A landscape architecture computer-aided design method and system

Abstract

This application relates to the field of landscape design technology, and particularly to a computer-aided design method and system for landscape architecture. The method includes: obtaining basic site parameters of the landscape to be planned to provide data support for subsequent planning calculations; calculating multiple capacity allocation schemes based on the number of landscape modules and carrying capacity; generating multiple fully connected schemes by combining the preset number of functional areas, thereby systematically optimizing the spatial accessibility and ecological flow relationships between functional areas; systematically optimizing the fully connected schemes to achieve a global improvement from structural rationality to functional matching; and optimizing the optimal auxiliary design scheme to improve the coordination, scientific nature, and feasibility of the scheme, thus completing the transformation of landscape architecture design from experience-driven to data-driven, reducing manual comparison and repetitive calculations, improving design efficiency and output quality, and promoting the intelligent and ecological development of landscape planning.

Description

Technical Field

[0001] This application belongs to the field of landscape design technology, and in particular relates to a computer-aided design method and system for landscape architecture. Background Technology

[0002] Landscape architecture design is a highly comprehensive applied discipline, mainly involving multiple aspects such as natural ecology, spatial art, engineering technology, and human environment. Its core objective is to achieve the organic integration of the natural and artificial environments through spatial organization, landscape configuration, and environmental coordination, while meeting ecological functions and usage needs. In practical applications, landscape architecture design not only needs to consider the aesthetic expression of the landscape but also needs to take into account multiple factors such as the site's topographical features, hydrological conditions, plant ecological relationships, and pedestrian flow organization, in order to construct landscape spaces that are aesthetically pleasing, functional, and sustainable.

[0003] Traditional landscape architecture design typically relies heavily on manual drawing and experience-based judgment. Designers depend on their professional knowledge and aesthetic experience to divide the site into functional zones, arrange spaces, and configure plants. However, as landscape projects expand in scale and increase in functional complexity, this experience-based design model has gradually revealed numerous problems. Design decisions often require multiple rounds of manual comparison and revision, a time-consuming and inefficient process. Furthermore, due to a lack of dynamic calculations and data support, traditional design struggles to predict and assess the feasibility and sustainability of solutions in the early stages, leading to issues such as low space utilization or ecological damage after implementation. Although modern landscape architecture design is gradually transforming towards digitalization and intelligence, many design support systems in current applications remain at the level of geometric modeling and visualization, failing to fully support the intelligent and systematic needs of modern landscape architecture design. Summary of the Invention

[0004] This application provides a computer-aided design method and system for landscape architecture, which can solve the problem that existing landscape architecture design assistance systems are still limited to geometric modeling and visualization, and cannot fully support the intelligent and systematic needs of modern landscape architecture design.

[0005] In a first aspect, embodiments of this application provide a computer-aided design method for landscape architecture, including:

[0006] Obtain the basic parameters of the site for the landscape garden to be planned; wherein, the basic parameters of the site include the number of landscape modules, the bearing capacity of the landscape modules, and the number of preset functional areas;

[0007] Based on the number of landscape modules and the carrying capacity of the landscape modules, calculate multiple capacity allocation schemes corresponding to the landscape garden to be planned.

[0008] Based on the number of preset functional areas and the various capacity allocation schemes corresponding to the landscape garden to be planned, multiple sets of fully connected schemes for the landscape garden to be planned are obtained.

[0009] The complete connectivity schemes in each group are systematically optimized to obtain the candidate planning schemes corresponding to each group of complete connectivity schemes;

[0010] The optimal auxiliary design scheme is selected from all the candidate planning schemes.

[0011] The technical solutions described in this application embodiment have at least the following technical effects:

[0012] The computer-aided landscape design method provided in this application, by acquiring the basic parameters of the site of the landscape to be planned, can comprehensively grasp the basic topographic features and spatial capacity of the planning area, providing accurate data support for subsequent planning calculations. Capacity allocation calculations based on the number and carrying capacity of landscape modules can achieve a scientific balance of resource load among different landscape modules in the early stages, avoiding the problems of uneven space utilization and functional overlap caused by manual judgment in traditional design. By combining the number of preset functional areas and multiple capacity allocation schemes, multiple fully connected schemes are formed, enabling systematic simulation and optimization of spatial accessibility and ecological flow relationships between functional areas, effectively improving the coordination and integrity of the overall plan. In the process of systematically optimizing each fully connected scheme, a global improvement from structural rationality to functional matching can be achieved. The optimized candidate planning schemes have higher scientific validity and feasibility, reducing the number of iterations and improving the efficiency and accuracy of design decisions. The optimal auxiliary design scheme, selected from all candidate schemes, not only achieves automated generation and intelligent screening of landscape planning results, but also significantly improves the system coordination and ecological adaptability of the scheme. By using computer-aided algorithms to analyze and optimize complex spatial relationships, it reduces manual comparison and repeated trial calculations, improves planning efficiency and result quality, and provides technical support for the ecological, intelligent and sustainable development of landscape architecture.

[0013] Secondly, embodiments of this application provide a computer-aided design system for landscape architecture, comprising:

[0014] The acquisition unit is used to acquire the basic parameters of the site of the landscape garden to be planned; wherein, the basic parameters of the site include the number of landscape modules, the bearing capacity of the landscape modules, and the number of preset functional areas;

[0015] The calculation unit is used to calculate multiple capacity allocation schemes corresponding to the landscape garden to be planned based on the number of landscape modules and the carrying capacity of the landscape modules;

[0016] The connectivity unit is used to obtain multiple fully connected schemes for the landscape garden to be planned based on the number of preset functional areas and the various capacity allocation schemes corresponding to the landscape garden to be planned.

[0017] An optimization unit is used to systematically optimize each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes.

[0018] The result unit is used to select the optimal auxiliary design scheme from all the candidate planning schemes.

[0019] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any of the first aspects above.

[0020] Fourthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any of the above aspects.

[0021] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the above aspects, and will not be repeated here. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a computer-aided landscape design method according to an embodiment of this application;

[0024] Figure 2 This is a partial schematic diagram illustrating the principle of a computer-aided landscape design method provided in one embodiment of this application;

[0025] Figure 3 This is a partial schematic diagram illustrating the principle of a computer-aided landscape design method provided in one embodiment of this application;

[0026] Figure 4 This is a partial schematic diagram illustrating the principle of a computer-aided landscape design method provided in one embodiment of this application;

[0027] Figure 5 This is a schematic diagram of the structure of a computer-aided landscape design system provided in one embodiment of this application;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0030] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0031] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0032] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determination" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determination," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0033] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0034] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0035] Traditional landscape architecture design typically relies heavily on manual drawing and experience-based judgment. Designers depend on their professional knowledge and aesthetic experience to divide the site into functional zones, arrange spaces, and configure plants. However, as landscape projects expand in scale and increase in functional complexity, this experience-based design model has gradually revealed numerous problems. Design decisions often require multiple rounds of manual comparison and revision, a time-consuming and inefficient process. Furthermore, due to a lack of dynamic calculations and data support, traditional design struggles to predict and assess the feasibility and sustainability of solutions in the early stages, leading to issues such as low space utilization or ecological damage after implementation. Although modern landscape architecture design is gradually transforming towards digitalization and intelligence, many design support systems in current applications remain at the level of geometric modeling and visualization, failing to fully support the intelligent and systematic needs of modern landscape architecture design.

[0036] To address the aforementioned issues, this application provides a computer-aided design method and system for landscape architecture. This method, by acquiring the basic site parameters of the landscape to be planned, comprehensively grasps the basic topographic features and spatial capacity of the planning area, providing accurate data support for subsequent planning calculations. Capacity allocation calculations based on the number and carrying capacity of landscape modules enable a scientific balance of resource load among different landscape modules in the early stages, avoiding the problems of uneven space utilization and functional overlap caused by manual judgment in traditional design. By combining the preset number of functional areas with multiple capacity allocation schemes, multiple fully connected schemes are formed, allowing for the systematic simulation and optimization of spatial accessibility and ecological flow relationships between functional areas, effectively improving the coordination and integrity of the overall planning. The systematic optimization of each fully connected scheme achieves a global improvement from structural rationality to functional matching. The optimized candidate planning schemes possess higher scientific validity and feasibility, reducing the number of iterations and improving the efficiency and accuracy of design decisions. The optimal auxiliary design scheme, selected from all candidate schemes, not only achieves automated generation and intelligent screening of landscape planning results, but also significantly improves the system coordination and ecological adaptability of the scheme. By using computer-aided algorithms to analyze and optimize complex spatial relationships, it reduces manual comparison and repeated trial calculations, improves planning efficiency and result quality, and provides technical support for the ecological, intelligent and sustainable development of landscape architecture.

[0037] The landscape architecture computer-aided design method provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the executing subject of the landscape architecture computer-aided design method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0038] For example, the electronic device can be various types of intelligent monitoring devices. This electronic device may include, but is not limited to, desktop computers, smart screens, smart TVs, handheld devices with wireless communication capabilities, computing devices, computers, laptops, etc.

[0039] To better understand the computer-aided landscape design method provided in the embodiments of this application, the specific implementation process of the computer-aided landscape design method provided in the embodiments of this application will be described by way of example below.

[0040] Figure 1 This illustration shows a schematic flowchart of a computer-aided landscape design method provided in an embodiment of this application. The computer-aided landscape design method includes:

[0041] S100, obtain the basic parameters of the site for the landscape garden to be planned; among which, the basic parameters of the site include the number of landscape modules, the bearing capacity of the landscape modules, and the number of preset functional areas.

[0042] It can be understood that basic site parameters refer to the quantitative information set describing the physical, ecological, and functional characteristics of a site, obtained by landscape architecture professionals before planning and design. Basic site parameters can include core indicators such as the number of landscape modules, the carrying capacity of landscape modules, and the number of pre-designed functional zones. The number of landscape modules describes the total number of spatial units within the site that can be independently planned or developed, and is the basic unit for functional zoning and capacity configuration. The carrying capacity of a landscape module represents the maximum capacity that a single landscape module can withstand in terms of structural safety, ecological load, and pedestrian density, and is an important physical parameter determining the scale of functional zoning. The number of pre-designed functional zones is used to define the spatial functional objectives during the design phase, such as recreational areas, activity areas, water features, and ecological conservation areas. When acquiring basic site parameters, remote sensing imagery, topographic mapping data, and geological survey results can be used. 3D geographic information modeling tools (such as ArcGIS or Rhino) can be used to automatically extract the spatial boundaries and structural attributes of modules, and manually uploaded ecological constraint indicators can be used for parameter normalization. The establishment of basic parameters for the site can form a structured spatial data framework, providing a unified data benchmark for subsequent capacity allocation calculations, connectivity construction, and planning optimization. This enables precise quantification of the site's objective conditions and provides scientific data input and reliable constraints for the overall planning of the landscape architecture.

[0043] S200 calculates various capacity allocation schemes for the landscape garden to be planned, based on the number of landscape modules and their carrying capacity.

[0044] A capacity allocation scheme, as understood, refers to a combination of functional area capacity configurations in a landscape garden calculated based on the number and carrying capacity of landscape modules. It determines the spatial proportion and carrying capacity distribution among different functional areas. The "capacity" in the capacity allocation scheme represents the comprehensive carrying capacity of a functional area under multiple dimensions, including area, ecological load, and activity density. The generation of a capacity allocation scheme relies on the principle of capacity balance, meaning the total capacity of all functional areas cannot exceed the total carrying capacity of the landscape modules. Capacity constraint equations can be established based on the number and carrying capacity of landscape modules, and mathematical optimization algorithms (including linear programming, integer programming, or heuristic algorithms) can be used to generate multiple capacity allocation results that satisfy the constraints. Each capacity allocation result is recorded as an independent scheme, used to describe the functional area distribution pattern of the landscape garden under different planning strategies. The generation of capacity allocation schemes not only improves the efficiency of spatial resource utilization but also provides a diverse reference basis for subsequent connectivity structure construction and path layout optimization, ensuring a dynamic balance between ecological carrying capacity and human use in each functional area of ​​the landscape garden, and achieving the rationality, adaptability, and long-term sustainability of landscape space functions.

[0045] In one possible implementation, S200 calculates multiple capacity allocation schemes for the landscape garden to be planned, based on the number of landscape modules and their carrying capacity, including:

[0046] S210, based on the number of landscape modules and the carrying capacity of the landscape modules, determine the capacity allocation constraints and the capacity allocation range of each preset functional area; wherein, the constraints include that the total capacity of all preset functional areas does not exceed the total carrying capacity of the landscape modules, and the capacity of each preset functional area is within its corresponding capacity allocation range; the lower limit of the capacity of a single preset functional area is the carrying capacity of a single landscape module, and the upper limit of the capacity is the total carrying capacity of the landscape modules, and the total carrying capacity of the landscape modules is the product of the number of landscape modules and the carrying capacity of a single landscape module.

[0047] It can be understood that capacity allocation constraints refer to the set of mathematical constraints that limit the scope of capacity calculation and allocation ratio in the process of capacity allocation in landscape architecture. Capacity allocation constraints consist of the total capacity limit of functional areas and the boundary conditions of individual functional areas. Please refer to [link / reference]. Figure 2 The summation constraint in the capacity allocation conditions is used to ensure that the sum of the capacities of all preset functional areas does not exceed the total bearing capacity of the landscape module. Its calculation formula is as follows: ,in, Indicates the first The capacity of each preset function area Indicates the number of landscape modules. This represents the carrying capacity of a single landscape module. The total carrying capacity of a landscape module is the sum of the carrying capacities of all landscape modules. Capacity boundary conditions are used to limit the upper and lower limits of the capacity of each functional area, ensuring that the lower limit of the capacity of each functional area is not lower than the carrying capacity of a single landscape module, and the upper limit of the capacity does not exceed the total carrying capacity of the landscape modules. A capacity constraint matrix can be established based on the site's foundation parameters, and all capacity combinations that meet the conditions can be calculated using a multi-objective constraint solving algorithm. This ensures the spatial proportion coordination and structural stability during the capacity allocation process, preventing resource overload or space waste in functional areas. By executing the definition and calculation of capacity allocation constraints, the landscape architecture capacity configuration results can achieve the optimal distribution of functional area capacity while ensuring overall carrying capacity balance, providing a quantitative and verifiable theoretical basis for planning and design.

[0048] S220 generates multiple capacity allocation schemes for the planned landscape gardens that meet the constraints, based on the constraints and the capacity allocation range of each preset functional area.

[0049] Multiple capacity allocation schemes refer to a set of different capacity configuration results generated by a capacity allocation algorithm under the premise of satisfying capacity allocation constraints. These schemes express the spatial allocation patterns of landscape architecture under different design intentions. Each set of capacity allocation schemes represents an independent set of capacity allocation results, including the capacity parameters and spatial proportions of each preset functional area. The feasible solution space can be determined based on the capacity constraints, and then multiple sets of capacity combinations that meet the conditions can be generated in the solution space using random sampling search, genetic optimization algorithms, or simulated annealing algorithms. After normalization, each combination forms a capacity allocation scheme with a complete parameter structure. The generation of multiple schemes enables multi-objective design options in the planning stage, allowing designers to conduct trade-off analyses under different objectives such as functional priority, ecological balance, or aesthetic orientation. This facilitates diversified exploration and scientific decision-making in scheme space, providing a rich data input foundation for subsequent connectivity calculations, path optimization, and layout generation, ultimately enhancing the intelligence and scalability of landscape architecture planning.

[0050] S300, based on the preset number of functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned, obtains multiple sets of fully connected schemes for the landscape garden to be planned.

[0051] It can be understood that multiple sets of fully connected schemes refer to a set of landscape layout models with complete spatial accessibility and logical coherence, formed based on the existing landscape capacity allocation scheme and through the design of passageways connecting functional areas. Fully connected schemes ensure that there is at least one physical or functionally accessible path between all pre-defined functional areas, meeting the systematic requirements of the garden in terms of traffic organization, ecological circulation, and landscape coherence. This can be achieved by reading the functional area capacity parameters and spatial location constraints from each capacity allocation scheme, and then calculating the possible number and types of passageways between functional areas according to the principle of full connectivity. By calculating the number of passageways for each capacity allocation scheme, multiple sets of spatial layout models with complete connectivity relationships are established. Model construction can be achieved through spatial accessibility matrices, topological connectivity analysis, and path redundancy detection algorithms, thereby ensuring that traffic flow, ecological flow, and pedestrian flow paths between any two functional areas have traversability and redundancy, forming a diverse set of schemes that conform to spatial logic, capacity constraints, and ecological circulation principles. This provides a foundation for subsequent systematic optimization and candidate scheme selection, ensuring the overall coordination and stability of landscape planning at both spatial and functional levels.

[0052] In one possible implementation, S300, based on the preset number of functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned, obtains multiple sets of fully connected schemes for the landscape garden to be planned, including:

[0053] S310, based on the number of preset functional areas and the capacity allocation scheme corresponding to each capacity allocation scheme of the landscape garden to be planned, calculate the number of connection channels corresponding to each capacity allocation scheme.

[0054] It is understood that the number of connecting passages refers to the number of passages within the planned landscape garden. Please refer to [link / reference needed]. Figure 3 This refers to the number of passageways required to achieve complete connectivity in terms of traffic, sightlines, ecology, and function between pre-defined functional areas. Connecting passageways serve as bridges for interaction, pedestrian flow, and ecological energy exchange between functional areas within the landscape architecture's spatial structure. The number of pre-defined functional areas refers to the total number of functional zones pre-defined during the planning and design phase based on usage needs, landscape functions, and spatial distribution, such as rest areas, exhibition areas, water features, vegetation areas, and management areas. Each capacity allocation scheme represents a combination of functional area capacities formed under the constraint of the total carrying capacity of the landscape modules, including data on the space, number of people, and ecological load that each functional area can accommodate. A functional area pair matrix can be established based on the number of pre-defined functional areas. Each element of the matrix corresponds to whether a direct connection is needed between two functional areas. The connection strength between functional area pairs is calculated using capacity allocation scheme data, and the existence of connecting passageways is determined based on the strength threshold. If the functional areas have high interdependence, dense traffic demand, or high mobility of ecological elements, connecting passageways are set between the corresponding functional area pairs. This calculation process can yield the number of connecting passages in the landscape garden under various capacity allocation schemes, enabling a quantitative description of the complexity of the garden's spatial network. It reflects the potential advantages and disadvantages of the planning scheme in terms of traffic convenience, ecological continuity, and spatial coordination, thus providing a basis for optimizing the overall layout of the garden.

[0055] Optionally, S310, based on the preset number of functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned, calculate the number of connection channels corresponding to each capacity allocation scheme, including:

[0056] S311, determine the number of fully connected basic channels based on the number of preset functional areas; the number of basic channels is the product of the number of preset functional areas multiplied by the number of preset functional areas minus one, and then the product is divided by two.

[0057] It can be understood that the number of basic, fully connected pathways refers to the minimum number of pathways that must be set up in landscape architecture planning to ensure the most basic spatial connectivity between all pre-designed functional areas. The calculation of the number of basic, fully connected pathways is based on combinatorial mathematics principles. Each functional area needs to maintain at least one pathway connection with all other functional areas except itself. Therefore, with n pre-designed functional areas, the number of basic pathways is calculated using the formula: B = n(n−1) / 2. In the formula, n represents the number of functional areas, and the result B represents the total number of pathways required to maintain full connectivity of the system under non-redundant conditions. This ensures that there is at least one direct pathway between any two functional areas, realizing the minimum connectivity framework of the landscape architecture spatial system. This guarantees that the spatial network of the landscape architecture is logically connected and structurally simple, providing a scalable infrastructure for subsequent capacity balancing and ecological path planning.

[0058] S312, calculate the total capacity of any two preset functional areas based on each capacity allocation scheme corresponding to the landscape garden to be planned.

[0059] It can be understood that the sum of the capacities of any two pre-defined functional zones refers to the comprehensive capacity value obtained by arithmetically adding the capacity parameters of two different functional zones under a specific capacity allocation scheme. This total capacity is used to assess the load relationship and interaction intensity between functional zones and serves as the data basis for determining whether to increase the number of passageways. When calculating the total capacity, the capacity value of each functional zone can be extracted from the capacity allocation scheme. This capacity value represents the number of people, facilities, or ecological carrying capacity that the functional zone can accommodate. A double-loop algorithm can be used to traverse all combinations of pre-defined functional zones, calculate the sum of the capacities of any two functional zones, and store the results in a capacity relationship matrix. The value of each cell in the matrix corresponds to the comprehensive capacity level of a pair of functional zones. The calculation of the total capacity not only has quantitative significance but also reflects the potential traffic pressure and population distribution trends of the spatial system. For example, when two high-capacity functional zones are adjacent, the passageways connecting them often require higher carrying capacity or more backup routes to prevent traffic or ecological bottlenecks. By calculating the total capacity, the load matching degree between functional areas can be quantified, providing an accurate data basis for the rational configuration of the number of channels and the judgment of channel carrying capacity thresholds, thereby achieving the balance of spatial functions and the guarantee of structural safety at the macro planning level.

[0060] S313, calculate the number of connection channels corresponding to each capacity allocation scheme based on the total capacity.

[0061] The process of calculating the number of connecting passages based on the total capacity is understandable. It combines the capacity relationship of functional areas with the carrying capacity characteristics of the passage system to determine the actual number of passages required for landscape architecture under various capacity allocation schemes. The total capacity of any two functional areas can be compared with the carrying capacity threshold of the corresponding passage to determine if there is any capacity over-limitation. The carrying capacity threshold is a quantitative parameter determined by a combination of passage design standards, traffic flow simulation, and structural stability analysis, used to limit the maximum bearable capacity of a single passage. A capacity ratio model can be constructed. ,in This represents the total capacity of the two functional areas. This represents the channel carrying capacity threshold. If the ratio... This indicates that the existing basic channels are sufficient to support the combination of functional areas; if the ratio In such cases, additional channels need to be added based on the excess capacity to distribute the flow. The capacity ratio model ensures that the landscape garden space network maintains structural stability and smooth flow even under high-intensity use in multi-functional areas, forming a channel configuration mechanism corresponding to the capacity allocation scheme. This ensures that the connectivity of the landscape garden space conforms to both logical integrity and meets the design requirements of structural safety and pedestrian flow balance.

[0062] For example, S313, calculating the number of connection channels corresponding to each capacity allocation scheme based on the total capacity includes:

[0063] S3131, obtain the carrying threshold for each connection channel; the carrying threshold is the maximum limit of the sum of the capacities of the two preset functional areas that a single channel can adapt to.

[0064] It is understandable that the carrying capacity threshold is a parameter used in landscape architecture spatial structure planning to measure the maximum capacity that a single connecting passage can support under normal operating conditions. The carrying capacity threshold not only includes load limitations at the physical structural level but also comprehensively considers factors such as traffic density, ecological connectivity, landscape circulation, and safe evacuation capacity within functional areas. The carrying capacity threshold of a single connecting passage is defined as the maximum limit of the sum of the capacities of the two pre-set functional areas that the passage can accommodate, representing the maximum flow of people, goods, and ecological energy that the passage can support without affecting the normal operation of the functional areas. The process of determining the carrying capacity threshold typically includes three stages: first, the structural parameter evaluation stage, which determines its physical carrying capacity through quantitative analysis of the passage's length, width, structural type, and material strength; second, the functional load evaluation stage, which calculates the total functional demand per unit time based on the capacity data, usage frequency, and traffic patterns of the two pre-set functional areas; and third, the safety factor correction stage, which can combine landscape safety design standards and risk assessment models (such as the structural reliability model based on ISO 2394) to reduce the initial carrying capacity, forming the final carrying capacity calculation result. The load-bearing threshold can be automatically calculated using parametric modeling software, or calibrated by designers manually uploading structural test data. By accurately obtaining the load-bearing threshold of each connecting passage, overload operation can be effectively avoided during capacity allocation and spatial layout stages, thereby improving the overall safety, traffic efficiency, and ecological connectivity of the landscape architecture spatial system. This provides a reliable quantitative basis for subsequent optimization of the number of passages and generation of connectivity schemes.

[0065] S3132, based on the sum of the capacities of any two preset functional areas in each capacity allocation scheme, determine whether the total capacity exceeds the carrying capacity threshold.

[0066] Determining whether the total capacity exceeds the carrying capacity threshold is a crucial step in landscape architecture spatial connectivity calculations. It determines whether the existing connection channel design between two pre-defined functional areas meets the requirements for matching capacity and safety. The total capacity refers to the sum of the capacity values ​​of any two pre-defined functional areas under a specific capacity allocation scheme, reflecting the potential interaction intensity and resource flow demands between the two functional areas. The carrying capacity threshold is the maximum capacity that a single connection channel can support, reflecting the safe range allowed by the channel structure, material strength, traffic organization, and ecological flow. The total capacity is compared with the carrying capacity threshold of the corresponding connection channel. When the total capacity is less than or equal to the carrying capacity threshold, it indicates that the channel design can meet the flow and ecological carrying capacity requirements of the functional area, and is considered safe and feasible. When the total capacity exceeds the carrying capacity threshold, it is marked as overloaded, requiring subsequent adjustments to the number of channels or layout optimization. It can be implemented using automated algorithms, and batch calculations can be performed through logical judgment statements or constraint verification modules to establish a logical mapping relationship between capacity allocation schemes and spatial channel structures. This ensures that the connection design between various functional areas of the landscape garden not only meets functional requirements but also maintains stability and security during long-term operation, thereby laying a reliable constraint foundation for the subsequent generation of fully connected schemes.

[0067] S3133, if the total capacity does not exceed the carrying threshold, the number of connection channels between the preset functional areas remains at 1 corresponding to the number of basic channels.

[0068] It is understandable that when the total capacity does not exceed the carrying capacity threshold, maintaining a basic passage between functional areas is sufficient to meet spatial connectivity requirements. A basic passage refers to a single route established to ensure basic accessibility between functional areas without causing capacity overload. Under this condition, the landscape architecture planning system will not add additional passages but will incorporate the basic passage into the overall connectivity network structure. In the calculation, the case where R=Csum / T≤1 is determined using a capacity ratio model, where... This represents the total capacity of the two functional areas. This indicates the carrying capacity threshold of the passageway, and the number of connections for this functional area combination is fixed at 1. This achieves compliance with the principles of spatial economy and structural simplicity, avoiding increased construction costs and waste of ecological space caused by redundant passageways. The configuration of basic passageways is usually determined by the relative location of functional areas and landscape hierarchy to balance visual continuity and ease of access, thereby optimizing the structure of the landscape garden spatial network. This ensures that the connectivity of each functional area meets load balancing standards while maintaining overall layout harmony, thus enhancing the spatial logic and ecological coordination of the planning scheme.

[0069] S3134, If the total capacity exceeds the carrying threshold, determine the number of additional channels between preset functional areas based on the total capacity carrying threshold.

[0070] It is understandable that when the total capacity exceeds the carrying capacity threshold, the landscape architecture planning system needs to add additional passageways based on the degree of capacity overrun to distribute the pressure on pedestrian flow and ecological load. The determination of the number of additional passageways is based on the capacity overrun ratio. By calculating the ratio of the total capacity to the carrying capacity threshold, the excess multiple is obtained, thereby estimating the required number of new passageways. An integer-based processing method can be used to ensure that the number of passageways is a feasible discrete value. The specific formula is as follows:

[0071]

[0072] in This indicates that the number exceeds a multiple. If This refers to the addition of functions between the preset functional areas. The addition of additional passageways not only reflects the concept of load balancing control but also embodies the flexible design philosophy of landscape architecture. Through a capacity threshold-driven passageway addition mechanism, circulation efficiency and structural safety are maintained in high-density functional areas. The added passageways are optimized in distribution during the layout generation phase to avoid spatial congestion or ecological disturbance, enhancing the adaptability of the landscape architecture spatial system and ensuring that the planning scheme maintains a high level of spatial connectivity and safety redundancy even under different capacity distribution scenarios.

[0073] For example, in S3134, if the total capacity exceeds the carrying threshold, the number of additional channels between preset functional areas is determined based on the total capacity carrying threshold, including:

[0074] S31341, If ​​the total capacity exceeds the carrying capacity threshold, calculate the ratio of the total capacity to the carrying capacity threshold, and perform integer processing on the ratio to obtain the excess multiple.

[0075] It's understandable that calculating the ratio of the total capacity to the carrying capacity threshold is the core step in determining channel additions. This ratio reflects the relative relationship between the load pressure and channel capacity between two functional areas. After the ratio calculation, it needs to be integerized to obtain the multiple required for exceeding the limit. Integerization is to ensure that the theoretical result can be adopted in actual construction. All functional area combinations can be iterated over, and the total capacity for each group can be calculated... and corresponding carrying threshold Calculate the ratio .like This indicates that the channel load is exceeded. The comparison value is rounded down to obtain the excess multiple. This multiple indicates the order of magnitude of the need to increase the number of passageways, ensuring traffic safety and functional continuity in high-load areas of the landscape garden, and providing technical support for dynamic expansion design.

[0076] S31342, determine the number of additional channels between preset functional areas based on the multiple.

[0077] It is understandable that determining the number of additional passageways involves mapping the excess multiple to the actual number of passageways that can be constructed, in order to compensate for the load imbalance caused by exceeding capacity limits. The calculated excess multiple K can be converted into the number of new passageways N=K−1, and the passageways are arranged according to the spatial relationship and directional constraints between functional areas. Additional passageways are typically staggered on either side of or above / below the existing basic passageways to distribute traffic density and pedestrian flow fluctuations. The reasonable determination of the number of additional passageways enables the landscape garden spatial system to possess dynamic adaptability and stability when capacity allocation changes. The effect of implementing this step is to maintain coordination between spatial connectivity and capacity distribution through quantitative control methods, significantly improving the overall spatial resilience and operational safety of the garden.

[0078] S3135, count the number of basic channels and the number of additional channels between all preset functional area pairs for each capacity allocation scheme, and obtain the number of connection channels corresponding to the capacity allocation scheme.

[0079] The process of calculating the number of basic and additional access routes involves integrating the access route configuration results of all functional area pairs to form a complete table of access route quantities. By iterating through the data records of each functional area pair in the capacity relationship matrix and summing the number of basic and additional access routes, the total number of routes for each capacity allocation scheme can be obtained. Based on the route quantity results, a route distribution map is generated, displaying the connectivity and traffic density of each functional area. Spatial location mapping and connection relationship reconstruction are performed based on the route quantity, thereby achieving the coherence of the overall landscape architecture structure and the balanced coordination of functional areas.

[0080] S320 generates a layout based on the number of connection channels corresponding to each capacity allocation scheme, resulting in a fully connected scheme for each capacity allocation scheme of the landscape garden to be planned.

[0081] Layout generation, as understood, refers to the process of constructing functional areas and passageways within a pre-defined spatial layout framework after determining the number of connecting channels for each capacity allocation scheme, thereby forming a fully connected layout scheme with spatial integrity and logical accessibility. The core objective of layout generation is to comprehensively map capacity, connectivity, and spatial relationships to achieve a rational spatial configuration of functional areas. Based on the number of connecting channels corresponding to each capacity allocation scheme, the spatial distance, azimuth, and connection relationships of each functional area can be determined. Subsequently, functional area nodes and passageway edges are constructed in a graph structure within the 3D spatial layout model. Finally, dynamic adjustments are made based on the number of channels, spatial weights, and functional relationships to ensure the symmetry and accessibility of the spatial layout. Spatial force-oriented algorithms or topology constraint optimization algorithms can be used during layout generation to automatically balance the spatial density and passageway length of functional areas, generating a spatial layout model with high visibility, high traffic efficiency, and functional coordination. This provides a spatial configuration foundation for landscape architecture master planning that can be directly converted into design drawings.

[0082] Optionally, S320, based on the number of connection channels corresponding to each capacity allocation scheme, a layout is generated to obtain a fully connected scheme corresponding to each capacity allocation scheme of the landscape garden to be planned, including:

[0083] S321, based on the number of connection channels corresponding to each capacity allocation scheme, build a corresponding number of connection channels between the preset functional areas in the preset spatial layout framework to obtain a fully connected scheme corresponding to each capacity allocation scheme of the landscape garden to be planned.

[0084] It can be understood that a spatial layout framework refers to the spatial coordinate system and topological constraint set used in landscape architecture planning to arrange functional areas and connecting passages. It defines the relative positions, boundary constraints, and connectivity relationships of functional areas in the planar and vertical directions. During layout generation, all functional areas and passages are geometrically mapped within the preset spatial layout framework based on the number of connecting passages corresponding to each capacity allocation scheme. The passage layout process follows the principles of connectivity quantity, capacity ratio, and spatial density constraints of functional areas. This can be achieved through path generation algorithms (such as A...). Path optimization algorithms or Voronoi diagram-based partitioning algorithms automatically plan channel routes, ensuring that channel distribution is structurally uniform, visually harmonious, and functionally efficient. The layout generation result is a set of 3D spatial structure models with fully connected features, where the spatial relationship between each functional area and channel is calculated through structural balancing and path optimization, transforming abstract capacity and channel data into a visualized spatial structure.

[0085] S400: Systematically optimize each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes.

[0086] Systematic optimization, as understood, refers to the process of globally optimizing and coordinating multi-objectives regarding the number of connecting channels, spatial layout structure, and functional efficiency based on a fully connected landscape architecture scheme. This aims to obtain a more rational, economical, and functionally balanced candidate planning scheme. A fully connected scheme is a preliminary connectivity model obtained from capacity allocation and spatial channel calculations, ensuring full coverage between functional areas, but it may not achieve optimal layout coordination and resource utilization. The core task of systematic optimization is to comprehensively consider multiple factors such as ecology, transportation, aesthetics, and construction costs, and to dynamically correct and structurally optimize each group of fully connected schemes. A multi-parameter optimization model can be established based on preset optimization objectives. The objective function of the multi-parameter optimization model can include minimizing the total channel length, maximizing the functional achievement rate, and balancing space utilization. Then, heuristic algorithms (such as Particle Swarm Optimization (PSO) or Genetic Algorithm (GA)) are used to iteratively solve each group of fully connected schemes, adjusting the number, layout, and connection angles of connecting channels in real time. Each iteration calculates the corresponding functional achievement rate, i.e., the comprehensive performance ratio that the scheme can achieve while meeting the interaction needs of all functional areas. The scheme with the highest functional achievement rate or the optimal objective function value is selected as the candidate planning scheme. Through this systematic optimization process, while ensuring the structural integrity of the landscape garden, we can achieve a rational number of passageways, efficient flow organization, and coordinated landscape space, thereby significantly improving the scientific nature, feasibility, and spatial experience value of the planning scheme, and providing solid data support for the final selection of auxiliary design schemes.

[0087] In one possible implementation, S400, systematic optimization is performed on each group of fully connected solutions to obtain candidate planning schemes corresponding to each group of fully connected solutions, including:

[0088] S410, compare the number of connection channels of each group of fully connected schemes with a preset connection channel threshold. If the number of connection channels exceeds the preset connection channel threshold, iterate the number of connection channels of each group of fully connected schemes and calculate the functional implementation rate of the fully connected scheme in each iteration. The fully connected scheme with the highest functional implementation rate after iteration is retained as the candidate planning scheme corresponding to the fully connected scheme.

[0089] It is understood that the threshold for the number of connection channels is a pre-set upper limit parameter; please refer to [link / reference]. Figure 4This method constrains the total number of pathways that can be accommodated in a garden space, preventing land waste, ecological degradation, or increased construction complexity due to excessive pathways. The number of pathways in each fully connected scheme is compared to this threshold; if the number exceeds the threshold, an iterative correction process is triggered. Iterative correction is achieved by gradually reducing redundant pathways and recalculating the connection strength of each functional area. After each iteration, the functional achievement rate of the current scheme is calculated, i.e., the degree to which the interaction needs of functional areas are met. The functional achievement rate can be calculated based on a functional coverage model, set as the ratio of the actual number of connections in each functional area to the theoretically required number of connections. The system continuously executes multiple rounds of iterations, and when the functional achievement rate shows a stable or maximizing trend, the optimal structure is determined. Finally, the scheme with the highest functional achievement rate is retained as the candidate planning scheme. This method can reduce the number of pathways while maintaining functional integrity, thereby achieving spatial optimization, cost control, and ecological coordination, providing a balanced and highly implementable planning foundation for overall garden design.

[0090] In one possible implementation, S400, systematic optimization is performed on each group of fully connected solutions to obtain candidate planning schemes corresponding to each group of fully connected solutions, including:

[0091] S420: If the number of connection channels does not exceed the preset connection channel threshold, optimize the channel path for each group of fully connected schemes to obtain the candidate planning schemes corresponding to each group of fully connected schemes.

[0092] It is understandable that the local structural improvement process performed by a fully connected scheme with the number of connecting passages not exceeding a threshold aims to optimize the passage layout to improve traffic efficiency and landscape harmony while maintaining a reasonable number of passages. The object of passage path optimization is the connection routes between functional areas, and its optimization objectives include minimizing path length, minimizing intersection conflicts, and maximizing visual continuity of the landscape. Constraints on the coordinates of functional area nodes and passable areas can be established in a 3D spatial model, and then shortest path algorithms (such as Dijkstra's algorithm or A*) can be used. The algorithm calculates the optimal path between each functional area pair; then, a path smoothing algorithm (such as B-spline curve fitting) is used to aesthetically and streamline the straight or polygonal paths, ensuring a natural transition in curvature, slope, and landscape views. After optimization, the system re-evaluates the overall functional achievement rate and comprehensive path score to confirm the structural rationality and user comfort of the scheme. Path optimization not only improves traffic organization efficiency but also reduces structural conflicts and landscape fragmentation, making the overall layout of the landscape architecture more harmonious, coherent, and ecological, thus forming a candidate planning scheme that combines functionality and artistry.

[0093] S500 selects the optimal auxiliary design scheme from all candidate planning schemes.

[0094] It is understandable that the selection of the optimal auxiliary design scheme is a decision-making stage in the landscape architecture planning process. Its main function is to select the scheme that performs best under comprehensive indicators from multiple candidate planning schemes, providing a reference for subsequent design refinement and construction. Candidate planning schemes are intermediate results with reasonable structure and complete functions, formed after systematic optimization and pathway optimization. During the selection process, calculations can be performed based on a multi-dimensional comprehensive evaluation model, which includes indicators such as functional achievement rate, pathway layout coordination, construction feasibility, ecological impact index, and landscape visual score. Each candidate scheme obtains a comprehensive evaluation value through a weighted scoring method, with weights set according to project planning objectives or owner preferences. The Analytic Hierarchy Process (AHP) or fuzzy comprehensive evaluation method can be used for scoring and ranking, ultimately selecting the scheme with the highest comprehensive evaluation value as the optimal auxiliary design scheme, taking into account functionality, ecology, and artistry, thereby improving the overall design quality and implementation effect.

[0095] Corresponding to the landscape architecture computer-aided design method in the above embodiments, this application also provides a landscape architecture computer-aided design system, in which each unit can implement each step of the landscape architecture computer-aided design method. Figure 5 The diagram shows a structural block diagram of a computer-aided landscape design system provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0096] Reference Figure 5 The landscape architecture computer-aided design system includes:

[0097] The acquisition unit is used to acquire multi-dimensional geographic attribute data corresponding to each preset spatial grid from a preset multi-source geographic information database.

[0098] The analysis unit is used to analyze the multi-dimensional geographic attribute data corresponding to each of the spatial grids to obtain multiple grid areas with risk coupling effects and to identify them as risk areas to be investigated; wherein, the grid area is the geographic area corresponding to a single spatial grid.

[0099] The retrieval unit is used to retrieve the refined geographic monitoring data and regional response data corresponding to each of the risk areas to be investigated from the multi-source geographic information database.

[0100] The identification unit is used to analyze the refined geographic monitoring data and regional response data of each of the risk areas to be investigated, and to identify specific impact information instances contained in each of the risk areas to be investigated; wherein, the specific impact information instance is an information instance in which the rate of change of information flow exceeds a threshold within a continuous time period.

[0101] The handling unit is used to determine a risk handling plan for the specific impact information instance based on the specific impact information instance of the risk area to be investigated.

[0102] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0103] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit module can exist physically separately, or two or more unit modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0104] This application also provides an electronic device. Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the electronic device 6 to perform the steps in any of the above-described embodiments of the landscape computer-aided design method, or to perform the functions of each unit in the above-described system embodiments.

[0105] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0106] The electronic device can be of various types of intelligent monitoring devices. This electronic device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0107] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0108] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0109] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0110] This application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the steps in any of the above method embodiments.

[0111] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0112] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0113] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] In the embodiments provided in this application, it should be understood that the disclosed landscape architecture computer-aided design system / electronic device and method can be implemented in other ways. For example, the landscape architecture computer-aided design system / electronic device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0115] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A computer-aided design method for landscape architecture, characterized in that, include: Obtain the basic parameters of the site for the landscape garden to be planned; wherein, the basic parameters of the site include the number of landscape modules, the bearing capacity of the landscape modules, and the number of preset functional areas; Based on the number of landscape modules and the carrying capacity of the landscape modules, calculate multiple capacity allocation schemes corresponding to the landscape garden to be planned. Based on the number of preset functional areas and the various capacity allocation schemes corresponding to the landscape garden to be planned, multiple sets of fully connected schemes for the landscape garden to be planned are obtained; wherein, the fully connected scheme is used to ensure that there is at least one physical or functional access path between all preset functional areas; The complete connectivity schemes in each group are systematically optimized to obtain the candidate planning schemes corresponding to each group of complete connectivity schemes; The optimal auxiliary design scheme is obtained by screening all the candidate planning schemes; The step of obtaining multiple fully connected schemes for the planned landscape garden based on the number of preset functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned includes: Based on the number of preset functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned, calculate the number of connection channels corresponding to each capacity allocation scheme; Based on the number of connection channels corresponding to each of the capacity allocation schemes, a layout is generated to obtain a fully connected scheme corresponding to each of the capacity allocation schemes for the landscape garden to be planned.

2. The computer-aided design method for landscape architecture as described in claim 1, characterized in that, The calculation of multiple capacity allocation schemes corresponding to the landscape garden to be planned, based on the number of landscape modules and the carrying capacity of the landscape modules, includes: Based on the number of landscape modules and their carrying capacity, capacity allocation constraints and capacity allocation ranges for each preset functional area are determined. The constraints include that the total capacity of all preset functional areas does not exceed the total carrying capacity of the landscape modules, and that the capacity of each preset functional area is within its corresponding capacity allocation range. The lower limit of the capacity of a single preset functional area is the carrying capacity of a single landscape module, and the upper limit is the total carrying capacity of the landscape modules, where the total carrying capacity is the product of the number of landscape modules and the carrying capacity of a single landscape module. Based on the constraints and the capacity allocation range of each preset functional area, multiple capacity allocation schemes corresponding to the planned landscape gardens that meet the constraints are generated.

3. The computer-aided design method for landscape architecture as described in claim 1, characterized in that, The step of calculating the number of connection channels corresponding to each capacity allocation scheme based on the number of preset functional areas and each capacity allocation scheme corresponding to the landscape garden to be planned includes: The number of fully connected basic channels is determined based on the number of preset functional areas; wherein, the number of basic channels is the product of the number of preset functional areas multiplied by the number of preset functional areas minus one, and then the product is divided by two. Calculate the total capacity of any two preset functional areas based on each capacity allocation scheme corresponding to the landscape garden to be planned; The number of connection channels corresponding to each capacity allocation scheme is calculated based on the total capacity.

4. The computer-aided design method for landscape architecture as described in claim 3, characterized in that, The step of calculating the number of connection channels corresponding to each capacity allocation scheme based on the total capacity includes: Obtain the carrying threshold for each connection channel; the carrying threshold is the maximum limit of the sum of the capacities of the two preset functional areas that a single channel can adapt to; Based on the sum of the capacities of any two preset functional areas in each of the capacity allocation schemes, determine whether the sum of the capacities exceeds the carrying threshold. If the total capacity does not exceed the carrying threshold, the number of connection channels between preset functional areas is maintained at 1 corresponding to the basic number of channels; If the total capacity exceeds the carrying threshold, the number of additional channels between preset functional areas is determined based on the total capacity and the carrying threshold. The number of basic channels and the number of additional channels between all preset functional area pairs for each capacity allocation scheme are counted to obtain the number of connection channels corresponding to the capacity allocation scheme.

5. The computer-aided design method for landscape architecture as described in claim 4, characterized in that, If the total capacity exceeds the carrying threshold, determining the number of additional channels between preset functional areas based on the total capacity and the carrying threshold includes: If the total capacity exceeds the carrying capacity threshold, calculate the ratio of the total capacity to the carrying capacity threshold, and integerize the ratio to obtain the excess multiple. The number of additional channels between preset functional areas is determined based on the multiplier.

6. The computer-aided design method for landscape architecture as described in claim 1, characterized in that, The layout generation based on the number of connection channels corresponding to each capacity allocation scheme yields a fully connected scheme for each capacity allocation scheme of the landscape garden to be planned, including: Based on the number of connection channels corresponding to each capacity allocation scheme, a corresponding number of connection channels are set up between each preset functional area in a preset spatial layout framework to obtain a fully connected scheme corresponding to each capacity allocation scheme of the landscape garden to be planned.

7. The computer-aided design method for landscape architecture as described in claim 1, characterized in that, The systematic optimization of each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes includes: The number of connection channels in each group of fully connected schemes is compared with a preset connection channel threshold. If the number of connection channels exceeds the preset connection channel threshold, the number of connection channels in each group of fully connected schemes is iterated and the functional achievement rate of the fully connected scheme in each iteration is calculated. The fully connected scheme with the highest functional achievement rate after iteration is retained as the candidate planning scheme corresponding to the fully connected scheme.

8. The computer-aided design method for landscape architecture as described in claim 7, characterized in that, The systematic optimization of each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes includes: If the number of connection channels does not exceed a preset connection channel threshold, channel path optimization is performed on each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes.

9. A computer-aided design system for landscape architecture, characterized in that, The landscape architecture computer-aided design system for implementing the method according to any one of claims 1 to 8 comprises: The acquisition unit is used to acquire the basic parameters of the site of the landscape garden to be planned; wherein, the basic parameters of the site include the number of landscape modules, the bearing capacity of the landscape modules, and the number of preset functional areas; The calculation unit is used to calculate multiple capacity allocation schemes corresponding to the landscape garden to be planned based on the number of landscape modules and the carrying capacity of the landscape modules; The connectivity unit is used to obtain multiple fully connected schemes for the landscape garden to be planned based on the number of preset functional areas and the various capacity allocation schemes corresponding to the landscape garden to be planned. An optimization unit is used to systematically optimize each group of fully connected schemes to obtain candidate planning schemes corresponding to each group of fully connected schemes. The result unit is used to select the optimal auxiliary design scheme from all the candidate planning schemes.

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