A design parameter generation system and method for building landscape schemes

Abstract

This application provides a system and method for generating design parameters for architectural landscape schemes. The method includes: determining the initial value range of each design variable; constructing a relationship graph between the design variables; transferring constraints along explicit edges to determine an explicit feasible region jointly defined by all explicit edges; identifying all paths containing implicit edges within the explicit feasible region and calculating the cumulative coupling effect value on each path; selecting an adjustment path based on the cumulative coupling effect value, adjusting the values ​​of each design variable along the adjustment path, and verifying whether the adjusted values ​​satisfy the explicit feasible region; iteratively executing path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet preset requirements, and outputting design parameters that conform to all explicit constraints and implicit coupling constraints. This application's scheme can achieve joint decoupling optimization of explicit constraints and implicit conflicts, thereby improving the quality of generated architectural landscape design parameters.

Description

Technical Field

[0001] This application relates to the field of digital architectural design technology, and more specifically, to a system and method for generating design parameters for architectural landscape schemes. Background Technology

[0002] With the rapid development of digital building design technology, parametric modeling and performance optimization methods have been widely applied in the architectural landscape design phase. Using computer-aided tools, designers can quantitatively adjust key design variables such as building orientation, window-to-wall ratio, external shading dimensions, tree layout, and water area. Combined with energy consumption simulation and daylighting analysis, this allows for the initial optimization of energy-saving design parameters.

[0003] However, existing parameter generation methods often treat each design variable as an independent control object, failing to fully explore the inherent relationships between variables. Specifically, the geometric and thermal analytical relationships (i.e., explicit constraints) between building orientation, window-to-wall ratio, and external shading dimensions are not systematically used to compress the search space, resulting in a large number of invalid parameter combinations being included in the optimization scope, leading to low computational efficiency. Simultaneously, implicit coupling relationships that cannot be directly described by analytical expressions, such as the shading-lighting conflict between tree canopy width and window-to-wall ratio, and the lighting-heating conflict between window-to-wall ratio and external shading dimensions, are often treated separately or completely ignored in traditional methods. This results in design parameters that, while geometrically self-consistent, have significant defects in energy-saving performance, such as excessively high cooling loads in summer or insufficient natural lighting in winter. This separate handling of explicit constraints and implicit conflicts severely restricts the accuracy and efficiency of design parameter generation. Therefore, how to achieve joint decoupling optimization of explicit constraints and implicit conflicts to improve the quality of generated architectural landscape design parameters has become a challenge for the industry. Summary of the Invention

[0004] This application provides a system and method for generating design parameters for architectural landscape schemes, which can achieve joint decoupling optimization of explicit constraints and implicit conflicts, thereby improving the quality of generated architectural landscape design parameters.

[0005] In a first aspect, this application provides a method for generating design parameters for architectural landscape schemes, comprising the following steps:

[0006] Determine the initial value range for each design variable;

[0007] Construct a relationship graph among the design variables. The nodes of the relationship graph represent design variables, and the edges represent the relationships between design variables. Deterministic relationships with analytical expressions are called explicit edges, and relationships without analytical expressions that need to be evaluated by coupling effect evaluation rules are called implicit edges.

[0008] Constraints are propagated along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges;

[0009] Within the explicit feasible region, identify all paths containing implicit edges and calculate the cumulative coupling effect value on each path;

[0010] Based on the cumulative coupling effect value, select an adjustment path, adjust the values ​​of each design variable along the adjustment path, and verify whether the adjusted values ​​satisfy the explicit feasible region.

[0011] Iteratively execute path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and output design parameters that comply with all explicit and implicit coupling constraints.

[0012] Furthermore, determining the initial value range of each design variable specifically includes:

[0013] Based on the type and level of the architectural landscape scheme and the climate zone of the project location, the minimum allowable value, maximum allowable value and default value of each design variable are preset;

[0014] The design variables include at least the building orientation angle, south-facing window-to-wall ratio, west-facing window-to-wall ratio, external shading dimensions, tree planar coordinates, tree crown width, and water area;

[0015] The initial range of the building orientation angle is preset based on the solar trajectory and prevailing wind direction of the project location, and the initial range of the south-facing window-to-wall ratio is wider than that of the west-facing window-to-wall ratio.

[0016] Furthermore, the coupling effect evaluation rules include:

[0017] An evaluation function is configured for each implicit edge. The input of the evaluation function is the current value of the two design variables connected by the implicit edge, and the output is the coupling effect evaluation value that characterizes the degree of coupling conflict between the two.

[0018] The evaluation function includes a lighting-heating conflict evaluation rule and a shading-lighting conflict evaluation rule; wherein, the lighting-heating conflict evaluation rule is used to evaluate the implicit conflict between the window-to-wall ratio and the external shading size under the same orientation, and the shading-lighting conflict evaluation rule is used to evaluate the implicit conflict between the tree crown width and the window-to-wall ratio under the same orientation.

[0019] Furthermore, the construction of the relationship diagram between the various design variables specifically includes:

[0020] Treat each design variable as a node;

[0021] For any two design variables, determine whether there is a geometric dependency, physical coupling relationship or functional constraint relationship between them;

[0022] If the above relationship exists and has a closed analytic expression, then an explicit edge is established between the two corresponding nodes, and the forward and reverse propagation directions of the analytic expression are recorded.

[0023] If the above relationship exists but does not have a closed analytic expression, then an implicit edge is established between the two corresponding nodes, and the corresponding coupling effect evaluation rule is associated with the implicit edge.

[0024] Among them, the explicit edges between the window-to-wall ratio node and the external shading size node of each orientation belonging to the same building facade orientation are divided into the same explicit edge group, and the explicit edge groups corresponding to different facade orientations are independent of each other.

[0025] Based on the nodes, explicit edges, and implicit edges, construct the relationship graph between the design variables.

[0026] Furthermore, the step of performing constraint propagation along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges specifically includes:

[0027] Starting from the independent variable node with no explicit input, calculate the value range of the dependent variable node in sequence according to the direction of the explicit edge;

[0028] When a dependent variable node has multiple explicit edge inputs, take the intersection of the intervals derived from each input;

[0029] For explicit edge groups of window-to-wall ratios and external shading dimensions of different orientations within the same building facade, synchronous constraint transfer is performed to ensure geometric self-consistency.

[0030] The Cartesian product of the value intervals of all nodes constitutes the explicit feasible region.

[0031] Furthermore, the step of identifying all paths containing implicit edges within the explicit feasible region and calculating the cumulative coupling effect value on each path specifically includes:

[0032] In the association graph subgraph corresponding to the explicit feasible region, each node containing a hidden edge is taken as the starting node, and all reachable nodes are traversed along the direction of the association edge to search for a sequence of nodes that are alternately connected by nodes and edges and contain at least one hidden edge.

[0033] Each of the sequences is identified as a path containing hidden edges;

[0034] For each identified path, obtain the coupling effect evaluation value corresponding to each of the hidden edges on the path, and sum the coupling effect evaluation values ​​to obtain the cumulative coupling effect value of the path.

[0035] Furthermore, the step of selecting an adjustment path based on the cumulative coupling effect value, adjusting the values ​​of each design variable along the adjustment path, and verifying whether the adjusted values ​​satisfy the explicit feasible region specifically includes:

[0036] Calculate the ratio of the cumulative coupling effect value of each path containing implicit edges to the preset adjustment cost, and select the path with the smallest ratio as the current adjustment path. The preset adjustment cost is preset according to the type of design variables on the path, and the adjustment cost of building orientation is higher than the adjustment cost of tree plane coordinates.

[0037] Along the direction of the adjustment path, the values ​​of each design variable on the path are finely adjusted sequentially according to a preset step size;

[0038] After each variable adjustment is completed, it is checked whether the variable is still within the value range corresponding to the explicit feasible region. If it exceeds the range, the adjustment is rolled back and the step size is reduced.

[0039] Furthermore, the iterative execution path selection, value adjustment, and explicit feasible region verification continue until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, outputting design parameters that conform to all explicit and implicit coupling constraints, specifically including:

[0040] At the beginning of each iteration, an adjustment path is selected based on the cumulative coupling effect value of each path containing hidden edges.

[0041] Along the selected adjustment path, the values ​​of each design variable on the path are finely adjusted in turn according to the preset step size. After each variable is adjusted, it is checked whether the variable is still within the value range corresponding to the explicit feasible domain. If it exceeds the range, the adjustment is rolled back and the step size is reduced.

[0042] After one round of adjustments, the coupling effect evaluation values ​​of all implicit edges are recalculated;

[0043] The iteration terminates when the preset requirements are met; otherwise, it proceeds to the next iteration.

[0044] After the iteration terminates, output the final values ​​of all current design variables.

[0045] Furthermore, the preset requirements specifically include:

[0046] Configure a corresponding evaluation value threshold for each hidden edge;

[0047] When the current coupling effect evaluation value of all hidden edges is lower than their respective thresholds, it is determined that the first preset requirement is met;

[0048] Alternatively, when there is at least one hidden edge whose evaluation value is higher than its threshold, for each hidden edge that is higher than the threshold, if the hidden edge belongs to multiple paths, the path with the largest cumulative coupling effect value is taken as its representative path. When the rate of change of the cumulative coupling effect value of all representative paths in two consecutive iterations is less than the preset convergence accuracy, and all hidden edges that are higher than the threshold do not involve the west-facing window-to-wall ratio node, it is determined that the second preset requirement is met.

[0049] The preset requirement is determined to be met when either the first preset requirement or the second preset requirement is met.

[0050] Secondly, this application provides a design parameter generation system for architectural landscape schemes, comprising:

[0051] The initial value selection module is used to determine the initial value range of each design variable;

[0052] The association graph construction module is used to construct the association graph between various design variables. The nodes of the association graph represent design variables, and the edges represent the association relationships between design variables. Among them, deterministic associations with analytical expressions are called explicit edges, and associations without analytical expressions but requiring evaluation through coupling effect evaluation rules are called implicit edges.

[0053] A constraint propagation module is used to propagate constraints along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges.

[0054] The path identification module is used to identify all paths containing implicit edges within the explicit feasible region and calculate the cumulative coupling effect value on each path.

[0055] The path adjustment module is used to select an adjustment path based on the cumulative coupling effect value, adjust the values ​​of each design variable along the adjustment path, and verify whether the adjusted values ​​satisfy the explicit feasible region.

[0056] The iterative control module is used to iteratively perform path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and output design parameters that comply with all explicit and implicit coupling constraints.

[0057] Thirdly, this application provides a computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described method for generating design parameters for architectural landscape schemes.

[0058] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for generating design parameters for architectural landscape schemes.

[0059] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0060] This application constructs an explicit and implicit relationship graph among design variables, combines explicit constraint transmission with implicit path cumulative effect evaluation, and adopts a cost-priority path adjustment strategy to ultimately achieve self-consistent and efficient generation of architectural landscape design parameters. First, a relationship graph is constructed using design variables as nodes and explicit and implicit edges as connections, unifying geometric analytical relationships and physical coupling conflicts within the same graph structure. This achieves structural decoupling of explicit constraints and implicit conflicts, providing a clear graphical model foundation for subsequent constraint transmission and path search. Second, constraints are transmitted along explicit edges, and the intersection of the input intervals of each dependent variable node is taken to form an explicit feasible region jointly defined by all explicit edges. This transforms scattered analytical constraints into independent value intervals for each variable, effectively compressing the optimization search space and eliminating inconsistencies that do not satisfy geometric and thermal self-consistency. The algorithm combines parameters to reduce computational redundancy. Then, it identifies all paths containing implicit edges within the explicit feasible region and sums the coupling effect evaluation values ​​of each implicit edge on the path to obtain the cumulative coupling effect value. This transforms implicit conflicts that were originally unrepresentable into comparable path weights. A preset adjustment cost is then introduced, and the adjustment path is selected based on the minimum ratio of the cumulative coupling effect value to the adjustment cost. Priority is given to adjusting the path with the highest conflict resolution efficiency per unit cost, overcoming the inefficiency of equal weights or blind adjustments. During the adjustment process, each step verifies whether the variables fall within the explicit feasible region and employs a step-size backoff mechanism to ensure that the adjustment always satisfies all explicit constraints, avoiding damage to geometric self-consistency due to the resolution of implicit conflicts. Finally, it uses dual preset requirements to control the termination of the iteration, balancing the accuracy of the optimal solution with engineering convergence efficiency.

[0061] In summary, this application achieves joint decoupling optimization of explicit constraints and implicit conflicts through explicit constraint pre-pruning of the search space, path quantification of implicit conflicts, cost-priority path selection, and iterative adjustment of constraint self-verification, which significantly improves the generation quality and energy-saving performance of architectural landscape design parameters. Attached Figure Description

[0062] Figure 1 This is an exemplary flowchart of a method for generating design parameters for architectural landscape schemes according to some embodiments of this application;

[0063] Figure 2 This is an example schematic diagram illustrating the calculation of cumulative coupling effect values ​​according to some embodiments of this application;

[0064] Figure 3 This is a structural schematic diagram of a system for generating design parameters for architectural landscape schemes, as shown in some embodiments of this application.

[0065] Figure 4 This is a structural schematic diagram of a computer device for implementing a method for generating design parameters for architectural landscape schemes, according to some embodiments of this application. Detailed Implementation

[0066] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] refer to Figure 1 The figure is an exemplary flowchart of a method for generating design parameters for architectural landscape schemes according to some embodiments of this application. The method for generating design parameters for architectural landscape schemes mainly includes the following steps:

[0068] In step 101, the initial value range of each design variable is determined.

[0069] In this embodiment, the initial value range of each design variable can be determined by the following steps:

[0070] First, obtain the type and level of the architectural landscape scheme to be designed and the climate zone of the project location. The type and level of the architectural landscape scheme can be, for example, residential, office, commercial complex or cultural venue. The climate zone of the project location can be divided into severe cold, cold, hot summer and cold winter, hot summer and warm winter, temperate, etc. Then, for each type of design variable, based on its physical meaning and common sense of energy-saving design, preset its minimum allowable value, maximum allowable value and default value.

[0071] In practical applications, design variables include at least: building orientation angle, south-facing window-to-wall ratio, west-facing window-to-wall ratio, external shading dimensions, such as the overhang length of horizontal shading panels, tree planar coordinates, tree crown width, and water area. For building orientation angles, the initial value range can be preset to 15° east of south to 15° west of south, based on the solar trajectory (solar altitude angle on the winter solstice and azimuth angle on the summer solstice) and the prevailing summer wind direction. The default value is set to due south, i.e., 180°. For the south-facing window-to-wall ratio, in hot-summer and cold-winter regions, the minimum allowable value is set to 0.30, the maximum allowable value is set to 0.50, and the default value is set to 0.40. This is because south-facing areas receive more solar radiation in winter to reduce heating load, and in summer, appropriate shading can effectively control heat gain, thus allowing for a relatively large window-to-wall ratio. For the west-facing window-to-wall ratio, due to the significant increase in cooling load caused by afternoon sun exposure in summer, the minimum allowable value is set to 0.20, the maximum allowable value is set to 0.35, and the default value is set to 0.25. The initial value range for external shading dimensions is determined based on the window opening height, and is usually preset to 0.2 of the window height. The initial value ranges from 0.4 times the window height to 0.6 times the window height, with a default value of 0.4 times. This is because this ratio range effectively blocks direct sunlight in summer while ensuring sunlight can enter the room in winter, achieving a seasonal shading balance. The initial value range for the tree plane coordinates is a ring-shaped area 3 to 10 meters away from the building's exterior wall, with a default value of 5 meters away from the exterior wall. The tree canopy width is preset from 2 to 8 meters based on common landscape tree species, with a default value of 4 meters. This is because this canopy width range can cover the common specifications of most landscape trees, and the default value of 4 meters can provide moderate summer shading while avoiding excessive shading of winter sunlight and building views. The proportion of water body area to the total site area is preset from 1% to 10%, with a default value of 5%. This proportion range can provide effective evaporative cooling while controlling the construction and maintenance costs of water bodies and avoiding excessive occupation of green or activity space. In the above manner, an initial value range including minimum allowable value, maximum allowable value and default value is established for all design variables, which serves as the basis for subsequent correlation diagram construction and parameter optimization. It should be noted that the specific values ​​mentioned above are only an example of this embodiment, and can be adjusted according to different scheme types and climate zones in actual applications.

[0072] In step 102, a relationship graph is constructed between the design variables. The nodes of the relationship graph represent design variables, and the edges represent the relationships between the design variables. Deterministic relationships with analytical expressions are called explicit edges, and relationships without analytical expressions that need to be evaluated by coupling effect evaluation rules are called implicit edges.

[0073] In this embodiment, the relationship diagram between the design variables can be constructed using the following steps:

[0074] Treat each design variable as a node;

[0075] For any two design variables, determine whether there is a geometric dependency, physical coupling relationship or functional constraint relationship between them;

[0076] If the above relationship exists and has a closed analytic expression, then an explicit edge is established between the two corresponding nodes, and the forward and reverse propagation directions of the analytic expression are recorded.

[0077] If the above relationship exists but does not have a closed analytic expression, then an implicit edge is established between the two corresponding nodes, and the corresponding coupling effect evaluation rule is associated with the implicit edge.

[0078] Among them, the explicit edges between the window-to-wall ratio node and the external shading size node of each orientation belonging to the same building facade orientation are divided into the same explicit edge group, and the explicit edge groups corresponding to different facade orientations are independent of each other.

[0079] Based on the nodes, explicit edges, and implicit edges, construct the relationship graph between the design variables.

[0080] It should be noted that, in this application, explicit edges are used to connect two design variable nodes with closed analytical expressions and record the forward and reverse propagation directions of the analytical expression; implicit edges are used to connect two design variable nodes without closed analytical expressions but with significant coupling effects and associate them with corresponding coupling effect evaluation rules; explicit edge groups are sets used to classify explicit edges between window-to-wall ratio nodes and external shading size nodes belonging to the same building facade orientation, and explicit edge groups corresponding to different facade orientations are independent of each other; the association graph is a graph structure model used to comprehensively display all design variable nodes and the connection relationships between all explicit and implicit edges between nodes.

[0081] In practical application, firstly, each design variable is used as a node in the association diagram. The design variables include at least the building orientation angle, the south-facing window-to-wall ratio, the west-facing window-to-wall ratio, the external shading dimensions, the tree planar coordinates, the tree crown width, and the water area.

[0082] Secondly, for any two design variables, determine whether there is a geometric dependency, physical coupling, or functional constraint relationship between them. If such a relationship exists and has a closed analytical expression, then establish an explicit edge between the nodes corresponding to the two design variables, and record the forward and reverse propagation directions of the analytical expression on this explicit edge. The forward propagation direction refers to the direction from an independent variable node to a dependent variable node, and the reverse propagation direction refers to the direction from a dependent variable node to an independent variable node. It should be further explained that determining whether there is a geometric dependency, physical coupling, or functional constraint relationship between two design variables can be done as follows: Based on the physical meaning of the design variables and professional knowledge in the field of architectural landscape design, a variable association knowledge base is pre-established. This knowledge base is used to record the association types between common design variable pairs. For example, there is a geometric dependency between the window-to-wall ratio and the window area because the window area equals the window-to-wall ratio multiplied by the facade area; this relationship can be directly expressed by a geometric formula. The building orientation angle and solar radiation... There is a physical coupling relationship between heat and light, because changes in orientation angle alter the angle between sunlight and the heated surface, directly affecting the amount of solar radiation received per unit area. This relationship is described by the laws of solar radiation physics. There is a functional constraint relationship between tree canopy width and the ratio of south-facing windows to walls, because excessively large tree canopies can block natural light from south-facing windows. The two mutually restrict each other in terms of building lighting function, but there is no single analytical expression. For any two design variables, matching is performed by querying the variable association knowledge base or based on the following defined rules: If there is a deterministic conversion relationship between the two variables that can be directly expressed by mathematical formulas using geometric quantities such as length, area, and angle, then a geometric dependency relationship exists; if there is a causal relationship between the two variables described by physical laws such as heat conduction, radiative heat transfer, and fluid mechanics, then a physical coupling relationship exists; if there is no direct mathematical or physical law connection between the two variables, but a change in one indirectly constrains the other through building functionality, thermal comfort, or visual comfort requirements, then a functional constraint relationship exists.

[0083] Then, if the above relationship exists but does not have a closed analytical expression, an implicit edge is established between the nodes corresponding to the two design variables, and a corresponding coupling effect evaluation rule is associated with the implicit edge. The coupling effect evaluation rule is used to calculate the coupling effect evaluation value of the implicit edge under the current design variable value, so as to characterize the degree of coupling conflict between the two design variables.

[0084] Furthermore, regarding the management of explicit edges, explicit edges between the window-to-wall ratio node and the external shading dimension node of each orientation belonging to the same building facade orientation are divided into the same explicit edge group. The explicit edge groups corresponding to different facade orientations are independent of each other. That is, the explicit edge between the window-to-wall ratio and the external shading dimension of the south-facing facade and the explicit edge between the window-to-wall ratio and the external shading dimension of the west-facing facade belong to different explicit edge groups and are not subject to cross-constraint transfer.

[0085] Finally, based on all the nodes, all explicit edges, and all implicit edges mentioned above, a relationship graph is constructed among the design variables. This relationship graph uses nodes to represent design variables, explicit edges to represent deterministic relationships with analytical expressions, and implicit edges to represent relationships without analytical expressions that need to be evaluated through coupling effect evaluation rules. At the same time, explicit edge groups are used to manage explicit edges with the same facade orientation. This relationship graph serves as the basic data structure for subsequent constraint transfer and path analysis.

[0086] Preferably, in some embodiments, the coupling effect evaluation rules can be determined using the following steps:

[0087] An evaluation function is configured for each implicit edge. The input of the evaluation function is the current value of the two design variables connected by the implicit edge, and the output is the coupling effect evaluation value that characterizes the degree of coupling conflict between the two.

[0088] The evaluation function includes a lighting-heating conflict evaluation rule and a shading-lighting conflict evaluation rule; wherein, the lighting-heating conflict evaluation rule is used to evaluate the implicit conflict between the window-to-wall ratio and the external shading size under the same orientation, and the shading-lighting conflict evaluation rule is used to evaluate the implicit conflict between the tree crown width and the window-to-wall ratio under the same orientation.

[0089] It should be noted that the evaluation function described in this application is a function used to calculate a quantitative value based on the current values ​​of the two design variables connected by the implicit edge; the coupling effect evaluation value is a quantitative value used to characterize the degree of coupling conflict between the two design variables connected by the implicit edge, and this value is output by the evaluation function; the daylighting-heating conflict type evaluation rule is a specific calculation rule used to evaluate the implicit conflict between the window-to-wall ratio and the external shading size under the same orientation; the shading-daylighting conflict type evaluation rule is a specific calculation rule used to evaluate the implicit conflict between the tree crown width and the window-to-wall ratio under the same orientation; the implicit conflict refers to a non-deterministic correlation between two design variables that do not have an explicit analytical expression but are mutually constrained by physical or functional coupling, resulting in a change in the value of one variable indirectly affecting the performance of the other variable.

[0090] In practical application, an evaluation function is first configured for each implicit edge. The input parameters of the evaluation function are the actual values ​​of the two design variables connected by the implicit edge in the current iteration. For example, for an implicit edge connecting the south-facing window-to-wall ratio node and the external shading size node, the evaluation function receives the specific values ​​of the south-facing window-to-wall ratio and the external shading size as input parameters. The evaluation function selects the corresponding evaluation rule for calculation based on the conflict type associated with the implicit edge. If the implicit edge is used to express the coupling conflict between the window-to-wall ratio and the external shading size, the lighting-heating conflict type evaluation rule is called; if the implicit edge is used to express the coupling conflict between the tree crown width and the window-to-wall ratio, the shading-lighting conflict type evaluation rule is called.

[0091] The specific calculation method of the lighting-heat gain conflict evaluation rule is as follows: calculate the solar radiation heat gain in the room under typical summer conditions based on the current window-to-wall ratio, and calculate the shading efficiency of the shading component against direct sunlight based on the current external shading size. Then, after normalizing the solar radiation heat gain and the shading efficiency, calculate the absolute value of the deviation between the two. The absolute value of the deviation is used as the evaluation value of the coupling effect of the hidden edge. The larger the evaluation value, the more serious the lighting-heat gain conflict between the current window-to-wall ratio and the external shading size.

[0092] The specific calculation method of the shading-lighting conflict evaluation rule is as follows: Based on the current tree crown width and the distance between the tree and the building exterior wall, calculate the vertical and horizontal shading angles of the tree crown on the south-facing window. Then, based on the current south-facing window-to-wall ratio, calculate the average illuminance of indoor natural lighting. After normalizing the shading angle and the illuminance, calculate the matching degree deviation between the two. Use the matching degree deviation as the coupling effect evaluation value of the implicit edge. The larger the evaluation value, the more serious the shading-lighting conflict between the current tree crown width and the south-facing window-to-wall ratio.

[0093] The evaluation function corresponding to each implicit edge runs independently, and outputs the coupling effect evaluation value of the implicit edge under the current design variable value. Finally, the coupling effect evaluation values ​​calculated for each implicit edge are used as the basis data for subsequent path analysis and iterative optimization, and are used to calculate the cumulative coupling effect value of each path containing implicit edges.

[0094] In step 103, constraint propagation is performed along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges.

[0095] In this embodiment, constrained propagation along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges can be achieved through the following steps:

[0096] Starting from the independent variable node with no explicit input, calculate the value range of the dependent variable node in sequence according to the direction of the explicit edge;

[0097] When a dependent variable node has multiple explicit edge inputs, take the intersection of the intervals derived from each input;

[0098] For explicit edge groups of window-to-wall ratios and external shading dimensions of different orientations within the same building facade, synchronous constraint transfer is performed to ensure geometric self-consistency.

[0099] The Cartesian product of the value intervals of all nodes constitutes the explicit feasible region.

[0100] It should be noted that, in this application, the independent variable node is used to represent a design variable node whose value range can be independently determined by the initial value range and is not constrained by other design variables; the dependent variable node is used to represent a design variable node whose value range needs to be calculated by passing it from the independent variable node or other dependent variable node through one or more explicit edges; the synchronous constraint transfer is used to jointly solve the explicit edge group between the window-to-wall ratio node and the external shading dimension node of each orientation within the same building facade, so as to ensure that the geometric or thermal relationship corresponding to all explicit edges in the group is satisfied at the same time; the explicit feasible region is used to represent the set of all combinations of design variable values ​​that simultaneously satisfy the analytical expression constraints corresponding to all explicit edges.

[0101] In practical application, firstly, nodes without any explicit edges pointing to themselves are identified from all design variable nodes. These nodes are designated as independent variable nodes, and their value ranges are directly taken from their initial value ranges without calculation through other nodes. Other nodes are designated as dependent variable nodes. Secondly, propagation calculations are performed according to the direction of explicit edges. For each dependent variable node, all explicit edges pointing to it are found. Each explicit edge records its analytical expression and its forward propagation direction. For each explicit edge pointing to the dependent variable node, the current value range of the source node connected to that explicit edge is used to calculate the dependent variable node. The analytical expression corresponding to the explicit edge derives a candidate value range for the dependent variable node. When a dependent variable node has only one explicit edge input, the candidate value range derived from the explicit edge is directly used as the value range of the dependent variable node. When a dependent variable node has multiple explicit edge inputs, the intersection operation of the multiple candidate value ranges derived from these explicit edges is performed, and the common overlapping part of these intervals is taken as the final value range of the dependent variable node. If multiple candidate value ranges do not have a common overlapping part, it is determined that there is a contradiction in the current design variable system. At this time, it is necessary to adjust the initial value range of the independent variable node or correct the analytical expression of the explicit edge.

[0102] Then, for the explicit edge groups between the window-to-wall ratio nodes and the external shading dimension nodes of each orientation within the same building facade, instead of passing them independently one by one, synchronous constraint passing is performed. Specifically, the analytical expressions corresponding to all explicit edges within the explicit edge group are combined into a system of equations. The value ranges of the window-to-wall ratio nodes and the external shading dimension nodes within the facade are taken as unknowns. Under the constraints of their respective initial value ranges, the system of equations is solved jointly to obtain a set of value ranges that simultaneously satisfy all analytical expressions. Through synchronous constraint passing, it is ensured that there is no contradiction in the geometric relationship between the window-to-wall ratio and the external shading dimension within the same facade, that is, geometric self-consistency is achieved.

[0103] Finally, after calculating the value ranges of all independent and dependent variable nodes, the value ranges of all nodes are combined. Specifically, the value ranges of each node are taken and Cartesian products are performed on these ranges in the order of the design variables to obtain a multidimensional space composed of the combinations of all design variable values. Each point in this multidimensional space represents a specific value of a set of design variables, and this set of values ​​simultaneously satisfies the analytical expression constraints corresponding to all explicit edges. Finally, the multidimensional space obtained by the Cartesian product operation is used as the explicit feasible region. This explicit feasible region is used to limit all feasible value combinations of all design variables under the condition of satisfying explicit constraints, and serves as the boundary condition for searching paths containing implicit edges and adjusting the values ​​of design variables in subsequent steps.

[0104] In this embodiment, by passing constraints step by step along the explicit edge direction starting from the independent variable node, all deterministic relationships between design variables described by analytical expressions can be transformed into independent value intervals for each variable. When a dependent variable node is constrained by multiple explicit edges, taking the intersection of each input interval ensures that the variable simultaneously satisfies all explicit constraints, thereby eliminating contradictory intervals. Synchronously passing constraints to the explicit edge group of the window-to-wall ratio and external shading size on the same facade can avoid geometric inconsistencies caused by passing constraints one by one, ensuring that the parameters on the same facade are geometrically and thermally self-consistent. Finally, the value intervals of all nodes are combined by Cartesian product to obtain the complete solution space, i.e., the explicit feasible region, where all design variables simultaneously satisfy all explicit constraints. This explicit feasible region serves as the boundary condition for subsequent optimization searches, effectively narrowing the search range of design parameters and avoiding invalid calculations on combinations that clearly do not satisfy explicit constraints, thereby improving the efficiency and reliability of parameter generation.

[0105] In step 104, within the explicit feasible region, all paths containing implicit edges are identified, and the cumulative coupling effect value on each path is calculated.

[0106] In this embodiment, reference Figure 2This figure is an example schematic diagram illustrating the calculation of cumulative coupling effect values ​​according to some embodiments of this application. In this embodiment, identifying all paths containing implicit edges within the explicit feasible region and calculating the cumulative coupling effect value on each path can be achieved using the following steps:

[0107] In the association graph subgraph corresponding to the explicit feasible region, each node containing a hidden edge is taken as the starting node, and all reachable nodes are traversed along the direction of the association edge to search for a sequence of nodes that are alternately connected by nodes and edges and contain at least one hidden edge.

[0108] Each of the sequences is identified as a path containing hidden edges;

[0109] For each identified path, obtain the coupling effect evaluation value corresponding to each of the hidden edges on the path, and sum the coupling effect evaluation values ​​to obtain the cumulative coupling effect value of the path.

[0110] It should be noted that the subgraph of the association graph in this application is used to represent the substructure composed of the same nodes and edges extracted from the complete association graph when all node value ranges are not empty under the explicit feasible region constraint; the reachable node is used to represent all nodes that can be reached by traversing along the direction of the association edge starting from the starting node; the cumulative coupling effect value is a quantitative index used to measure the comprehensive severity of coupling conflict between design variables corresponding to all implicit edges on a path.

[0111] In practical application, firstly, the relationship graph between the constructed design variables and the explicit feasible region determined by explicit edge constraints are obtained. Based on whether the value range of each node in the explicit feasible region is empty, all nodes with non-empty value ranges are filtered out. These nodes and all edges connecting them are extracted from the original relationship graph to form the relationship graph subgraph. In this subgraph, only those nodes and edges that are actually valid within the explicit feasible region are retained. Secondly, taking each node in the relationship graph subgraph containing at least one implicit edge as the starting node, starting from this starting node, all reachable nodes are traversed along the direction of the relationship edges, including the direction of explicit edges and implicit edges. During the traversal, the nodes and edges connected to the nodes are recorded. The sequence is formed by alternating edges, and the nodes in the sequence must not appear repeatedly. For each such sequence, check whether it contains at least one hidden edge. If it does, the sequence is identified as a path containing a hidden edge. Repeat the above operation for all starting nodes to collect all paths that meet the conditions in the subgraph of the association graph. Then, for each identified path containing a hidden edge, obtain all the hidden edges traversed on the path. For each hidden edge, according to the coupling effect evaluation rule associated with the hidden edge, obtain the coupling effect evaluation value corresponding to the hidden edge in the current iteration round. Then, sum the coupling effect evaluation values ​​of all hidden edges on the path. The sum is the cumulative coupling effect value of the path.

[0112] In step 105, an adjustment path is selected based on the cumulative coupling effect value, the values ​​of each design variable are adjusted along the adjustment path, and it is verified whether the adjusted values ​​satisfy the explicit feasible region.

[0113] In this embodiment, selecting an adjustment path based on the cumulative coupling effect value, adjusting the values ​​of each design variable along the adjustment path, and verifying whether the adjusted values ​​satisfy the explicit feasible region can be achieved through the following steps:

[0114] Calculate the ratio of the cumulative coupling effect value of each path containing implicit edges to the preset adjustment cost, and select the path with the smallest ratio as the current adjustment path. The preset adjustment cost is preset according to the type of design variables on the path, and the adjustment cost of building orientation is higher than the adjustment cost of tree plane coordinates.

[0115] Along the direction of the adjustment path, the values ​​of each design variable on the path are finely adjusted sequentially according to a preset step size;

[0116] After each variable adjustment is completed, it is checked whether the variable is still within the value range corresponding to the explicit feasible region. If it exceeds the range, the adjustment is rolled back and the step size is reduced.

[0117] It should be noted that the preset adjustment cost in this application is used to quantify the comprehensive cost required to adjust all design variables on a path. This cost is preset according to the type of each design variable on the path, and the adjustment cost of building orientation is higher than the adjustment cost of tree plane coordinates.

[0118] In practical application, firstly, for each path, based on the types of all design variables on that path, a preset adjustment cost table is consulted to calculate the preset adjustment cost for that path. In this preset adjustment cost table, the adjustment cost for building orientation is set higher than the adjustment cost for tree plane coordinates; for example, the adjustment cost for building orientation is 10, and the adjustment cost for tree plane coordinates is 1. Other variable types are assigned adjustment costs between these two values ​​based on their overall impact on the design scheme. The cumulative coupling effect value of each path is divided by its preset adjustment cost to obtain the ratio corresponding to each path. Among all paths, the path with the smallest ratio is selected as the current adjustment path. Next, the sequence of design variables on the current adjustment path is obtained. This sequence is arranged from front to back according to the direction of the associated edges. For each design variable in the sequence, the preset step size corresponding to the variable is obtained. According to the direction of the current adjustment path, the current value of the variable is increased or decreased by a preset step size to complete one fine adjustment. The direction of the fine adjustment is determined by the direction of coupling conflict resolution indicated by the implicit edge on the path. For example, when the window-to-wall ratio is too large, resulting in serious conflicts between daylighting and heat gain, fine adjustment is performed along the direction of reducing the window-to-wall ratio.

[0119] Then, after fine-tuning each design variable, immediately verify whether the new value of the variable is still within the value range corresponding to the explicit feasible region, that is, determine whether the value is not less than the minimum allowable value of the variable and not greater than the maximum allowable value of the variable. If the new value is within the explicit feasible region, retain the adjustment and continue fine-tuning the next design variable on the path. If the new value exceeds the explicit feasible region, perform a rollback operation, restore the value of the variable to the value before fine-tuning, and reduce the preset step size of the variable, for example, to half of the original step size, and then try fine-tuning again using the reduced step size. If it still exceeds the explicit feasible region after reducing the step size, skip the variable, do not adjust it, and continue processing the next design variable on the path.

[0120] In step 106, the path selection, value adjustment and explicit feasible region verification are performed iteratively until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and the design parameters that meet all explicit constraints and implicit coupling constraints are output.

[0121] In this embodiment, the iterative execution path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and the output design parameters that conform to all explicit constraints and implicit coupling constraints, can be achieved through the following steps:

[0122] At the beginning of each iteration, an adjustment path is selected based on the cumulative coupling effect value of each path containing hidden edges.

[0123] Along the selected adjustment path, the values ​​of each design variable on the path are finely adjusted in turn according to the preset step size. After each variable is adjusted, it is checked whether the variable is still within the value range corresponding to the explicit feasible domain. If it exceeds the range, the adjustment is rolled back and the step size is reduced.

[0124] After one round of adjustments, the coupling effect evaluation values ​​of all implicit edges are recalculated;

[0125] The iteration terminates when the preset requirements are met; otherwise, it proceeds to the next iteration.

[0126] After the iteration terminates, output the final values ​​of all current design variables.

[0127] It should be noted that the preset requirements in this application are comprehensive conditions used to control the termination of the iteration, including the first preset requirement and the second preset requirement; the final value is used to represent the value reached by each design variable when the iteration terminates, and this set of values ​​simultaneously satisfies all explicit constraints and implicit coupling constraints.

[0128] In practical application, firstly, an initial iteration round is set, with the first iteration as the starting point. At the beginning of each iteration, all paths containing implicit edges and their corresponding cumulative coupling effect values ​​are obtained. Based on these cumulative coupling effect values, an adjustment path is selected according to the aforementioned path selection rules. This adjustment path is the target path for variable adjustment in this iteration. Secondly, along the direction indicated by the selected adjustment path, fine-tuning operations are performed on each design variable on the path sequentially according to a preset step size. The preset step size can be set according to the physical meaning and typical adjustment range of each design variable. For example, the step size for the building orientation angle is set to 5 degrees. The window-to-wall ratio step is set to 0.02, the tree plane coordinate step is set to 0.5 meters, and the external shading dimension step is set to 0.1 meters. After each design variable is fine-tuned, it is immediately checked whether the new value of the variable is still within the value range corresponding to the explicit feasible region. If the new value is within the value range, the result of this fine-tuning is retained, and the next design variable on the path is fine-tuned. If the new value exceeds the value range, a rollback operation is performed to restore the value of the variable to the value before fine-tuning, and the preset step size of the variable is reduced to half of the original step size, but the reduced step size should not be less than the preset minimum step size. Then, the fine-tuning is retried using the reduced step size. If the value still exceeds the range after a retry, the step size is reduced and the test is repeated until the step size reaches the preset minimum step size. If the variable value still cannot fall into the explicit feasible region at the minimum step size, the adjustment of the variable is abandoned, its original value is kept unchanged, and the variable is recorded as having failed to adjust in this iteration. The number of retries for each variable in a single iteration does not exceed the preset maximum number of retries, which can be set to 3 times. After processing the current variable, the above operation is performed on the next design variable on the path.

[0129] Then, after fine-tuning and verifying all design variables on the current adjustment path, the adjustment process of this iteration ends. At this point, the coupling effect evaluation value of all implicit edges is recalculated. That is, based on the updated design variable values, the coupling effect evaluation rules associated with each implicit edge are called to calculate the new evaluation value of each implicit edge under the current value. Next, it should be noted that for the first iteration, since there is no cumulative coupling effect value from the previous iteration, only the first preset requirement is checked, that is, whether the coupling effect evaluation value of all implicit edges is lower than their respective thresholds. If the first preset requirement is met, the iteration is terminated; if not, the next iteration is directly entered without judging the second preset requirement. For the second iteration and subsequent iterations, the specific steps for judging whether the preset requirement is met are as follows: First, check whether the coupling effect evaluation value of all implicit edges is lower than their respective thresholds. If the threshold is met, the first preset requirement is satisfied, and the iteration terminates. If at least one hidden edge has a coupling effect evaluation value higher than or equal to its corresponding threshold, the second preset requirement is determined. For each hidden edge with an evaluation value higher than or equal to the threshold, if it belongs to multiple paths, the path with the largest cumulative coupling effect value is taken as its representative path. If it belongs to only one path, that path is the representative path. Then, it is determined whether the rate of change of the cumulative coupling effect value of all representative paths in two consecutive iterations is less than the preset convergence accuracy, and whether these hidden edges do not involve the west-facing window-to-wall ratio node. If so, the second preset requirement is satisfied, and the iteration terminates. Otherwise, the next iteration begins. If the preset requirement is satisfied, the iteration process terminates. If the preset requirement is not satisfied, the next iteration begins, and the entire process of path selection, value adjustment, verification, and recalculation of evaluation value is repeated.

[0130] Finally, after the iteration terminates, the values ​​of all current design variables are obtained. These values ​​have undergone multiple rounds of adjustment, satisfying the analytical expression constraints corresponding to all explicit edges, and ensuring that the coupling effect evaluation values ​​of each implicit edge reach the acceptable level specified by the preset requirements. Finally, the final values ​​of all current design variables are output as design parameters that meet all explicit and implicit coupling constraints. This output result is used to guide the design optimization of architectural landscape schemes, achieving the coordination and unity of energy-saving goals and functional requirements.

[0131] Preferably, in some embodiments, the preset requirements can be set using the following steps:

[0132] Configure a corresponding evaluation value threshold for each hidden edge;

[0133] When the current coupling effect evaluation value of all hidden edges is lower than their respective thresholds, it is determined that the first preset requirement is met;

[0134] Alternatively, when there is at least one hidden edge whose evaluation value is higher than its threshold, for each hidden edge that is higher than the threshold, if the hidden edge belongs to multiple paths, the path with the largest cumulative coupling effect value is taken as its representative path. When the rate of change of the cumulative coupling effect value of all representative paths in two consecutive iterations is less than the preset convergence accuracy, and all hidden edges that are higher than the threshold do not involve the west-facing window-to-wall ratio node, it is determined that the second preset requirement is met.

[0135] The preset requirement is determined to be met when either the first preset requirement or the second preset requirement is met.

[0136] It should be noted that for the first iteration, since there is no cumulative coupling effect value from the previous iteration, the second preset requirement is not applied; it only applies to iterations after the first iteration. It should also be noted that the evaluation threshold in this application is a boundary value used to determine whether the coupling effect evaluation value of a hidden edge is acceptable; each hidden edge can be configured with its own threshold. The first preset requirement is a termination condition indicating that the coupling effect evaluation values ​​of all hidden edges have reached an acceptable level. The second preset requirement is a termination condition indicating that although the coupling effect evaluation values ​​of some hidden edges have not reached an acceptable level, the iteration has entered a convergent state and no high-risk variables are involved. The preset requirement is used to uniformly represent the overall termination condition corresponding to the satisfaction of either the first or second preset requirement. The representative path is used to represent the path with the largest cumulative coupling effect value among multiple paths to which a hidden edge belongs; when multiple paths have the same maximum value, the one with the longest path length is selected.

[0137] In practical application, firstly, an independent evaluation threshold is configured for each implicit edge. The specific value of the evaluation threshold can be preset according to the type of design variable connected by the implicit edge and the climate zone of the project location. For example, for an implicit edge connecting the south-facing window-to-wall ratio and the external shading size, its evaluation threshold can be set to 0.2; for an implicit edge connecting the tree crown width and the south-facing window-to-wall ratio, its evaluation threshold can be set to 0.15. The thresholds for different implicit edges can be the same or different, and are determined by the designers based on engineering experience or simulation data.

[0138] Then, after the current iteration is completed, the coupling effect evaluation values ​​of all implicit edges are obtained. Each implicit edge's coupling effect evaluation value is compared with its corresponding evaluation threshold. If the coupling effect evaluation values ​​of all implicit edges are lower than their respective thresholds, the first preset requirement is met. If at least one implicit edge has a coupling effect evaluation value higher than or equal to its corresponding threshold, the second preset requirement is entered into the determination process. That is, all implicit edges with evaluation values ​​higher than or equal to the threshold are first identified. For each such implicit edge, its representative path is determined according to the aforementioned definition. That is, if the implicit edge belongs to multiple paths, the path with the largest cumulative coupling effect value is taken as its representative path; if it belongs to only one path, that path is the representative path. Next, obtain the cumulative coupling effect value of the representative path in the two most recent consecutive iterations, calculate the change in the cumulative coupling effect value in these two iterations divided by the cumulative coupling effect value in the previous iteration, and obtain the rate of change of the representative path. Determine whether the rate of change is less than the preset convergence accuracy. The preset convergence accuracy is a configurable positive number, for example, it can be set to 5%, and the specific value is determined according to the engineering requirements. At the same time, check whether all implicit edges with evaluation values ​​higher than or equal to the threshold do not involve the west-facing window-to-wall ratio node, that is, the two design variables connected by these implicit edges do not contain the west-facing window-to-wall ratio. If the rate of change of all representative paths is less than the preset convergence accuracy, and these implicit edges do not involve the west-facing window-to-wall ratio node, then it is determined that the second preset requirement is met.

[0139] Finally, if either the first preset requirement or the second preset requirement is met, the preset requirement is determined to be satisfied. This preset requirement is used to control the termination time of the iteration process; that is, once the preset requirement is met, the iteration stops, and the final values ​​of all current design variables are output.

[0140] On the other hand, in some embodiments, this application provides a design parameter generation system for architectural landscape schemes, with reference to Figure 3 The figure is a schematic diagram of a design parameter generation system for architectural landscape schemes according to some embodiments of this application. This system includes: an initial value generation module 301, an association graph construction module 302, a constraint transfer module 303, a path identification module 304, a path adjustment module 305, and an iteration control module 306, which are described below:

[0141] The initial value selection module 301 is used to determine the initial value range of each design variable;

[0142] The association graph construction module 302 is used to construct an association graph between various design variables. The nodes of the association graph represent design variables, and the edges represent the association relationships between design variables. Among them, deterministic associations with analytical expressions are called explicit edges, and associations without analytical expressions but requiring evaluation through coupling effect evaluation rules are called implicit edges.

[0143] The constraint transfer module 303 is used to transfer constraints along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges.

[0144] The path identification module 304 is used to identify all paths containing implicit edges within the explicit feasible region and calculate the cumulative coupling effect value on each path.

[0145] The path adjustment module 305 is used to select an adjustment path according to the cumulative coupling effect value, adjust the values ​​of each design variable along the adjustment path, and verify whether the adjusted values ​​satisfy the explicit feasible region.

[0146] The iterative control module 306 is used to iteratively perform path selection, value adjustment, and explicit feasible domain verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and output design parameters that conform to all explicit constraints and implicit coupling constraints.

[0147] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described method for generating design parameters for architectural landscape schemes.

[0148] In some embodiments, reference Figure 4 The figure is a schematic diagram of the structure of a computer device implementing a method for generating design parameters for architectural landscape schemes, according to some embodiments of this application. The method for generating design parameters for architectural landscape schemes in the above embodiments can be achieved through... Figure 4 The computer device shown is used to implement this, and the computer device 400 includes at least one processor 401, a communication bus 402, a memory 403, and at least one communication interface 404.

[0149] Processor 401 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0150] The communication bus 402 can be used to transmit information between the aforementioned components.

[0151] The memory 403 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 403 may exist independently and be connected to the processor 401 via the communication bus 402. The memory 403 may also be integrated with the processor 401.

[0152] The memory 403 stores program code for executing the scheme of this application, and its execution is controlled by the processor 401. The processor 401 executes the program code stored in the memory 403. The program code may include one or more software modules. The design parameter generation method for architectural landscape schemes in the above embodiments can be implemented by the processor 401 and one or more software modules in the program code in the memory 403.

[0153] Communication interface 404 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0154] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0155] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0156] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for generating design parameters for architectural landscape schemes.

[0157] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0158] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for generating design parameters for architectural landscape schemes, characterized in that, The method includes: Determine the initial value range for each design variable; Construct a relationship graph among the design variables. The nodes of the relationship graph represent design variables, and the edges represent the relationships between design variables. Deterministic relationships with analytical expressions are called explicit edges, and relationships without analytical expressions that need to be evaluated by coupling effect evaluation rules are called implicit edges. Constraints are propagated along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges; Within the explicit feasible region, identify all paths containing implicit edges and calculate the cumulative coupling effect value on each path; Based on the cumulative coupling effect value, select an adjustment path, adjust the values ​​of each design variable along the adjustment path, and verify whether the adjusted values ​​satisfy the explicit feasible region. Iteratively execute path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and output design parameters that comply with all explicit and implicit coupling constraints.

2. The method as described in claim 1, characterized in that, Determining the initial value range of each design variable specifically includes: Based on the type and level of the architectural landscape scheme and the climate zone of the project location, the minimum allowable value, maximum allowable value and default value of each design variable are preset; The design variables include at least the building orientation angle, south-facing window-to-wall ratio, west-facing window-to-wall ratio, external shading dimensions, tree planar coordinates, tree crown width, and water area; The initial range of the building orientation angle is preset based on the solar trajectory and prevailing wind direction of the project location, and the initial range of the south-facing window-to-wall ratio is wider than that of the west-facing window-to-wall ratio.

3. The method as described in claim 1, characterized in that, The coupling effect evaluation rules include: An evaluation function is configured for each implicit edge. The input of the evaluation function is the current value of the two design variables connected by the implicit edge, and the output is the coupling effect evaluation value that characterizes the degree of coupling conflict between the two. The evaluation function includes a lighting-heating conflict evaluation rule and a shading-lighting conflict evaluation rule; wherein, the lighting-heating conflict evaluation rule is used to evaluate the implicit conflict between the window-to-wall ratio and the external shading size under the same orientation, and the shading-lighting conflict evaluation rule is used to evaluate the implicit conflict between the tree crown width and the window-to-wall ratio under the same orientation.

4. The method as described in claim 1, characterized in that, The construction of the relationship diagram between the various design variables specifically includes: Treat each design variable as a node; For any two design variables, determine whether there is a geometric dependency, physical coupling relationship or functional constraint relationship between them; If the above relationship exists and has a closed analytic expression, then an explicit edge is established between the two corresponding nodes, and the forward and reverse propagation directions of the analytic expression are recorded. If the above relationship exists but does not have a closed analytic expression, then an implicit edge is established between the two corresponding nodes, and the corresponding coupling effect evaluation rule is associated with the implicit edge. Among them, the explicit edges between the window-to-wall ratio node and the external shading size node of each orientation belonging to the same building facade orientation are divided into the same explicit edge group, and the explicit edge groups corresponding to different facade orientations are independent of each other. Based on the nodes, explicit edges, and implicit edges, construct the relationship graph between the design variables.

5. The method as described in claim 1, characterized in that, The step of performing constraint propagation along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges specifically includes: Starting from the independent variable node with no explicit input, calculate the value range of the dependent variable node in sequence according to the direction of the explicit edge; When a dependent variable node has multiple explicit edge inputs, take the intersection of the intervals derived from each input; For explicit edge groups of window-to-wall ratios and external shading dimensions of different orientations within the same building facade, synchronous constraint transfer is performed to ensure geometric self-consistency. The Cartesian product of the value intervals of all nodes constitutes the explicit feasible region.

6. The method as described in claim 1, characterized in that, Within the explicit feasible region, identifying all paths containing implicit edges and calculating the cumulative coupling effect value on each path specifically includes: In the association graph subgraph corresponding to the explicit feasible region, each node containing a hidden edge is taken as the starting node, and all reachable nodes are traversed along the direction of the association edge to search for a sequence of nodes that are alternately connected by nodes and edges and contain at least one hidden edge. Each of the sequences is identified as a path containing hidden edges; For each identified path, obtain the coupling effect evaluation value corresponding to each of the hidden edges on the path, and sum the coupling effect evaluation values ​​to obtain the cumulative coupling effect value of the path.

7. The method as described in claim 1, characterized in that, The step of selecting an adjustment path based on the cumulative coupling effect value, adjusting the values ​​of each design variable along the adjustment path, and verifying whether the adjusted values ​​satisfy the explicit feasible region specifically includes: Calculate the ratio of the cumulative coupling effect value of each path containing implicit edges to the preset adjustment cost, and select the path with the smallest ratio as the current adjustment path. The preset adjustment cost is preset according to the type of design variables on the path, and the adjustment cost of building orientation is higher than the adjustment cost of tree plane coordinates. Along the direction of the adjustment path, the values ​​of each design variable on the path are finely adjusted sequentially according to a preset step size; After each variable adjustment is completed, it is checked whether the variable is still within the value range corresponding to the explicit feasible region. If it exceeds the range, the adjustment is rolled back and the step size is reduced.

8. The method as described in claim 1, characterized in that, The iterative execution path selection, value adjustment, and explicit feasible region verification continue until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements. The output then includes design parameters that conform to all explicit and implicit coupling constraints, specifically: At the beginning of each iteration, an adjustment path is selected based on the cumulative coupling effect value of each path containing hidden edges. Along the selected adjustment path, the values ​​of each design variable on the path are finely adjusted in turn according to the preset step size. After each variable is adjusted, it is checked whether the variable is still within the value range corresponding to the explicit feasible domain. If it exceeds the range, the adjustment is rolled back and the step size is reduced. After one round of adjustments, the coupling effect evaluation values ​​of all implicit edges are recalculated; The iteration terminates when the preset requirements are met; otherwise, it proceeds to the next iteration. After the iteration terminates, output the final values ​​of all current design variables.

9. The method as described in claim 1, characterized in that, The preset requirements specifically include: Configure a corresponding evaluation value threshold for each hidden edge; When the current coupling effect evaluation value of all hidden edges is lower than their respective thresholds, it is determined that the first preset requirement is met; Alternatively, when there is at least one hidden edge whose evaluation value is higher than its threshold, for each hidden edge that is higher than the threshold, if the hidden edge belongs to multiple paths, the path with the largest cumulative coupling effect value is taken as its representative path. When the rate of change of the cumulative coupling effect value of all representative paths in two consecutive iterations is less than the preset convergence accuracy, and all hidden edges that are higher than the threshold do not involve the west-facing window-to-wall ratio node, it is determined that the second preset requirement is met. The preset requirement is determined to be met when either the first preset requirement or the second preset requirement is met.

10. A design parameter generation system for architectural landscape schemes, characterized in that, include: The initial value selection module is used to determine the initial value range of each design variable; The association graph construction module is used to construct the association graph between various design variables. The nodes of the association graph represent design variables, and the edges represent the association relationships between design variables. Among them, deterministic associations with analytical expressions are called explicit edges, and associations without analytical expressions but requiring evaluation through coupling effect evaluation rules are called implicit edges. A constraint propagation module is used to propagate constraints along the explicit edges to determine the explicit feasible region jointly defined by all explicit edges. The path identification module is used to identify all paths containing implicit edges within the explicit feasible region and calculate the cumulative coupling effect value on each path. The path adjustment module is used to select an adjustment path based on the cumulative coupling effect value, adjust the values ​​of each design variable along the adjustment path, and verify whether the adjusted values ​​satisfy the explicit feasible region. The iterative control module is used to iteratively perform path selection, value adjustment, and explicit feasible region verification until the coupling effect evaluation values ​​of all implicit edges meet the preset requirements, and output design parameters that comply with all explicit and implicit coupling constraints.

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