Diversified building scheme rapid construction method and system based on modular concept

Abstract

The present application relates to the technical field of building informatization, in particular to a diversified building scheme rapid construction method and system based on a modular concept, comprising the following steps: obtaining a node flow line density passing direction and connectivity strength ratio mapping to establish a space pressure distribution model through a space sensor, calculating a pressure adaptation coefficient to generate a module position configuration table, collecting a time sequence frequency and a passing probability calculation time period adaptation index to generate a module time sequence layout scheme, adjusting the module position according to the layout scheme to form a phased building layout form, and optimizing a connected path to generate a diversified building scheme set. In the present application, the pressure distribution is formed through flow line density ratio operation and gradient descent mapping, the space self-organization optimization is realized by combining node pressure and use frequency, the space dynamic response and layout sensitivity are improved based on time sequence occupation and passing probability weighted normalization, the load aggregation and resource waste are reduced, and the operation balance and overall utilization rate are enhanced.

Description

Technical Field

[0001] This invention relates to the field of building information technology, and in particular to a method and system for rapidly constructing diverse building solutions based on the modular concept. Background Technology

[0002] Building Information Modeling (BIM) technology refers to a comprehensive technical system that utilizes information technology to digitally represent and integrate information management throughout the entire lifecycle of a building, including design, construction, and operation and maintenance. Its core aspects include the construction and management of BIM data, the collaboration and sharing of architectural design data, the information-based control of the construction process, and the intelligent data application during operation and maintenance. This technical field achieves seamless information flow and efficient collaboration across building projects from initial design to completion and operation, forming an integrated technical support system for architectural design and management.

[0003] The traditional method for rapidly constructing diverse architectural schemes refers to the technical process of generating different design schemes during the architectural design phase, addressing various design requirements such as building form, spatial layout, and structural combination through manual modeling, parametric modeling scripting, or model assembly based on preset templates. This method relies on architects manually creating scheme models according to the design brief, or gradually adjusting building volume and component arrangement within design software using limited parametric constraints to form preliminary design results of diverse architectural schemes.

[0004] Traditional architectural design relies primarily on static models and spatial organization based on human experience. This approach fails to establish a quantitative relationship between circulation distribution and node locations. As the building operates, it struggles to reflect the spatial pressure differences caused by changes in pedestrian flow, leading to excessive loads in localized areas or an imbalance in functional zone distribution. When usage frequency and traffic direction change over time, the original layout cannot be adjusted according to actual usage, resulting in decreased pedestrian flow efficiency and space utilization deviation. The design results lack dynamic feedback capabilities, making it difficult to support continuous coordination and optimization of the building throughout its operational cycle. Summary of the Invention

[0005] To address the challenges of traditional architectural design methods that rely primarily on static models and manual judgment in spatial organization, failing to establish quantitative relationships between circulation patterns and node locations, and thus struggling to reflect spatial pressure variations caused by changes in pedestrian flow during building operation—leading to excessive load-bearing capacity in localized areas or imbalanced functional zones—this invention provides a method for the rapid construction of diverse architectural solutions based on a modular design concept.

[0006] To achieve the above objectives, this invention employs a rapid construction method for diverse building solutions based on a modular concept, comprising the following steps:

[0007] S1: Obtain streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors, calculate the ratio of streamline density values ​​between adjacent nodes, and use the gradient descent algorithm to correlate the ratio results with the node coordinates to establish a spatial pressure distribution model.

[0008] S2: Call the node pressure of the spatial pressure distribution model, collect the functional type parameters of multiple modules to calculate the pressure adaptation coefficient, obtain the module usage frequency parameter, sort the nodes with pressure adaptation coefficients greater than the pressure threshold, and generate a module location configuration table.

[0009] S3: Call the module location configuration table, collect the node's time sequence occupancy frequency parameters and directional passage probability parameters, calculate the time period adaptation index based on the sorting weight in the module location configuration table, normalize the time period index using a weighted average algorithm, and generate a module time sequence layout scheme.

[0010] S4: Call the module time sequence layout scheme to execute the module spatial arrangement, adjust the position order according to the time period adaptation index of the module in different time periods, and allocate the module to the core access position and the peripheral auxiliary position to form a phased building layout form.

[0011] As a further aspect of the present invention, the spatial pressure distribution model includes node pressure gradient values, spatial stress distribution intervals, and pressure coordinate mapping relationships; the module location configuration table includes node pressure level sequences, module configuration priorities, and spatial coordinate indexes; the module temporal layout scheme includes a time-period adaptation index set, module dynamic temporal distribution, and time-normalized weight parameters; the phased building layout form includes a core functional area layout, an auxiliary functional area layout, and a temporal location association structure; the core accessible location is a node with a time-period adaptation index higher than the 75th percentile; and the peripheral auxiliary location is a node with a time-period adaptation index lower than the 25th percentile.

[0012] As a further aspect of the present invention, the specific steps of S1 are as follows:

[0013] S101: Obtain streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors; perform ratio calculations on the streamline density parameters of adjacent nodes; index and map the ratio results to the traffic direction vectors to generate a streamline density ratio sequence set.

[0014] S102: Based on the streamline density ratio sequence set, collect the spatial coordinate parameters of adjacent nodes. For the numerical deviation between the ratio sequence elements and the node coordinates, use the gradient descent algorithm to control the gradient direction vector to decrease iteratively, record the error convergence point and aggregate it to generate a coordinate mapping distribution set.

[0015] S103: Based on the coordinate mapping distribution set, call the node connectivity strength coefficient, perform weighted normalization operation on the mapping density, associate the superposition result with the original node coordinates, calculate the pressure gradient based on the node spatial difference, and establish a spatial pressure distribution model.

[0016] As a further aspect of the present invention, the specific steps of S2 are as follows:

[0017] S201: Obtain the node pressure parameters of the spatial pressure distribution model, collect the function type parameters of multiple modules, match the node pressure parameters with the function type parameters according to the node index, perform ratio calculation on the matching results and compare them with the pressure benchmark value to generate a node pressure response distribution set;

[0018] S202: Based on the node pressure response distribution set, collect the usage frequency parameters of multiple modules, perform weighted calculation on the node response offset and usage frequency and compare it with the pressure threshold, filter nodes higher than the threshold and sort them to generate a node priority sequence set;

[0019] The pressure threshold is based on the pressure ratio data of all nodes in the node pressure response distribution set. The mean and standard deviation of the node pressure ratios are calculated, and the linear combination of the mean and standard deviation is used as the initial pressure threshold.

[0020] S203: Based on the node priority sequence set, perform a corresponding mapping between the spatial location index of the node and the module number, establish a correspondence table between nodes and modules, and aggregate and integrate the spatial location parameters of the nodes in the sequence according to the correspondence table to generate a module location configuration table.

[0021] As a further aspect of the present invention, the specific steps of S3 are as follows:

[0022] S301: Call the module location configuration table, index and retrieve the node module location information, collect the node's timing occupancy frequency parameter and directional passage probability parameter, aggregate the two types of parameters according to the node sequence and perform consistency verification to generate a node parameter set;

[0023] S302: Based on the node parameter set, call the sorting weight parameter in the module location configuration table, perform a weighted comparison operation on the occupancy frequency parameter and the direction passage probability parameter for the same time period, calculate the node time period weighted value and aggregate it according to the time index to generate a time period adapted weighted distribution set;

[0024] S303: Based on the time period adapted weighted distribution set, the weighted average algorithm is used to perform normalization calculation on the weighted value sequence, establish the time period index sequence and arrange and adjust the interval according to the time index to generate the module time sequence layout scheme.

[0025] As a further aspect of the present invention, the specific steps of S4 are as follows:

[0026] S401: Obtain the time period adaptation index in different time periods in the module time sequence layout scheme, calculate the difference between the module adaptation index and the average adaptation index benchmark value, divide the interval according to the adaptation index change rate threshold, perform level coding according to the interval index, and generate the module time period adaptation classification result.

[0027] S402: Based on the module time period adaptation and hierarchical results, call the coordinate mapping distribution set and time period index sequence, analyze the node position centrality in the coordinate mapping distribution set to calculate the core accessibility coordinate coefficient, and perform weighted summation with the module time period weight value and serialize and arrange it to obtain the module space priority sequence set;

[0028] S403: Based on the module space priority sequence set, read the position weight factor and calculate the module space occupancy rate. After comparing it with the layout volume threshold, perform position offset correction calculation, allocate the module to the core access position and the peripheral auxiliary position, and aggregate the correction index mapping to obtain the staged building layout form.

[0029] As a further aspect of the present invention, the adaptation index change rate threshold is determined based on the average change amplitude of the adaptation index in adjacent time periods in the original time-series layout data.

[0030] The layout volume threshold is determined based on the relationship between the total building volume control parameters and the module design volume ratio.

[0031] As a further aspect of the present invention, the method further includes step S5:

[0032] S5: Based on the phased building layout, optimize the connection path between modules, calculate the weighted connection distance between adjacent modules and the time period adaptation index, adjust the relative position of modules through the path length optimization principle, verify that the adjusted layout meets the building code requirements, and generate a diverse set of building schemes.

[0033] The diverse set of architectural solutions includes spatial layout optimization paths, standard adaptation verification results, and architectural form combination schemes.

[0034] As a further aspect of the present invention, the specific steps of S5 are as follows:

[0035] S501: Based on the phased building layout morphology data, extract the module spatial coordinate set and boundary constraint parameters, calculate the three-dimensional Euclidean distance between adjacent modules, map the distance value with the corresponding time period adaptation index and perform weighted accumulation to generate a module weighted connectivity distance set;

[0036] S502: Call the weighted connectivity distance set of the modules, compare the weighted connectivity distance value with the path optimization benchmark value according to the path length optimization principle, identify the module pairs whose difference exceeds the benchmark, perform directional translation adjustment on the relative position coordinates of the module pairs and recalculate the distance to obtain the module relative position adjustment parameter set;

[0037] S503: Call the relative position adjustment parameter set of the module, perform verification on the layout coordinate set according to the building code parameters, search the structural spacing, passage path width and ventilation and lighting parameter range, eliminate layouts that do not conform to the building code and classify and encode them, and generate a diverse set of building schemes.

[0038] A rapid assembly system for diverse building solutions based on modular design principles, including:

[0039] The spatial streamline acquisition module acquires streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space through spatial sensors. It also performs ratio calculations on the streamline density values ​​between adjacent nodes, uses a gradient descent algorithm to correlate the ratio results with the node coordinates, establishes a spatial pressure distribution model, and transmits it to the pressure mapping modeling module.

[0040] The pressure mapping modeling module calls the node pressure of the spatial pressure distribution model, collects the module function type parameters and usage frequency parameters, calculates the pressure adaptation coefficient, sorts the nodes that exceed the pressure threshold, generates a module location configuration table, and passes it to the function adaptation calculation module.

[0041] The functional adaptation calculation module calls the module location configuration table, collects the node time sequence occupancy frequency and directional passage probability, calculates the time period adaptation index based on the sorting weight, performs normalization processing using a weighted average algorithm, generates a module time sequence layout scheme, and passes it to the time sequence layout generation module.

[0042] The temporal layout generation module calls the temporal layout scheme of the module to perform spatial arrangement, adjusts the position order of the module according to the time period adaptation index, and allocates it to the core access area and the peripheral auxiliary area to form a phased building layout form, which is then passed to the path optimization and adjustment module.

[0043] The path optimization and adjustment module, based on the connection path of the phased building layout optimization module, performs a weighted calculation of the connection distance between adjacent modules and the time period adaptation index, adjusts the relative positions of the modules according to the path length optimization principle, and generates a diverse set of building schemes.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] In this invention, by calculating the ratio of streamline density between nodes in a building space and using a gradient descent algorithm to map the density results to node coordinates, a continuous pressure distribution pattern can be formed in the space. Combined with the dynamic correlation between node pressure and usage frequency, optimized sorting based on pressure adaptation can be achieved in the spatial configuration, enabling the spatial layout to generate a self-organizing adjustment trend according to pedestrian flow characteristics. Furthermore, weighted normalization is performed using temporal occupancy frequency and passage probability as variables, so that the spatial form maintains passage efficiency and functional coordination in different time periods, thereby improving the dynamic response capability and layout sensitivity of the building space, reducing local load accumulation and resource waste, and enhancing the balance of the spatial operation state and overall utilization rate. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the accompanying drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the steps of the present invention;

[0048] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0049] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0050] Figure 4 This is a detailed schematic diagram of S3 of the present invention;

[0051] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0052] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0053] Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0054] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0055] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0056] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0057] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0058] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0059] Please see Figure 1 This invention provides a method for rapidly constructing diverse building solutions based on a modular concept, comprising the following steps:

[0060] S1: Obtain streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors, calculate the ratio of streamline density values ​​between adjacent nodes, and use the gradient descent algorithm to correlate the ratio results with the node coordinates to establish a spatial pressure distribution model.

[0061] S2: Call the node pressure of the spatial pressure distribution model, collect the functional type parameters of multiple modules to calculate the pressure adaptation coefficient, obtain the module usage frequency parameter, sort the nodes with pressure adaptation coefficients greater than the pressure threshold, and generate a module location configuration table.

[0062] S3: Call the module location configuration table, collect the node's time sequence occupancy frequency parameters and directional passage probability parameters, calculate the time period adaptation index based on the sorting weight in the module location configuration table, normalize the time period index using a weighted average algorithm, and generate a module time sequence layout scheme.

[0063] S4: Call the module time sequence layout scheme to execute the module spatial arrangement. Adjust the position order according to the time period adaptation index of the module in different time periods, and allocate the module to the core access position and the peripheral auxiliary position to form a phased building layout form.

[0064] S5: Optimize the connection path between modules based on the phased building layout form, calculate the connection distance between adjacent modules with time period adaptation index, adjust the relative position of modules through path length optimization principle, verify that the adjusted layout meets the building code requirements, and generate a diverse set of building schemes.

[0065] The spatial pressure distribution model includes node pressure gradient values, spatial stress distribution intervals, and pressure coordinate mapping relationships. The module location configuration table includes node pressure level sequences, module configuration priorities, and spatial coordinate indices. The module temporal layout scheme includes a time-period adaptation index set, module dynamic temporal distribution, and time-normalized weight parameters. The phased building layout forms include core functional area layout, auxiliary functional area layout, and temporal location-related structures. The diverse building scheme set includes spatial layout optimization paths, code adaptation verification results, and building form combination schemes. Core access locations are nodes with a time-period adaptation index higher than the 75th percentile, and peripheral auxiliary locations are nodes with a time-period adaptation index lower than the 25th percentile.

[0066] Please see Figure 2 The specific steps of S1 are as follows:

[0067] S101: Obtain streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors; perform ratio calculations on the streamline density parameters of adjacent nodes; index and map the ratio results to the traffic direction vectors to generate a streamline density ratio sequence set.

[0068] By acquiring streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors, the process of acquiring streamline density values ​​is first refined. Specifically, this involves capturing streamline density values ​​in the entrance area of ​​a large commercial complex during weekday morning rush hours (e.g., morning). to Using infrared passenger flow sensors installed on the ceiling, passenger flow data is collected at three preset key nodes: Node A is located at the main entrance, Node B is located in the middle of the wide corridor leading from the entrance to the atrium, and Node C is located at the end of the corridor leading to the escalator. The sensors... Data is refreshed every few minutes, accumulating... Minutes, the total number of people passing through node A during this period is The streamline density value is [value missing]. People / minute; similarly, the streamline density value of node B is measured as follows: The streamline density value at node C was measured to be [value missing] people / minute. The document describes the process of obtaining pedestrian direction vectors, using wide-angle cameras deployed near nodes and video analytics to track pedestrian movement. Taking the journey from node A to node B as an example, a vector vector is established with node A as the origin. In a two-dimensional coordinate system, most pedestrians move directly from node A to node B. Their average trajectory in the coordinate system appears as a straight line close to the positive X-axis. This direction vector is recorded as... From node B to node C, the pedestrian needs to turn left towards the escalator, and their travel direction vector is recorded as follows: Finally, the setting of the connectivity strength coefficient is explained in detail. This coefficient is set with reference to the physical reachability and visual permeability between nodes, and its value ranges from [0, 1]. This indicates that there is absolutely no connection. This indicates a completely unobstructed physical and visual connection between node A and node B, forming a straight corridor without any obstacles. The connectivity strength coefficient is set to [value missing]. Although node B and node C are physically connected, due to the presence of a visual corner, their connectivity strength coefficient is set to [value missing]. Next, the ratio of streamline density parameters of adjacent nodes is calculated. Taking node A and node B as an example, the streamline density ratio is calculated as follows: The ratio of node B to node C is Subsequently, the ratio result is indexed and mapped with the previously obtained traffic direction vector to determine the streamline density ratio of node pair (A, B). With the direction vector Link them to form a data pair; similarly, the ratio of node pair (B, C) is used. With the direction vector The system associates adjacent node pairs and processes them sequentially to generate a set of streamline density ratio sequences.

[0069] S102: Based on the streamline density ratio sequence set, collect the spatial coordinate parameters of adjacent nodes. For the numerical deviation between the ratio sequence elements and the node coordinates, use the gradient descent algorithm to control the gradient direction vector to decrease iteratively, record the error convergence point and aggregate it to generate a coordinate mapping distribution set.

[0070] Based on the generated streamline density ratio sequence set, the spatial coordinate parameters of adjacent nodes are collected. First, these spatial coordinate parameters are the initial design coordinates in the Building Information Model (BIM). Assuming that the southwest corner of the building is taken as the origin in the design drawings, the coordinates of node A are... The coordinates of node B are The coordinates of node C are The units are all meters. Next, the numerical deviation between the ratio sequence elements and the node coordinates is processed. This deviation is defined as the difference between the ideal spatial relationship implied by the streamline density ratio K and the geometric relationship represented by the actual coordinates. Taking node A and node B as examples, their streamline density ratio is... The ratio is greater than This indicates that as pedestrian traffic spreads from dense to sparse areas, a certain buffer space is needed. Therefore, an ideal distance calculation method is established, such as:

[0071] ;

[0072] in Coordinate difference, actual geometric distance for meters, then the ideal distance is meters, the deviation between the two is Meters, then, the gradient descent algorithm is used to control the gradient direction vector to decrease iteratively. Specifically, this process involves first defining an error function, for example... Set the coordinates of node B Treating it as a variable, calculate the error E. and The partial derivatives of the error surface at that point are used to obtain the gradient of the error surface. This gradient vector indicates the direction of the fastest increase in error. For example, the calculated gradient direction vector is... This means that moving node B only in the X direction will cause a change in error. To reduce the error, it is necessary to move along the opposite direction of the gradient, i.e. The coordinates of node B are adjusted, with the adjustment step size determined by a preset learning rate, which is set empirically. Then, the new X coordinate of node B after a single iteration is:

[0073] ;

[0074] The Y-coordinate remains unchanged. This adjustment process is applied to the node pairs and iterated repeatedly until the sum of the total errors of the node pairs is less than a preset convergence threshold, for example... When the iteration stops, the new coordinate positions of the nodes after they stabilize are recorded, and the convergence points are aggregated to generate a coordinate mapping distribution set.

[0075] S103: Based on the coordinate mapping distribution set, call the node connectivity strength coefficient, perform weighted normalization operation on the mapping density, associate the superposition result with the original node coordinates, calculate the pressure gradient based on the node spatial difference, and establish a spatial pressure distribution model.

[0076] Based on the generated coordinate mapping distribution set, the node connectivity coefficients are retrieved. This step first extracts the connectivity coefficients between nodes from the generated raw data. For example, the coefficient between nodes A and B is... The coefficient between nodes B and C is Meanwhile, prepare the original streamline density values ​​of the nodes, as shown in Table 1.

[0077] Table 1: Node Initial Parameters Table

[0078] Node identifier Streamline density value (persons / minute) A 150 B 100 C 120

[0079] Table 1 lists the initial streamline density monitoring values ​​of the nodes. Next, a weighted normalization operation is performed on the mapped density. Here, the mapped density specifically refers to the original streamline density value of each node. The weighting operation uses the connectivity strength coefficient to calculate a comprehensive influence value. Taking node B as an example, it is affected by its neighboring nodes A and C. Its weighted density value is calculated as: node B's own density + (node ​​A's density × connectivity strength from A to B) + (node ​​C's density × connectivity strength from C to B), i.e. Similarly, assuming node A is only connected to B, its weighted density value is Node C is only connected to B, and its weighted density value is A set of weighted density values ​​was obtained. Then, normalization is performed, first determining the maximum value of the data set. The minimum value is The weighted density value for each node is calculated using the formula (current value - minimum value) / (maximum value - minimum value). For example, the normalized result for node B is... The normalized result of node A is The normalized result of node C is Then, the normalized value, referred to as the "overlay result," is associated with the original coordinates of the node. For example, the original coordinates of node A are then overlaid. with normalized value Association, linking the original coordinates of node B with normalized value Finally, the pressure gradient is calculated based on the spatial difference between nodes. Here, "pressure" refers to the previously normalized value, and the pressure gradient is the rate of change of pressure per unit distance. For example, the pressure difference between node A and node B is... The straight-line distance between the two points is If the distance is meters, then the magnitude of the pressure gradient in that direction is... The direction is from high pressure to low pressure, that is, from B to A. By performing this calculation on adjacent node pairs, a vector field describing the spatial evacuation or congestion trend is established, that is, a spatial pressure distribution model.

[0080] Please see Figure 3 The specific steps of S2 are as follows:

[0081] S201: Obtain the node pressure parameters of the spatial pressure distribution model, collect the function type parameters of multiple modules, match the node pressure parameters with the function type parameters according to the node index, perform ratio calculation on the matching results and compare them with the pressure benchmark value to generate a node pressure response distribution set;

[0082] Obtain the nodal pressure parameters of the generated spatial pressure distribution model, specifically the pressure parameters of node A. The pressure parameters of node B are: The pressure parameters of node C are Subsequently, functional type parameters of multiple pre-defined modules embedded in the building space were collected. These parameters were based on a quantitative assessment of the ability of different functional business formats to attract foot traffic. Through analysis of industry data, the functional types were divided into four categories: "catering," "retail," "leisure," and "transportation," and each category was assigned a... arrive The functional attractiveness coefficient between categories, for example, the coefficient for the "restaurant" category is set at [value missing] due to its high customer attraction. The "retail" category is set as The "leisure" category is set as "Transportation" category (such as pure corridors) is set as Next, the node pressure parameters are matched with the functional type parameters of the modules to be deployed according to the node index. Assuming the plan is to deploy a "retail" module at node A, a "catering" module at node B, and a "leisure" module at node C, a matching pair is formed: Node A Node B Node C Then, for each matching result, a ratio calculation is performed, specifically by dividing the node pressure parameter by the function type parameter. The calculation result for node A is... The calculation result for node B is The calculation result for node C is The ratio result will be compared with a preset pressure benchmark value, which is set to reflect an ideal situation where the space pressure and functional requirements are perfectly matched. The ratio of node A and The comparison revealed that its value was less than the baseline value, so the ratio of node B was adjusted. and The comparison revealed that its value was greater than the baseline value, so the ratio of node C was adjusted. and By comparison, it was found that the value was much smaller than the baseline value. By recording the index of each node and its corresponding pressure ratio, a node pressure response distribution set was generated.

[0083] S202: Based on the node pressure response distribution set, collect the usage frequency parameters of multiple modules, calculate the node response offset and usage frequency in a weighted manner and compare it with the pressure threshold, filter nodes that are higher than the threshold and sort them to generate a node priority sequence set;

[0084] The pressure threshold is based on the pressure ratio data of all nodes in the node pressure response distribution set. The mean and standard deviation of the node pressure ratios are calculated, and the linear combination of the mean and standard deviation is used as the initial pressure threshold.

[0085] Based on the generated nodal pressure response distribution set, i.e., the pressure ratios of nodes A, B, and C are respectively First, the usage frequency parameters of the modules to be deployed are collected. These parameters are estimated by statistically analyzing the average daily customer traffic of functional modules in similar commercial projects. For example, the estimated average daily usage frequency of the "Catering" module (corresponding to node B) is... Visitors / day, the "Retail" module (corresponding to node A) is Visitors / day, the "Leisure" module (corresponding to node C) is Person-times / day. Next, a weighted calculation is performed on the node response offset and usage frequency. The first step is to calculate the node response offset, which is defined as the node pressure ratio and pressure baseline value. The absolute value of the difference, the offset of node A is The offset of node B is The offset of node C is The second step is to assign weights based on usage frequency and normalize the usage frequency of the modules, resulting in a total frequency of [missing information]. Visitors / day, the weight of node B is The weight of node A is The weight of node C is The third step is to multiply the node's response offset by its corresponding usage frequency weight to obtain the final weighted response value. The weighted response value for node A is... The weighted response value of node B is The weighted response value of node C is Subsequently, the weighted response value is compared with a dynamically calculated pressure threshold, which is based on the pressure ratio data of all nodes in the node pressure response distribution set. First, calculate its mean. Then, its standard deviation is calculated to be approximately The pressure threshold is set as the sum of the mean and one standard deviation, i.e. However, this threshold is based on a pressure ratio scale, while the weighted response value scale is different. Therefore, the threshold calculation method needs to be adjusted for the weighted response value itself. The statistics show that the mean is The standard deviation is The threshold is set as the mean plus one standard deviation, i.e. Filter out responses with weighted response values ​​higher than The only node is node C. If the conditions are met, and multiple nodes meet the conditions, they are sorted from high to low according to their weighted response values, and finally a node priority sequence set is generated.

[0086] S203: Based on the node priority sequence set, perform a mapping between the spatial location index of the node and the module number, establish a mapping table between nodes and modules, aggregate and integrate the spatial location parameters of the nodes in the sequence according to the mapping table, and generate a module location configuration table.

[0087] Based on the generated set of node priority sequences, this sequence currently contains only node C. To make the example more complete, assume that the weighted response value of node A is... It is also higher than the threshold. And lower than node C The resulting priority sequence is {Node C, Node A}. Next, a mapping is performed between the spatial location indices of the nodes in the sequence and the preset module numbers. First, a unique number is assigned to each module to be deployed; for example, M01 represents the "Retail" module, M02 represents the "Catering" module, and M03 represents the "Leisure" module. According to the settings in S201, node A corresponds to M01, node B corresponds to M02, and node C corresponds to M03. Then, based on the priority sequence {Node C, Node A}, a temporary node-module mapping table is established. This table clarifies the functional modules that high-priority nodes will support; that is, node C maps to module M03, and node A maps to module M01. Subsequently, based on this mapping table, the spatial location parameters of nodes C and A in the sequence are aggregated and integrated, and the original three-dimensional coordinates of these two nodes are extracted from the building information model. The coordinates of node C are... The coordinates of node A are The module number, its corresponding node identifier, the spatial coordinates of the node, and its order in the priority sequence are integrated into a new table, which ultimately generates the module location configuration table.

[0088] Table 2: Module Location Configuration Table

[0089] Module Number Node identifier X coordinate (meters) Y coordinate (meters) Priority M03 C 30 40 1 M01 A 10 20 2

[0090] As shown in Table 2, this table lists the modules that need to be configured according to priority and their detailed spatial location information. The priority field in the table is assigned a value according to the order of the nodes in the priority sequence set, and the smaller the number, the higher the priority.

[0091] Please see Figure 4 The specific steps of S3 are as follows:

[0092] S301: Call the module location configuration table, index and retrieve the node module location information, collect the node's timing occupancy frequency parameter and directional passage probability parameter, aggregate the two types of parameters according to the node sequence and perform consistency verification to generate a node parameter set;

[0093] The generated module location configuration table is invoked. First, nodes C and A are indexed and retrieved. Then, the timing occupancy frequency parameters of these two nodes are collected. This parameter is obtained through Bluetooth positioning beacons pre-embedded within the building. The daily operating time is divided into four time periods: T1 (9:00-12:00), T2 (12:00-15:00), T3 (15:00-18:00), and T4 (18:00-21:00), each lasting 3 hours. The occupancy frequency is obtained by calculating the percentage of average dwell time of independent Bluetooth device IDs within the node's signal coverage area relative to the total dwell time within each time period. For example, for node C (leisure module), its occupancy frequency in time period T1 is... T2 is T3 is T4 is For node A (retail module), its occupancy frequency during time period T1 is: T2 is T3 is T4 is Subsequently, the directional traffic probability parameter is collected. This parameter is obtained through video surveillance image analysis and represents the probability that the flow of people at a specific node will mainly flow to the next node. Taking node A as an example, which is mainly connected to node B, the analysis of video data shows that the probability of flowing from A to B in time period T1 is... T2 is T3 is T4 is For node C, its main flow direction is back to node B, and the probability of flowing from C to B in time period T1 is... T2 is T3 is T4 is Then, these two types of parameters are aggregated according to the sequence {node C, node A} to form parameter pairs for each node in each time period. For example, the parameter pair for node C in time period T1 is ( The parameter pair of node A in time period T2 is ( Finally, a consistency check is performed, which specifically checks whether the two types of parameters collected by each node completely cover the four time periods from T1 to T4. If node A lacks the directional passage probability parameter for time period T4, the data of that node in time period T4 will be marked as invalid and will not participate in subsequent calculations. After the data is verified to be complete, a set of node parameters is generated.

[0094] S302: Based on the node parameter set, call the sorting weight parameter in the module location configuration table, perform a weighted comparison operation on the occupancy frequency parameter and the direction passage probability parameter for the same time period, calculate the node time period weighted value and aggregate it by time index to generate a time period adapted weighted distribution set;

[0095] Based on the generated set of node parameters, namely the occupancy frequency and passage probability data of nodes C and A in four time periods, the sorting weight parameter in the module location configuration table is first called. This weight parameter is set according to the priority field, specifically using a reverse order weighting method. The smaller the priority value, the higher the weight. The weight W is set to 1 / priority. Therefore, the priority is 1 / priority. The sorting weight of node C is Priority is The sorting weight of node A is Next, a weighted comparison operation is performed on the occupancy frequency parameter and the directional passage probability parameter within the same time period. This operation is defined as multiplying the two parameters to obtain a base score, and then multiplying it by the ranking weight of the node. Taking the calculation of time period T1 as an example, the base score of node C is... The basic structure of node A is divided into Then, calculate the weighted value of the node for each time period. The weighted value of node C in T1 is... The weighted value of node A in T1 is Then, the time-weighted values ​​of the nodes are aggregated according to the time index. Specifically, the weighted values ​​of nodes within the same time period are added together. The aggregated value for time period T1 is... Similarly, the aggregate value for time period T2 is calculated: the weighted value of node C is... The weighted value of node A is The aggregate value is The aggregate value for time period T3 is The aggregate value for time period T4 is Finally, the aggregated results are obtained by sorting by time index, generating a time-adapted weighted distribution set.

[0096] S303: Based on the time period adapted weighted distribution set, the weighted average algorithm is used to perform normalization calculation on the weighted value sequence, establish the time period index sequence and arrange and adjust the interval according to the time index to generate the module time sequence layout scheme;

[0097] The weighted distribution set is adapted to the generated time period, i.e., the weighted value sequence from T1 to T4. First, the weighted sequence is normalized using the min-maximum normalization method. The calculation involves subtracting the minimum value from each value in the sequence, then dividing by the difference between the maximum and minimum values. The minimum value in the sequence is... The maximum value is Then the normalized value of T1 is The normalized value of T2 is The normalized value of T3 is The normalized value of T4 is Thus, a time-period exponential series is established. Then, the indexes are arranged according to time indices T1 to T4, and interval adjustments are performed on the index sequence. Specifically, three activity level intervals are set, and the index is adjusted within these intervals. to The definition between them is "low fit". to The definition between them is "medium fit". to The definition between them is "high fit," which maps the calculated time-period index sequence to intervals one by one. The index of T1 is... Falling into the "low fit" range, the index for T2 is Falling into the "high compatibility" range, T3's index is Falling into the "high compatibility" range, T4's index is If the result falls into the "high adaptability" range, the adjustment results will be compiled into a table to generate a module timing layout scheme.

[0098] Table 3: Module Timing Layout Scheme

[0099] Time Period Index Time range Time Period Index Compatibility Level T1 9:00-12:00 0 Low compatibility T2 12:00-15:00 0.662 High compatibility T3 15:00-18:00 1 High compatibility T4 18:00-21:00 0.789 High compatibility

[0100] As shown in Table 3, this table details the quantitative index for each time period and its corresponding qualitative fit level.

[0101] Please see Figure 5 The specific steps of S4 are as follows:

[0102] S401: Obtain the time period adaptation index in different time periods in the module time sequence layout scheme, calculate the difference between the module adaptation index and the average adaptation index benchmark value, divide the interval according to the adaptation index change rate threshold, perform level coding according to the interval index, and generate the module time period adaptation classification result.

[0103] Obtain the time period adaptation index for different time periods in the generated module time sequence layout scheme, i.e., the time period index sequence. First, the difference between the module adaptation index and the average adaptation index benchmark value is calculated. The average adaptation index benchmark value here is calculated based on the aforementioned time period index sequence. Specifically, the calculation process involves summing the index values ​​in the sequence and then dividing by the number of time periods. This baseline value serves as the average level for measuring overall fit. Then, the difference between the fit index for each time period and this baseline value is calculated; the difference for time period T1 is... The difference in time period T2 is The difference in time period T3 is The difference in time period T4 is Next, the intervals are divided based on the adaptation index change rate threshold. This threshold is not a single value, but a set of boundary values ​​used to define the intervals. These boundary values ​​are set according to the sign and magnitude of the difference, specifically dividing the intervals into four sections: when the difference is greater than... "High fit" is defined as when the difference is within a certain range. arrive Between (including) When the difference is defined as "general fit", it is considered a "general fit". (excluding) to Between (including) A "mild mismatch" is defined as a difference less than or equal to 0.5%. The time interval is defined as "mismatch". Then, a level coding is performed according to the interval index, assigning a numerical code to each interval. For example, "high fit" is coded as 3, "moderate fit" as 2, "slight mismatch" as 1, and "mismatch" as 0. The previously calculated time interval difference is substituted into the interval for judgment. The difference of T1 is... Less than If it falls into the "mismatch" interval, the code is 0, and the difference in T2 is... exist arrive Between these values, falling into the "general fit" range, the code is 2, and the difference between T3 and T3 is... Greater than It falls into the "high fit" range, with a code of 3, and the difference between T4 and T4. exist arrive Between these values, the value falls into the "general adaptation" range, is encoded as 2, and the final module time period adaptation classification result is generated.

[0104] Table 4: Module Time Period Adaptation Hierarchy Table

[0105] Time Period Index Difference Adaptation range Level coding T1 -0.61275 Mismatch 0 T2 0.04925 General compatibility 2 T3 0.38725 High compatibility 3 T4 0.17625 General compatibility 2

[0106] As shown in Table 4, this table summarizes the deviation of the adaptation index from the benchmark value for each time period, and gives the adaptation level and corresponding numerical code.

[0107] S402: Based on the module time period adaptation and hierarchical results, call the coordinate mapping distribution set and time period index sequence, analyze the node position centrality in the coordinate mapping distribution set to calculate the core accessibility coordinate coefficient, and perform weighted summation with the module's time period weight value and serialize and arrange it to obtain the module space priority sequence set;

[0108] Based on the generated module time-segment adaptation and hierarchical results, the generated coordinate mapping distribution set and the generated time-segment exponential sequence are first called. Specifically, the new coordinates of nodes A and C after iterative convergence are extracted, assuming to be A'. With C' Simultaneously call the time period exponential sequence Then, a weighted sum is performed on the time-segment weight value of the module and the core accessibility coordinate coefficient. The first step is to determine the time-segment weight value of the module, which reflects the overall importance of the module in the time dimension. The specific calculation method is to decompose the weighted value of the node in the time segment. For the node corresponding to each module, the weighted value of its time segment is averaged. For module M03 (node ​​C), its time-segment weight value is... For module M01 (node ​​A), its time period weight value is The second step is to determine the core accessibility coordinate coefficients. These coefficients are obtained by analyzing the positional centrality of nodes in the coordinate mapping distribution set. Taking the geometric center of the associated nodes (A', C', and associated B') as the origin, the reciprocal of the distance from the node to this center is calculated and normalized. Assuming the calculated coefficient for node C' is... The coefficient of node A' is The third step is to perform a weighted summation, setting a combined weight for the time weight and the spatial coefficient. Based on experience, these two are set to be equally important, meaning the combined weight is 1. Calculate the space priority value for module M03. Calculate the spatial priority value for module M01. Finally, the modules are serialized and arranged in descending order of their spatial priority. Therefore, the arrangement result is {module M03, module M01}, generating a module space priority sequence set.

[0109] S403: Based on the module space priority sequence set, read the location weight factor and calculate the module space occupancy rate. After comparing it with the layout volume threshold, perform the location offset correction calculation, allocate the module to the core accessible location and the peripheral auxiliary location, and aggregate the correction index mapping to obtain the staged building layout form.

[0110] Based on the generated module space priority sequence set, i.e., {module M03, module M01}, firstly, the preset location weight factor is read. This factor is set based on the initial assessment of the commercial value of multiple candidate locations during the architectural design phase, and its value range is [value range missing]. to The higher the value, the larger the position factor. Assume the original position weight factor of node C is... Node A is Then, the module space occupancy rate is calculated. This calculation requires calling the module's basic design parameters, i.e., the standard footprint. Assuming the standard footprint of module M03 (leisure module) is... Module M01 (Retail Module) is Simultaneously, obtain the maximum layout area that node position can provide. Assume that node C position can provide... Location A can provide The space occupancy rate of module M03 on node C is The space occupancy rate of module M01 on node A is Next, the calculated space occupancy rate will be compared with the layout volume threshold, which is set according to building codes and pedestrian comfort, and is generally set at [value missing]. Left and right are used to control the development intensity of local areas; here it is set to... The comparison results show that module M03 has the highest utilization rate. Below the threshold The occupancy rate of module M01 Above the threshold Subsequently, position offset correction calculations are performed on modules exceeding the threshold. Based on the module spatial priority sequence, the highest priority module M03 is processed first. Since its occupancy rate does not exceed the threshold, it is assigned to its corresponding core reachable location, node C. Next, module M01 is processed. Because its occupancy rate exceeds the threshold, the system will search for a peripheral auxiliary location in the vicinity of node A. Assuming it is approximately [distance missing] from node A... There is a spare space point A at 1 meter. aux It can provide The area of ​​, whose location weighting factor is . The occupancy rate of module M01 here is... Below the threshold Therefore, the position of module M01 is corrected from node A to A. auxFinally, the final position allocation results of the modules, including the index changes before and after correction, are mapped and aggregated. For example, the coordinates of module M03 are mapped to those of node C. Map module M01 to auxiliary position A aux coordinates (e.g.) ), to obtain the phased architectural layout form.

[0111] Please see Figure 6 The specific steps of S5 are as follows:

[0112] S501: Based on phased building layout morphology data, extract the module spatial coordinate set and boundary constraint parameters, calculate the three-dimensional Euclidean distance between adjacent modules, map the distance value with the corresponding time period adaptation index and perform weighted accumulation to generate a module weighted connectivity distance set;

[0113] Based on the generated phased building layout data, i.e., the coordinates of module M03 are... The coordinates of module M01 are First, extract the spatial coordinate sets of these two modules and obtain the preset boundary constraint parameters. These parameters define the usable area of ​​the building layout, for example, a... arrive The rectangular plane is then used to calculate the three-dimensional Euclidean distance between the two adjacent modules. This distance is calculated by taking the square root of the sum of the squares of the coordinate differences. Meters, then this distance value is matched with the corresponding time period adaptation index sequence. Mapping is performed, and a weighted summation calculation is executed. Here, weighted summation is defined as multiplying a single physical distance value by the adaptation activity (i.e., adaptation index) across multiple time periods and then summing the results. This quantifies the overall "connectivity cost" brought by physical distance under different time-based activity levels. Specifically, the calculation involves multiplying the physical distance value by the adaptation activity (i.e., the adaptation index) across multiple time periods and then summing the results. Multiply each meter by the fitness index from T1 to T4, then add the products together. This result represents the weighted connectivity distance between modules M03 and M01. This calculation is performed once for each module pair within the analysis scope, ultimately generating a set of weighted connectivity distances for the modules.

[0114] S502: Call the module weighted connectivity distance set, compare the weighted connectivity distance value with the path optimization benchmark value according to the path length optimization principle, identify module pairs whose difference exceeds the benchmark, perform directional translation adjustment on the relative position coordinates of the module pairs and recalculate the distance to obtain the module relative position adjustment parameter set;

[0115] The generated set of weighted connectivity distances for modules is called, and the weighted connectivity distance value of module pair (M01, M03) is extracted. Based on the path length optimization principle, this value is first compared with a path optimization benchmark value. This benchmark value is set with reference to the ideal pedestrian flow distance of similar functional combinations (retail and leisure) in typical commercial buildings, and is set as follows: Meters, and summing this ideal distance with the time-of-day fit index. Multiply to obtain the base value Next, the difference between the current calculated value and the benchmark value is compared, and the difference is calculated as follows: It then determines whether the difference exceeds a preset range, which is defined as the baseline value. ,Right now ,because Greater than Therefore, module pair (M01, M03) is identified as needing position adjustment. Subsequently, a directional translation adjustment is performed on the relative position coordinates of this module pair. First, the direction of the adjustment vector is determined, which is determined by the coordinates of module M01. Coordinates pointing to module M03 That is, vector To standardize the distance traveled, we need to calculate the unit vector of the vector. First, we calculate its magnitude, which is the square root of the sum of the squares of the vector components. Then, each component of the vector is divided by the magnitude to obtain the unit direction vector, whose components are approximately Set the adjustment step size to Meters, translate module M01 along this unit vector direction, its new coordinates are the old coordinates plus the product of the unit vector and the step size, that is... The recalculated and adjusted physical distance is approximately meters, the new weighted connectivity distance is approximately The module number M01 and the new coordinates after the adjustment will be changed. Record these parameters to obtain the module's relative position adjustment parameter set.

[0116] S503: Call the module relative position adjustment parameter set, perform verification on the layout coordinate set according to the building code parameters, search the structural spacing, passage path width and ventilation and lighting parameter range, eliminate layouts that do not conform to the building code and classify and code them, and generate a diverse set of building schemes.

[0117] The generated module relative position adjustment parameter set is invoked, that is, the new coordinates of module M01 are... Module M03 coordinates are maintained Without changing anything, firstly, for this new layout coordinate set, a verification is performed based on the building code parameters. These parameters are obtained by retrieving them from the building design code database. The first item is the structural spacing, which requires that the outer boundary of the module be aligned with the nearest load-bearing column (assuming it is located at...). The distance between them must not be less than Meters, calculated, M01 (according to Calculate, set as The boundary of the column is closest to the point where the column is. meters, greater than The first requirement is meters, which meets the requirements. The second requirement is the width of the passageway; the main public corridor width must be no less than [a certain value]. The clearance between modules M01 and M03 is approximately meters. meters (assuming M03 is) ), greater than The first requirement is meters, which meets the requirements. The third requirement is ventilation and lighting parameters, which require that the straight-line distance between the business area and the exterior windows or atrium not exceed [a certain value]. meters, assuming the east exterior wall of the building is located at At location M03, the distance from the outer wall meters, M01 is a distance from the outer wall M01 does not meet this specification, therefore this layout scheme will be rejected. The system will then attempt to generate another adjustment scheme, such as shifting M01 only in the positive Y-axis direction. Rice to The entire set of verifications is then re-executed. Assuming that all verification items of the new scheme pass, it is categorized and coded as "V-OPT-001", meaning "effective scheme - optimized - number 001". The previous scheme that was eliminated due to insufficient lighting is coded as "I-LGT-001", meaning "invalid scheme - lighting problem - number 001". Finally, through multiple iterations of adjustment and verification, the valid schemes that pass the verification, their codes, module coordinates and other information are summarized to generate a diverse set of architectural schemes.

[0118] Table 5. Diverse Architectural Schemes

[0119] Scheme coding Solution Status Module M01 coordinates Module M03 coordinates V-OPT-001 efficient (15.0，24.0，0.0) (30.0，40.0，0.0) I-STR-001 invalid (16.4，26.4，0.0) (30.0，40.0，0.0)

[0120] As shown in Table 5, this table records the different building layout schemes generated after final verification, and marks the validity status of each scheme and its specific spatial coordinate data.

[0121] Please see Figure 7 A rapid construction system for diverse building solutions based on the modular concept, including:

[0122] The spatial streamline acquisition module acquires streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space through spatial sensors. It also performs ratio calculations on the streamline density values ​​between adjacent nodes, uses a gradient descent algorithm to correlate the ratio results with the node coordinates, establishes a spatial pressure distribution model, and transmits it to the pressure mapping modeling module.

[0123] The pressure mapping modeling module calls the node pressure of the spatial pressure distribution model, collects the module function type parameters and usage frequency parameters, calculates the pressure adaptation coefficient, sorts the nodes that exceed the pressure threshold, generates a module location configuration table, and passes it to the function adaptation calculation module.

[0124] The function adaptation calculation module calls the module location configuration table, collects the node time sequence occupancy frequency and directional passage probability, calculates the time period adaptation index based on the sorting weight, performs normalization processing using a weighted average algorithm, generates a module time sequence layout scheme, and passes it to the time sequence layout generation module.

[0125] The temporal layout generation module calls the module temporal layout scheme to execute spatial arrangement, adjusts the module position order according to the time period adaptation index, and allocates them to the core access area and the peripheral auxiliary area to form a phased building layout form, which is then passed to the path optimization and adjustment module.

[0126] The path optimization and adjustment module, based on the phased building layout form optimization module's connection path, performs a weighted calculation of the connection distance between adjacent modules and the time period adaptation index, adjusts the relative positions of modules according to the path length optimization principle, and generates a diverse set of building schemes.

[0127] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for rapidly assembling diverse building solutions based on a modular concept, characterized in that: Includes the following steps: S1: Obtain the streamline density value, passage direction vector and connectivity strength coefficient of the nodes in the building space through spatial sensors. The connectivity strength coefficient is set with reference to the physical accessibility and visual permeability between nodes. The streamline density values ​​between adjacent nodes are calculated by ratio. The gradient descent algorithm is used to correlate the ratio results with the node coordinate positions to establish a spatial pressure distribution model. S2: Call the node pressure of the spatial pressure distribution model, collect the functional type parameters of multiple modules to calculate the pressure adaptation coefficient, obtain the module usage frequency parameter, sort the nodes with pressure adaptation coefficients greater than the pressure threshold, and generate a module location configuration table. S3: Call the module location configuration table, index and retrieve the node module location information, collect the node's time-series occupancy frequency parameter and directional passage probability parameter, aggregate the two types of parameters according to the node sequence and perform consistency verification to generate a node parameter set; Based on the node parameter set, the sorting weight parameter in the module location configuration table is called to perform a weighted comparison operation on the occupancy frequency parameter and the direction passage probability parameter in the same time period, calculate the node time period weighted value and aggregate it according to the time index to generate a time period adapted weighted distribution set. Based on the time period-adapted weighted distribution set, the weighted value sequence is normalized using the minimum-maximum normalization method. A time period index sequence is established and arranged and adjusted according to the time index to generate a module time sequence layout scheme. S4: Call the module time sequence layout scheme to execute the module spatial arrangement, adjust the position order according to the time period adaptation index of the module in different time periods, and allocate the module to the core access position and the peripheral auxiliary position to form a phased building layout form.

2. The method for rapid construction of diverse building schemes based on the modular concept according to claim 1, characterized in that, The spatial pressure distribution model includes node pressure gradient values, spatial stress distribution intervals, and pressure coordinate mapping relationships. The module location configuration table includes node pressure level sequences, module configuration priorities, and spatial coordinate indexes. The module temporal layout scheme includes a time-period adaptation index set, module dynamic temporal distribution, and time-normalized weight parameters. The phased building layout form includes core functional area layout, auxiliary functional area layout, and temporal location association structure. The core accessible location is a node with a time-period adaptation index higher than the 75th percentile, and the peripheral auxiliary location is a node with a time-period adaptation index lower than the 25th percentile.

3. The method for rapid construction of diverse building schemes based on the modular concept according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space using spatial sensors; perform ratio calculations on the streamline density parameters of adjacent nodes; index and map the ratio results to the traffic direction vectors to generate a streamline density ratio sequence set. S102: Based on the streamline density ratio sequence set, collect the spatial coordinate parameters of adjacent nodes. For the numerical deviation between the ratio sequence elements and the node coordinates, use the gradient descent algorithm to control the gradient direction vector to decrease iteratively, record the error convergence point and aggregate it to generate a coordinate mapping distribution set. S103: Based on the coordinate mapping distribution set, call the node connectivity strength coefficient, perform weighted normalization operation on the original streamline density value of the node, associate the superposition result with the original coordinate of the node, calculate the pressure gradient based on the node spatial difference, and establish a spatial pressure distribution model.

4. The method for rapid construction of diverse building schemes based on the modular concept according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Obtain the node pressure parameters of the spatial pressure distribution model, collect the function type parameters of multiple modules, match the node pressure parameters with the function type parameters according to the node index, perform ratio calculation on the matching results and compare them with the pressure benchmark value to generate a node pressure response distribution set; S202: Based on the node pressure response distribution set, collect the usage frequency parameters of multiple modules, perform weighted calculation on the node response offset and usage frequency and compare it with the pressure threshold, filter nodes higher than the threshold and sort them to generate a node priority sequence set; S203: Based on the node priority sequence set, perform a corresponding mapping between the spatial location index of the node and the module number, establish a correspondence table between nodes and modules, and aggregate and integrate the spatial location parameters of the nodes in the sequence according to the correspondence table to generate a module location configuration table.

5. The method for rapid construction of diverse building schemes based on the modular concept according to claim 1, characterized in that, The specific steps of S4 are as follows: S401: Obtain the time period adaptation index in different time periods in the module time sequence layout scheme, calculate the difference between the module adaptation index and the average adaptation index benchmark value, divide the interval according to the adaptation index change rate threshold, perform level coding according to the interval index, and generate the module time period adaptation classification result. S402: Based on the module time period adaptation and hierarchical results, call the coordinate mapping distribution set and time period index sequence, analyze the node position centrality in the coordinate mapping distribution set to calculate the core accessibility coordinate coefficient, and perform weighted summation with the module time period weight value and serialize and arrange it to obtain the module space priority sequence set; S403: Based on the module space priority sequence set, read the position weight factor and calculate the module space occupancy rate. After comparing it with the layout volume threshold, perform position offset correction calculation, allocate the module to the core access position and the peripheral auxiliary position, and aggregate the correction index mapping to obtain the staged building layout form.

6. The method for rapid construction of diverse building schemes based on the modular concept according to claim 5, characterized in that, The adaptation index change rate threshold is determined based on the average change amplitude of the adaptation index in adjacent time periods in the original time-series layout data. The layout volume threshold is determined based on the relationship between the total building volume control parameters and the module design volume ratio.

7. The method for rapid construction of diverse building schemes based on the modular concept according to claim 1, characterized in that, The method also includes step S5: S5: Based on the phased building layout, optimize the connection path between modules, calculate the weighted connection distance between adjacent modules and the time period adaptation index, adjust the relative position of modules through the path length optimization principle, verify that the adjusted layout meets the building code requirements, and generate a diverse set of building schemes. The diverse set of architectural solutions includes spatial layout optimization paths, standard adaptation verification results, and architectural form combination schemes.

8. The method for rapid construction of diverse building schemes based on the modular concept according to claim 7, characterized in that, The specific steps of S5 are as follows: S501: Based on the phased building layout morphology data, extract the module spatial coordinate set and boundary constraint parameters, calculate the three-dimensional Euclidean distance between adjacent modules, map the distance value with the corresponding time period adaptation index and perform weighted accumulation to generate a module weighted connectivity distance set; S502: Call the weighted connectivity distance set of the modules, compare the weighted connectivity distance value with the path optimization benchmark value according to the path length optimization principle, identify the module pairs whose difference exceeds the benchmark, perform directional translation adjustment on the relative position coordinates of the module pairs and recalculate the distance to obtain the module relative position adjustment parameter set; S503: Call the relative position adjustment parameter set of the module, perform verification on the layout coordinate set according to the building code parameters, search the structural spacing, passage path width and ventilation and lighting parameter range, eliminate layouts that do not conform to the building code and classify and encode them, and generate a diverse set of building schemes.

9. A rapid construction system for diverse building solutions based on modular design, characterized in that: The system is used to implement the rapid construction method for diverse building schemes based on the modular concept as described in any one of claims 1-8, and the system includes: The spatial streamline acquisition module acquires streamline density values, traffic direction vectors, and connectivity coefficients of nodes within the building space through spatial sensors. It also performs ratio calculations on the streamline density values ​​between adjacent nodes, uses a gradient descent algorithm to correlate the ratio results with the node coordinates, establishes a spatial pressure distribution model, and transmits it to the pressure mapping modeling module. The pressure mapping modeling module calls the node pressure of the spatial pressure distribution model, collects the module function type parameters and usage frequency parameters, calculates the pressure adaptation coefficient, sorts the nodes that exceed the pressure threshold, generates a module location configuration table, and passes it to the function adaptation calculation module. The functional adaptation calculation module calls the module location configuration table to index and retrieve the node module location information, collects the temporal occupancy frequency parameters and directional passage probability parameters of the nodes, aggregates the two types of parameters according to the node sequence and performs consistency verification to generate a node parameter set; based on the node parameter set, it calls the sorting weight parameters in the module location configuration table to perform a weighted comparison operation on the occupancy frequency parameters and directional passage probability parameters of the same time period, calculates the node time period weighted value and aggregates it according to the time index to generate a time period adaptation weighted distribution set; according to the time period adaptation weighted distribution set, it uses the min-max normalization method to perform normalization calculation on the weighted value sequence, establishes a time period index sequence and arranges and adjusts the intervals according to the time index to generate a module temporal layout scheme; The temporal layout generation module calls the temporal layout scheme of the module to perform spatial arrangement, adjusts the position order of the module according to the time period adaptation index, and allocates it to the core access area and the peripheral auxiliary area to form a phased building layout form, which is then passed to the path optimization and adjustment module. The path optimization and adjustment module, based on the connection path of the phased building layout optimization module, performs a weighted calculation of the connection distance between adjacent modules and the time period adaptation index, adjusts the relative positions of the modules according to the path length optimization principle, and generates a diverse set of building schemes.

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