization method and device based on texture protection provided in the embodiment, on the one hand, the internal shape elements, i.e., the perimeter and area, and the orientation elements, i.e., the azimuth, of the small-scale block are used as the construction elements of the weight of the edge in the nearest neighbor building texture network, so that the influence of the internal shape elements and the orientation elements on the texture measure is considered, and the measure result of the historical block texture is more accurate; on the other hand, the preset termination condition and the random building removal are used, so that the optimal reconstruction scheme can be obtained after multiple iterations, and the manpower is saved. In summary, the method can generate the optimal reconstruction scheme of the historical block considering the fire evacuation and the traditional texture protection.

[0082] Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A fire evacuation optimization method for historical blocks based on texture protection, which is used to obtain the optimal renovation plan based on the floor plan and evacuation data of the target historical block, characterized by: The following steps are involved: Step S1, extracting architectural data of the target historic block from the plan; Step S2, calculating a corresponding renovation plan based on the building data as an initial renovation plan; Step S3, randomly selecting a group of buildings from the target historical block, and deleting the data corresponding to these buildings from the building data to obtain the building data of the current iteration round; Step S4, calculating a renovation plan for the current iteration based on the building data of the current iteration; Step S5: Determine whether to terminate the iteration based on the transformation plan of the current iteration, the transformation plan of the previous iteration, the initial transformation plan, and the preset termination condition. If yes, execute step S6; if not, execute step S3. Step S6: Calculate the most balanced transformation plan based on all the transformation plans as the optimal transformation plan. The renovation plan includes the building data, average texture robustness and the total population evacuation time. The specific process of calculating the renovation plan based on the building data includes the following steps: Step T1, constructing a nearest neighbor building texture network based on the building data; Step T2: calculating the average robustness of the texture using a multi-scale urban texture resilience measurement method based on the nearest neighbor building texture network; Step T3: Calculate the evacuation time of all the people based on the evacuation data and the building data. The nearest neighbor building texture network includes multiple nodes, edges between nodes and weights corresponding to the edges. The node is a building mass point in the building data. The edges are the connections between buildings in the building data. The building data includes the perimeter, azimuth and area of ​​the building, The calculation expression of the weight is: W ij =S ij +D ij +IN i , S ij =|S j -S i |, D ij =|D j -D i |, Where W ij is the weight between building i and building j, S ij is the shape difference between building i and building j, S i is the shape index of building i, P i is the perimeter of building i, A i is the area of ​​building i, D ij is the orientation difference between building i and building j, D i is the azimuth of building i, DI i is the nearest neighbor distance, The step T2 includes the following sub-steps: Step T2-1, removing edges greater than a selected threshold in the nearest neighbor building texture network to obtain multiple unconnected texture clusters; Step T2-2, obtaining multiple key thresholds according to the largest texture cluster and the second largest texture cluster; Step T2-3: Calculate the average robustness of the texture using the multi-scale resilience measurement method of urban texture based on all the key thresholds and the nearest neighbor building texture network. The calculation expression of the average robustness of the texture is: Where R ij is the toughness strength of the texture connection between building i and building j in the building data of the current iteration round, D is the number of the critical thresholds, is the size of the texture cluster to which the texture connection between building i and building j belongs at the tth critical threshold, is the size of the largest texture cluster under the tth critical threshold, and n is the number of edges in the nearest neighbor building texture network.

2. The fire evacuation optimization method for historic blocks based on texture protection according to claim 1 is characterized by: in, The evacuation data includes the number of people evacuated, the speed of evacuation and the evacuation entrances and exits. In step T3, the evacuated population is evenly distributed in each street and lane corresponding to the building data of the current iteration round, and the evacuation time of the entire population is calculated using the shortest path algorithm.

3. The fire evacuation optimization method for historic blocks based on texture protection according to claim 1 is characterized by: in, The preset termination condition is that the average robustness of the texture corresponding to the current iteration round is greater than the average robustness of the texture corresponding to the initial transformation plan, and the improvement value of the total population evacuation time corresponding to the current iteration round compared with the total population evacuation time corresponding to the previous iteration round is greater than the preset improvement threshold.

4. The fire evacuation optimization method for historic blocks based on texture protection according to claim 1 is characterized by: in, The calculation expression of the improvement value is: Where a is the improvement value, b is the total population evacuation time corresponding to the previous iteration round, and c is the total population evacuation time corresponding to the current iteration round. The preset improvement threshold is 3%.

5. A device for optimizing fire evacuation in a historical block based on texture protection according to any one of claims 1 to 4, for obtaining an optimal reconstruction plan based on a plan view and evacuation data of a target historical block, characterized in that: include: Building data extraction module, scheme calculation module, building demolition module, iterative judgment module, iterative control module and equilibrium solution calculation module, The building data extraction module is used to extract the building data of the target historical block from the plan. The solution calculation module is used to calculate the corresponding renovation solution based on the building data. The building demolition module is used to randomly select a batch of buildings from the target historical block and delete the data corresponding to these buildings from the building data to obtain the building data of the current iteration round. The iteration judgment module stores a preset termination condition and is used to judge whether to terminate the iteration based on the transformation plan of the current iteration round, the transformation plan of the previous iteration round, the initial transformation plan and the preset termination condition. The iterative control module is used to control the solution calculation module to calculate the corresponding renovation solution as the initial renovation solution based on the building data, and control the building demolition module, the solution calculation module and the iterative judgment module to perform multiple rounds of iterations to calculate the renovation solution for each iteration round. The balance solution calculation module is used to calculate the most balanced transformation solution according to all the transformation solutions as the optimal transformation solution. The renovation plan includes the building data, average texture robustness and total population evacuation time. The solution calculation module includes: A nearest neighbor building texture network generating unit, configured to construct a nearest neighbor building texture network based on the building data of the current iteration round; A texture measurement unit, configured to calculate an average texture robustness based on the nearest neighbor building texture network by using a multi-scale urban texture resilience measurement method; The evacuation time simulation unit is used to calculate the evacuation time of the entire population based on the evacuation data and the building data of the current iteration round.

Images