Method and system for generating variable space residence design scheme

Abstract

The invention discloses a method and system for generating a variable space residence design scheme, and relates to the field of residence design, and the method comprises the steps: obtaining an initial residence three-dimensional model containing fixed and variable function regions, and providing a basis for subsequent design; generating a plurality of pre-selected positions in the fixed function area based on preset building specifications and structure requirements, calculating comprehensive performance indexes to determine optimal position distribution, and generating pre-selected positions in the variable function area according to user demand parameters, space variability rules and the position distribution of the fixed function area; the method comprises the steps that a preset module is arranged in a corresponding area, parameter value optimization layout is obtained through space variability simulation, finally, the preset module is placed in the corresponding area to generate the residence design three-dimensional model, the preset module adopts a standardized whole set of industrial finished products, and the personalized space requirements of different families in different development stages are met while the modular production efficiency is guaranteed. By implementing the method, the design efficiency of the variable space residence can be improved.

Description

Technical Field

[0001] The present application relates to the field of residential design, and in particular to a method and system for generating a variable space residential design scheme. Background Art

[0002] At present, the design of variable space housing mainly adopts the method of modular design and movable partition. The designer first determines the location of fixed functional areas, such as kitchens and bathrooms, and then plans variable functional areas in the remaining space. In the variable functional areas, designers will use movable partition walls or multifunctional furniture modules, such as foldable beds, retractable dining tables, etc., to achieve multifunctional conversion of space. This method changes the spatial layout through simple mechanical transformation to adapt to different life scenarios.

[0003] However, this automatic layout method based on preset templates has certain problems in practical application. If the focus is on the space utilization of residential design, the traffic flow design may be unreasonable. Meeting the traffic flow design may lead to low space utilization. Designers need to spend a lot of time fine-tuning the design, resulting in inefficient variable space residential design. Summary of the invention

[0004] The present application provides a method and system for generating a variable space residential design solution, which are used to improve the efficiency of variable space residential design.

[0005] In a first aspect, the present application provides a method for generating a variable space residential design scheme, which is applied to a system for generating a variable space residential design scheme, the method comprising: obtaining an initial residential three-dimensional model of a target design residence, the initial residential three-dimensional model comprising a fixed function area and a variable function area; within the fixed function area, based on preset building specifications and structural requirements, generating a plurality of fixed function pre-selected positions, calculating a comprehensive performance index corresponding to each fixed function pre-selected position, and using the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution, the comprehensive performance index being obtained by weighted calculation of space utilization rate, assembly rate and moving line efficiency ratio; within the variable function area, based on user demand parameters, space utilization rate and moving line efficiency ratio, The method comprises the following steps: according to the spatial variability rules and the position distribution of the fixed functional area, a plurality of pre-selected variable function positions are generated; a computational simulation tool is used to simulate the spatial variability of each variable function position based on the initial residential three-dimensional model, and a spatial variability parameter value corresponding to each variable function position is obtained, and the spatial variability parameter value is obtained by weighted calculation of the spatial conversion efficiency and the functional fitness; according to the spatial variability parameter value, the initial layout of the variable function area is optimized to obtain the position distribution of the variable function area; based on the position distribution of the fixed function area, a preset fixed module building is placed in the fixed function area, and based on the position distribution of the variable function area, a preset movable module is placed in the variable function area to generate a residential design three-dimensional model.

[0006] By adopting the above technical solution, the initial residential three-dimensional model containing fixed and variable functional areas is first obtained to provide a basis for subsequent design. Based on the preset building specifications and structural requirements, multiple pre-selected positions are generated in the fixed functional area and the comprehensive performance index is calculated to determine the optimal position distribution, thereby improving the space utilization rate, assembly rate and dynamic line efficiency ratio. In the variable functional area, the pre-selected positions are generated according to the user demand parameters, spatial variability rules and the position distribution of the fixed functional area, and then the parameter value optimization layout is obtained through spatial variability simulation. Finally, the preset modules are placed in the corresponding area to generate a residential design three-dimensional model, in which the preset modules use standardized complete sets of industrial products. While ensuring the modular production efficiency, they meet the personalized space needs of different families at different development stages, realize the intelligent design of residential space, and improve the design efficiency.

[0007] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining an initial residential three-dimensional model of the target designed residence, wherein the initial residential three-dimensional model includes fixed functional areas and variable functional areas, the method further includes: receiving personal information and design requirements input by a user, and constructing a user portrait based on the personal information and the design requirements, wherein the user portrait includes family structure, living habits and space preferences; generating multiple typical life scenes based on the user portrait, wherein each of the life scenes corresponds to a group of functional elements; performing a space demand analysis on each group of the functional elements to determine the minimum space size and form requirements required to realize each of the functional elements; designing multiple space modules according to the minimum space size and the form requirements, wherein the space modules include fixed functional modules and variable functional modules; combining multiple space modules based on a preset space combination rule library to obtain a module space combination scheme, wherein the preset space combination rule library includes module connection rules, module orientation rules, proximity rules and module variability rules; dividing the fixed function modules in the module space combination scheme into fixed functional areas, dividing the variable function modules into variable functional areas, and generating an initial residential three-dimensional model based on the fixed functional areas and the variable functional areas.

[0008] By adopting the above technical solution, before obtaining the initial residential three-dimensional model, user information and needs are received to build a user portrait, life scenes and functional elements are generated based on the user portrait, and space demand analysis is performed to determine the module size and shape requirements to make the design more in line with the user's actual life. Fixed and variable functional modules are designed and combined according to the rule library, and fixed and variable functional areas are divided to generate an initial model, which ensures the rationality and scientificity of the area division.

[0009] In combination with some embodiments of the first aspect, in some embodiments, the step of generating multiple fixed function pre-selected positions within the fixed function area based on preset building specifications and structural requirements specifically includes: within the fixed function area, identifying key function points and equipment positions within the fixed function area; converting the minimum spacing requirements in the preset building specifications into constraints between equipment, and setting the structural requirements as fixed boundaries, determining the movable range of the key function points and the equipment positions; generating multiple fixed function pre-selected positions based on the constraints, fixed boundaries and the movable range.

[0010] By adopting the above technical solution, key functional points and equipment locations are identified in fixed functional areas, building code requirements are converted into constraints and the movable range is determined. The pre-selected locations determined in this way can better consider the relationship between equipment and space utilization, avoiding unreasonable layout. When calculating the comprehensive performance indicators, the space utilization rate, assembly rate and moving line efficiency ratio are calculated and weighted respectively, which can comprehensively evaluate the advantages and disadvantages of each pre-selected location.

[0011] In combination with some embodiments of the first aspect, in some embodiments, the comprehensive performance index corresponding to each fixed function pre-selected position is calculated, and the fixed function pre-selected position with the highest comprehensive performance index is used as the fixed function area position distribution, and the comprehensive performance index is obtained by weighted calculation of the space utilization rate and the assembly rate, specifically including: calculating the space utilization rate and the assembly rate of each fixed function pre-selected position, the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules adopted; based on the preset key moving line path, measuring the actual length of the preset key moving line path in each of the fixed function pre-selected positions, comparing the actual length of the preset key moving line path with the preset ideal length, and obtaining the moving line efficiency ratio corresponding to each fixed function pre-selected position; assigning weight coefficients to the space utilization rate, the assembly rate and the moving line efficiency, and calculating the comprehensive performance index based on the weight coefficient, the space utilization rate, the assembly rate and the moving line efficiency; using the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution.

[0012] By adopting the above technical solution, the space utilization rate and assembly rate of each fixed-function pre-selected position are calculated, the degree of space use and module standardization is clarified, and the movement efficiency ratio is obtained by measuring and comparing the actual length with the ideal length based on the preset key movement path. Weight coefficients are assigned to these indicators and the comprehensive performance indicators are calculated. The position with the highest comprehensive performance index is used as the location distribution of the fixed-function area, ensuring that the fixed-function area reaches the optimal state in terms of space utilization, module assembly and movement design.

[0013] In combination with some embodiments of the first aspect, in some embodiments, the computational simulation tool is used to perform spatial variability simulation on each variable functional position based on the initial residential three-dimensional model to obtain spatial variability parameter values ​​corresponding to each variable functional position, specifically including: importing the initial residential three-dimensional model into the computational simulation tool, and for each of the variable functional positions, simulating the spatial change process of the variable functional position under different life scenarios to obtain the operation time and operation complexity required for converting one function to another, and each of the life scenarios corresponds to each functional layout of all the variable functional positions; calculating the spatial conversion efficiency based on the operation time and the operation complexity; evaluating the functional fitness of each variable functional position under each functional layout based on the spatial change process, and the functional fitness is calculated by space utilization and user usage efficiency, and the space utilization is obtained by evaluating the spatial changes in the simulation, and the user usage efficiency is obtained by evaluating the time it takes for the user to complete a specific task in the simulation; and obtaining the variability parameter value by weighted calculation based on the spatial conversion efficiency and the functional fitness.

[0014] By adopting the above technical solution, the initial residential three-dimensional model is imported into the computational simulation tool, and the spatial variability of each variable functional position is simulated. The simulation process covers the spatial changes under different life scenarios. The simulation obtains the operation time and operation complexity to calculate the spatial conversion efficiency, and evaluates the functional adaptability, thereby improving the spatial conversion efficiency and functional adaptability of the variable functional area.

[0015] In combination with some embodiments of the first aspect, in some embodiments, the step of optimizing the initial layout of the variable functional area according to the spatial variability parameter value to obtain the position distribution of the variable functional area specifically includes: establishing a spatial layout optimization model according to the spatial variability parameter value of each variable functional position; setting an optimization objective function based on the spatial layout optimization model, and the optimization objective function contains preset constraints, and the preset constraints include the minimum area requirement of the variable functional position and the minimum spacing requirement between functional areas; using the optimization algorithm to iteratively optimize the layout of the variable functional area to obtain a new layout scheme; performing spatial variability simulation on each of the new layout schemes, and calculating the variability parameter value of each of the new layout schemes; and using the layout scheme whose variability parameter value is greater than the preset parameter threshold as the position distribution of the variable functional area.

[0016] By adopting the above technical scheme, a spatial layout optimization model is established according to the spatial variability parameter value of each variable functional position, and an optimization objective function containing preset constraints is set to ensure that the optimization process meets the actual requirements. The optimization algorithm is used to iteratively optimize the layout of the variable functional area, and the layout scheme with a variability parameter value greater than the preset parameter threshold is used as the position distribution of the variable functional area, ultimately achieving the optimization of the layout of the variable functional area.

[0017] In combination with some embodiments of the first aspect, in some embodiments, after the step of placing a preset fixed module building into the fixed functional area based on the position distribution of the fixed functional area, and placing a preset movable module into the variable functional area based on the position distribution of the variable functional area, and generating a residential design three-dimensional model, the method also includes: sending the residential design three-dimensional model to a preset client for display.

[0018] By adopting the above technical solution, a three-dimensional model of residential design is generated, which fully presents the spatial layout and functional settings of the house, intuitively displays the design results, improves the visualization of residential design, and provides users with a clear design solution.

[0019] In a second aspect, an embodiment of the present application provides a system for generating a variable space residential design scheme, the system for generating a variable space residential design scheme comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, the one or more processors call the computer instructions to enable the system for generating a variable space residential design scheme to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0020] In the third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product is run on a system for generating a variable space residential design scheme, the system for generating a variable space residential design scheme executes the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a system for generating a variable-space residential design scheme, the system for generating a variable-space residential design scheme executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] It can be understood that the generation system of the variable space residential design scheme provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application obtains an initial residential three-dimensional model containing fixed and variable functional areas to provide a basis for subsequent design. Based on preset building specifications and structural requirements, multiple pre-selected positions are generated in fixed functional areas and the optimal position distribution is determined by calculating comprehensive performance indicators, thereby improving space utilization, assembly rate and dynamic line efficiency ratio. In the variable functional area, pre-selected positions are generated based on user demand parameters, spatial variability rules and fixed functional area position distribution, and then the parameter value optimization layout is obtained through spatial variability simulation. Finally, the preset modules are placed in the corresponding areas to generate a residential design three-dimensional model, in which the preset modules use standardized complete sets of industrial products. While ensuring modular production efficiency, they meet the personalized space needs of different families at different development stages, realize the intelligent design of residential space, and improve design efficiency.

[0024] 2. This application receives user information and needs to build a user portrait before obtaining the initial residential three-dimensional model, generates life scenes and functional elements based on the user portrait, conducts space demand analysis to determine module size and shape requirements, so that the design is more in line with the user's actual life, designs fixed and variable functional modules and combines them according to the rule library, divides the fixed and variable functional areas to generate the initial model, and ensures the rationality and scientificity of the area division.

[0025] 3. This application clarifies the degree of space utilization and module standardization by calculating the space utilization rate and assembly rate of each fixed-function pre-selected position, measures the preset key traffic line path and compares the actual length with the ideal length to obtain the traffic line efficiency ratio, assigns weight coefficients to these indicators and calculates the comprehensive performance index, and distributes the position with the highest comprehensive performance index as the fixed function area position distribution, ensuring that the fixed function area reaches the optimal state in terms of space utilization, module assembly and traffic line design. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a method for generating a variable space residential design scheme in an embodiment of the present application; Figure 2 is another flow chart of the method for generating a variable space residential design solution in an embodiment of the present application; Figure 3 It is another flow chart of the method for generating a variable space residential design scheme in the embodiment of the present application; Figure 4 It is a schematic diagram of a physical device structure of a system for generating a variable space residential design solution in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of a method for generating a variable space residential design solution in an embodiment of the present application.

[0030] S101. Obtain an initial three-dimensional residential model of a target designed residential building, wherein the initial three-dimensional residential model includes fixed functional areas and variable functional areas.

[0031] Among them, the target design residence represents a specific residential project that requires intelligent design, the initial residential three-dimensional model refers to a preliminary three-dimensional digital model of the target design residence, the fixed functional area is used to represent the immutable functional space in the residence, such as the kitchen, bathroom, etc., and the variable functional area refers to the space area that can be adjusted and changed according to needs, such as the living room, bedroom and other areas that can be flexibly changed in use.

[0032] Specifically, when starting the residential intelligent design process, you first need to obtain a preliminary residential 3D model as the basis for the design. The initial residential 3D model is usually created by an architect or designer based on project requirements and basic layout ideas. The model has divided the approximate range of fixed functional areas and variable functional areas. The initial residential 3D model is obtained by importing CAD files, BIM models or files in other 3D modeling software.

[0033] In some embodiments, the initial residential three-dimensional model can be obtained in a variety of ways: optionally, by using professional 3D modeling software such as Autodesk Revit or SketchUp to create an initial model, draw a floor plan according to project requirements and site conditions, and then stretch the floor plan into a three-dimensional model, divide the model into fixed function areas and variable function areas, and add basic walls, doors, windows and other structural elements, and export the created model to a general 3D file format; optionally, the initial model can be quickly generated using a preset residential template library, and the basic model closest to the target design residence can be selected from the template library. The model is adjusted according to specific needs, such as modifying the room size, adjusting the wall position, etc., marking the fixed function area and the variable function area in the adjusted model, and saving the modified model in a format that the system can recognize. It is understandable that other methods can also be used to obtain the initial residential three-dimensional model, such as using 3D scanning technology to scan and model existing buildings, or quickly generating an initial model through AI-assisted design tools, which are not limited here.

[0034] S102. Within the fixed function area, based on preset building specifications and structural requirements, generate multiple fixed function pre-selected positions, calculate the comprehensive performance index corresponding to each fixed function pre-selected position, and use the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution. The comprehensive performance index is obtained by weighted calculation of space utilization rate, assembly rate and traffic flow efficiency ratio.

[0035] Among them, the preset building specifications represent the standardized building design rules that need to be followed during the design process. Structural requirements refer to the engineering and technical requirements to ensure the safety and stability of the building. The fixed function pre-selected positions are used to represent the possible layout schemes within the fixed function area. The comprehensive performance index refers to the comprehensive score used to evaluate the advantages and disadvantages of the fixed function layout. The space utilization rate represents the efficiency of space use. The assembly rate is used to represent the degree of use of standardized modules. The moving line efficiency ratio refers to the ratio of the actual moving line to the ideal moving line.

[0036] Specifically, after the initial residential 3D model is determined, the fixed function area needs to be designed in detail. The system will generate multiple possible layout schemes in the fixed function area based on the preset building specifications and structural requirements, namely the fixed function pre-selected positions, evaluate each pre-selected position, and calculate its comprehensive performance index. The comprehensive performance index is based on the space utilization efficiency, standardization and ease of use, and the scheme with the highest comprehensive performance index is selected as the final fixed function area layout.

[0037] In some embodiments, the layout optimization of fixed functional areas can be achieved in a variety of ways: Optionally, a parametric design method can be used to define key parameters of fixed functional areas, such as room size, equipment location, etc., set parameter variation ranges and constraints, such as minimum spacing requirements, and use parametric design software to automatically generate multiple qualified layout schemes, calculate space utilization, assembly rate and dynamic line efficiency for each scheme, and weightedly calculate comprehensive performance indicators, and select the scheme with the highest comprehensive performance index as the final layout; Optionally, a spatial syntax analysis method can be used to abstract the fixed functional area into a topological graph, with nodes representing functional units and edges representing connection relationships, and calculate spatial syntax indicators such as integration and connectivity of each node, generate multiple layout schemes based on these indicators, and calculate the space utilization, assembly rate and dynamic line efficiency of each scheme, calculate the comprehensive score of each scheme based on spatial syntax indicators and performance indicators, and select the scheme with the highest score as the final layout of the fixed functional area. It can be understood that other methods can also be used, which are not limited here.

[0038] For example, the comprehensive performance index is composed of three sub-indicators, space utilization rate, assembly rate and traffic flow efficiency ratio. Assuming that the weights of these three indicators are w1, w2 and w3 respectively, the calculation formula of the comprehensive performance index is, comprehensive performance index = w1*space utilization rate + w2*assembly rate + w3*traffic flow efficiency ratio, where space utilization rate = effective use area / total area, effective use area refers to the area that can be actually utilized, excluding the space occupied by walls, pipes, etc., total area refers to the total area of ​​fixed functional areas, assembly rate = prefabricated component volume / total building volume, prefabricated component volume refers to the sum of the volumes of prefabricated modules used (such as integrated bathroom, integrated kitchen, etc.), and the total building volume refers to the total volume of fixed functional areas, traffic flow efficiency ratio = ideal traffic flow length / actual traffic flow length, the ideal traffic flow length is the sum of the straight-line distances between each functional area, and the actual traffic flow length is the sum of the actual walking distances between each functional area after considering the actual layout.

[0039] S103. In the variable function area, based on user demand parameters, spatial variability rules and the position distribution of the fixed function area, generate a plurality of variable function pre-selected positions.

[0040] Among them, the variable function area refers to the space in the house that can be flexibly adjusted according to needs. User demand parameters refer to specific indicators that reflect user living habits, preferences and needs. Spatial variability rules are used to represent the constraints and possibilities of spatial changes. The fixed function area location distribution refers to the fixed function layout determined in the previous step. The variable function pre-selected location represents the possible layout schemes within the variable function area.

[0041] Specifically, after completing the layout of fixed functional areas, the variable functional areas need to be designed. The system will analyze the demand parameters provided by the user, such as family structure, lifestyle, etc., to understand the user's specific needs for variable space. The system will consider the pre-defined spatial variability rules, which define the possibilities and limitations of space changes, such as the range of wall movement, the location of equipment interfaces, etc. At the same time, the system also needs to consider the determined fixed functional area layout to ensure that the design of the variable functional area is coordinated with the fixed area. Based on this information, the system will generate multiple possible layout plans for the variable functional area, that is, the pre-selected positions of the variable functions.

[0042] In some embodiments, the generation of variable function pre-selected positions can be achieved in a variety of ways: Optionally, a modular design method can be used to define a series of functional modules according to user demand parameters, such as work area, rest area, entertainment area, etc., and design variable forms of these modules, such as folding furniture, sliding partitions, etc. Based on the spatial variability rules, determine the combination mode and change possibility between modules, consider the location distribution of fixed functional areas, try different module combinations and arrangements in the variable functional area, and generate multiple qualified variable function pre-selected positions; Optionally, a parametric design method can be used to convert user demand parameters, spatial variability rules and fixed functional area location distribution into quantifiable design parameters, establish a parametric model, define the relationship and constraints between spatial elements, and automatically generate multiple qualified spatial layout plans by adjusting parameter values. The generated plans are screened and optimized to ensure that each plan meets the basic requirements, and multiple optimized variable function pre-selected positions are output. It can be understood that other methods can also be used to achieve the generation of variable function pre-selected positions, such as using a topology optimization algorithm to optimize the spatial layout, or using a rule-based expert system to generate the layout, which is not limited here.

[0043] S104. Using a computational simulation tool, based on the initial residential three-dimensional model, perform spatial variability simulation on each variable functional position to obtain a spatial variability parameter value corresponding to each variable functional position. The spatial variability parameter value is obtained by weighted calculation of spatial conversion efficiency and functional fitness.

[0044] Among them, computational simulation tools refer to software systems used for digital simulation and analysis. Spatial variability simulation refers to the digital simulation of spatial change processes. Spatial variability parameter values ​​are used to quantify indicators for evaluating spatial variability. Spatial conversion efficiency refers to the ease with which space can be converted from one function to another. Functional fitness refers to the suitability of space for a specific function.

[0045] Specifically, after generating multiple variable function pre-selected positions, these plans need to be evaluated and compared. The system will import the initial residential three-dimensional model into the computational simulation tool to simulate the spatial variability of each variable function pre-selected position. This process simulates the change process of the space under different functional requirements, including furniture movement, partition adjustment, etc. Through simulation, the system can evaluate the spatial conversion efficiency of each pre-selected position, that is, the difficulty and time required to convert from one functional layout to another. At the same time, the system will also evaluate the functional fitness under each functional layout, that is, the degree of support of the space for a specific function. The system will perform weighted calculations on the spatial conversion efficiency and functional fitness to obtain the spatial variability parameter value of each pre-selected position.

[0046] In some embodiments, spatial variability simulation and parameter value calculation can be achieved in a variety of ways: Optionally, dynamic simulation software can be used for simulation, and the three-dimensional model of each variable function pre-selected position can be imported into the dynamic simulation software, and different functional scenes can be set, such as work mode, rest mode, etc., to simulate the movement and change process of spatial elements (such as furniture, partitions) between different scenes, record the time and operation steps required for each change, and calculate the spatial conversion efficiency, which can be expressed as the reciprocal of the average transformation time. At the same time, the space utilization rate and user comfort under each functional layout are evaluated as indicators of functional fitness, and the spatial conversion efficiency and functional fitness are weighted averaged according to preset weights to obtain the spatial variability parameter value; Optionally, a discrete event simulation method can be used to decompose the spatial change process into a series of discrete events, such as moving furniture, adjusting partitions, etc., and assign execution time and resource consumption to each event. An event sequence is constructed to simulate different functional conversion processes, and the total time and resource consumption of the entire conversion process is counted to calculate the spatial conversion efficiency. At the same time, by evaluating the spatial performance indicators under each functional layout, such as lighting, ventilation, privacy, etc., the functional fitness is calculated, and the spatial variability parameter value is calculated by combining these indicators. It is understandable that other methods can also be used to achieve spatial variability simulation and parameter value calculation, such as using finite element analysis to evaluate the feasibility of spatial structure changes, or using multi-criteria decision-making methods to comprehensively evaluate spatial performance, which are not limited here.

[0047] S105. Optimize the initial layout of the variable functional area according to the spatial variability parameter value to obtain the position distribution of the variable functional area.

[0048] Among them, the spatial variability parameter value represents a quantitative evaluation index of the spatial variability. The variable function area refers to the space in the house that can be flexibly adjusted according to needs. The initial layout refers to the initial design of the variable function area space layout plan. Optimization refers to improving the performance of the design plan through adjustment and improvement. The variable function area position distribution represents the optimized variable function area space layout plan.

[0049] Specifically, after completing the spatial variability simulation and obtaining the spatial variability parameter values ​​of each pre-selected position, the initial layout of the variable functional area needs to be optimized. The system will sort the spatial variability parameter values ​​of all pre-selected positions and identify the best performing solutions. The system will analyze the common characteristics of these high-performance solutions, such as the space division method, furniture layout principles, etc. Based on these analysis results, the system will adjust and improve the initial layout. This process includes adjusting the partition position, rearranging the furniture layout, optimizing the equipment interface position, etc. During the adjustment process, the system will continuously evaluate the spatial variability parameter values ​​of the new solution to ensure that each adjustment can improve the overall performance. When the optimization reaches the preset goal or cannot continue to improve significantly, the system will output the final variable functional area location distribution plan. This optimized solution not only retains the basic framework of the initial layout, but also significantly improves the variability performance of the space.

[0050] In some embodiments, the optimization of the layout of the variable functional area can be achieved in a variety of ways: Optionally, an iterative optimization method can be used, starting from the initial layout, gradually making small adjustments, evaluating the scheme after each adjustment, calculating its spatial variability parameter value, retaining the scheme with better performance, and continuing to the next round of adjustments. Repeat this process multiple times, continuously improve the layout scheme, and when the preset number of iterations or performance requirements are reached, select the best scheme as the final variable functional area position distribution; Optionally, a template matching and adjustment method can be used to establish a high-performance layout template library containing a variety of excellent variable functional area layout schemes, select the template most similar to the initial layout from the template library, compare the selected template with the initial layout, find out the part that needs to be adjusted, and adjust the layout accordingly according to the actual situation to make it closer to the high-performance template, evaluate the adjusted scheme, and adopt it if the performance improvement is obvious, otherwise try other templates or adjustment methods. It can be understood that other methods can also be used to achieve this, which is not limited here.

[0051] S106: Based on the position distribution of the fixed functional area, a preset fixed module building is placed in the fixed functional area, and based on the position distribution of the variable functional area, a preset movable module is placed in the variable functional area to generate a three-dimensional residential design model.

[0052] Among them, the fixed functional area location distribution refers to the spatial layout of the unchangeable use. The preset fixed module building refers to the standardized fixed functional unit, such as kitchen, bathroom, etc. The variable functional area location distribution refers to the spatial layout of adjustable use. The preset movable module refers to the flexibly adjustable spatial unit, such as movable partitions, etc. The residential design three-dimensional model refers to the digital residential design plan.

[0053] Specifically, this step is to convert the previously optimized layout into a specific 3D model. The system will place pre-designed fixed modules, such as kitchen and bathroom units, at the corresponding positions according to the layout of fixed functional areas, and movable modules, such as partitions and adjustable furniture, according to the layout of variable functional areas. The system will ensure that the connections between the modules are reasonable, such as the location of doors and windows and the layout of pipelines, etc. The system generates a complete 3D model to show the overall layout and possible spatial changes.

[0054] In some embodiments, the generation of a three-dimensional model can be achieved in a variety of ways: optionally, using a simple module assembly method, preparing a basic three-dimensional model library containing commonly used fixed and movable modules, selecting appropriate modules from the library according to the layout plan, placing these modules in designated locations in the virtual space, adjusting the connections between the modules, ensuring that the overall layout is reasonable, adding basic lighting and materials, and generating a simple but practical three-dimensional model; optionally, using basic parametric design to create a simple residential frame model, setting basic parameters for each space unit, such as size and position, setting these parameters according to the layout plan, and the system automatically adjusting the space layout according to the parameters to generate a basic three-dimensional model to display the main spatial structure and functional areas. It is understandable that other methods can also be used to generate three-dimensional models, such as using ready-made architectural design software or using simple computer-aided design tools, which are not limited here.

[0055] In some embodiments, the variable space residential design scheme can not only realize modular design, but also meet personalized needs. For example, the system can provide differentiated space layout schemes according to different family types (formation period, growth period, mature period, etc.), adjust functional settings based on factors such as the number of family members and age, and provide additional options based on standardized modules to meet specific needs. In terms of the refined design of functional space, it supports double entrance settings to enhance privacy, and can be divided into family entrance lines and guest entrance lines; supports the segmented design of bathroom space to enhance the user experience; achieves a 5-10% storage space share through embedded design; adopts an open kitchen layout with integrated design, etc. At the same time, it adopts the concept of industrialized production and installation, uses a set of industrial products with standard design, and ensures quality stability and service life through industrialized production.

[0056] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the method for generating a variable space residential design solution in an embodiment of the present application.

[0057] S201. Receive personal information and design requirements input by a user, and build a user portrait based on the personal information and the design requirements. The user portrait includes family structure, living habits, and space preferences.

[0058] Personal information refers to the user's basic information, including age, gender, occupation, income, etc. Design requirements refer to the user's specific requirements for the house, such as the number of rooms, size, style preferences, etc. User portraits are a comprehensive description of user characteristics, including family structure (such as single, couple, family with children, etc.), living habits (such as work and rest time, eating habits, leisure methods, etc.) and space preferences (such as open or closed space, natural light requirements, storage needs, etc.). For example, a young dual-income family needs a flexible workspace, while a family with children needs a multi-functional activity area.

[0059] In this step, the system first collects the user's personal information and design requirements through the user interface or questionnaire survey. The system uses data analysis algorithms, such as cluster analysis or decision trees, to integrate the collected information into a complete user portrait. This portrait not only contains explicit data, such as the number of family members, but also contains implicit information inferred from the data, such as lifestyle and space usage habits. For example, based on the user's occupation and hobbies, the user's needs for work space and leisure space can be inferred.

[0060] S202: Generate multiple typical life scenarios based on the user portrait, each of which corresponds to a set of functional elements.

[0061] Typical life scenarios refer to various situations that users may encounter in their daily lives, such as work, rest, entertainment, dining, etc. Functional elements refer to the space functions that must be available to meet the needs of specific scenarios, such as office areas, rest areas, restaurants, etc. For example, for a user who often works at home, "working from home" is a typical scenario, and the corresponding functional elements include workbenches, storage spaces, lighting equipment, etc.

[0062] In this step, the system first creates multiple life scenarios based on the information in the user portrait using scenario generation algorithms. These algorithms use rule-based systems or machine learning models to infer possible daily activities based on information such as the user's occupation, hobbies, and family structure. For example, for a family with children, scenarios such as "family dinner", "children playing", and "study tutoring" are generated, and the system assigns corresponding functional elements to each scenario. This process can be achieved through a predefined scenario-function mapping table, or it can be dynamically generated using a more complex association rule mining algorithm. In the end, the system generates a list of scenarios, each with a corresponding set of functional elements.

[0063] S203: Analyze the space requirements for each group of functional elements to determine the minimum space size and shape requirements required to realize each functional element.

[0064] Space requirement analysis refers to the quantitative and qualitative assessment of the space required for each functional element. The minimum space size refers to the minimum area and height required to achieve the function. The form requirement refers to the geometric characteristics of the space, such as aspect ratio, openness, connectivity, etc. For example, for a work area, the minimum space size is 2 square meters, and the form requirements include window side, square layout, etc.

[0065] In this step, the system first builds a space requirement model for each functional element. This model contains the basic space requirements of the functional element, such as minimum area, minimum height, ideal shape, etc. This information can come from architectural design standards, ergonomic data, or historical design cases. The system uses spatial analysis algorithms, such as space syntax or space syntax analysis, to evaluate the space requirements of each functional element. These algorithms take into account factors such as the relationship between functions, user activity patterns, and accessibility of space. For example, for an open kitchen, the system must consider not only the minimum space required for cooking, but also the relationship with the adjacent dining area.

[0066] S204. Design a plurality of space modules according to the minimum space size and the form requirement, wherein the space modules include fixed function modules and variable function modules.

[0067] In this step, the system first reads the minimum space size and form requirements of each functional element determined in the previous step, and uses parametric design algorithms to generate space modules that meet these requirements. These algorithms adjust predefined module templates to meet specific space requirements. For example, for a workspace module, the length and width of the module are adjusted according to the minimum area requirements, while considering form requirements such as window positions. The space modules generated by the system are divided into two categories: fixed function modules and variable function modules. Fixed function modules are used for areas with relatively fixed positions and functions, such as kitchens and bathrooms. The design of these modules will take into account factors such as pipeline layout and equipment installation. Variable function modules are used for areas that require flexible changes, such as living rooms and bedrooms. The design of these modules will include elements such as movable partitions and multifunctional furniture to achieve spatial variability. The system will generate multiple different module design schemes for each functional element to provide more combination possibilities.

[0068] S205. Based on a preset space combination rule library, a plurality of the space modules are combined to obtain a module space combination scheme. The preset space combination rule library includes module connection rules, module orientation rules, proximity rules and module variability rules.

[0069] In this step, the system first loads the preset space combination rule library. This rule library contains four main types of rules: module connection rules, module orientation rules, proximity rules, and module variability rules. Module connection rules define how different modules are physically connected, such as which modules can be directly adjacent and which require transition spaces. Module orientation rules specify the ideal orientation of a specific module, such as bedrooms should avoid western exposure. Proximity rules define the ideal distance and relationship between different functional modules, such as the kitchen should be close to the dining room. Module variability rules specify the change mode and range of variable functional modules. The system uses these rules as constraints to combine space modules through combinatorial optimization algorithms (such as genetic algorithms or simulated annealing algorithms). The objective functions of the algorithm include maximizing space utilization, minimizing the distance of moving lines, etc. During the combination process, the system will continuously check whether the generated solution meets all the rules. If not, it will be adjusted or regenerated. In addition, the system will also consider user preferences and design requirements and adjust the weights of certain rules. For example, if the user pays special attention to privacy, the system will increase the weight of separating the bedroom from the public area. Ultimately, the system will generate multiple module space combination solutions that comply with the rules and select the best solution based on the comprehensive score.

[0070] S206, dividing the fixed function modules in the module space combination scheme into fixed function areas, dividing the variable function modules into variable function areas, and generating an initial residential three-dimensional model based on the fixed function areas and the variable function areas.

[0071] In this step, the system first divides the optimal module space combination scheme generated in the previous step into regions. The system marks the fixed function modules (such as kitchen, bathroom, etc.) in the scheme as fixed function areas. At the same time, the system marks the variable function modules (such as living room, bedroom, etc.) as variable function areas. The system uses a 3D modeling algorithm to convert the divided areas into the initial residential 3D model. This process includes several steps: First, the system generates the corresponding geometry in 3D space according to the size and position information of each module. The system adds basic architectural elements such as walls, floors, and ceilings to ensure the structural integrity of the model. For fixed function areas, the system directly places preset fixed facilities such as kitchen equipment and sanitary ware. For variable function areas, the system reserves variable space and adds placeholders for movable partitions or multifunctional furniture. The system also considers building specifications, such as the minimum width of stairs and corridors, to ensure that the model meets basic building requirements. The system renders the model preliminarily and adds material and lighting information to more intuitively display the design effect.

[0072] S207: Obtain an initial residential three-dimensional model of the target designed residence, wherein the initial residential three-dimensional model includes fixed functional areas and variable functional areas.

[0073] It can be understood that this step is similar to step S101 and will not be described in detail here.

[0074] S208: In the fixed functional area, identify key functional points and equipment locations in the fixed functional area.

[0075] In this step, the system first reads the 3D model data of the fixed functional area, including the geometric size and shape information of the space. The system selects the corresponding function point identification rules according to the pre-defined function types (such as kitchen, bathroom, etc.). For example, for the kitchen area, the system will look for suitable locations for the sink, stove and refrigerator; for the bathroom, the system will determine the potential locations of the toilet, shower area and sink. The system determines these key functional points by analyzing the geometric features of the space, such as the continuity of the wall, the location of the corners, the location of the windows and doors, etc. At the same time, the system will consider the pipeline layout, such as the location of the water pipes and drains, to determine the possible location of the equipment that needs water. The system also checks the distribution of power sockets to determine the potential placement points of electrical appliances. Finally, the system generates a coordinate list containing each identified key functional point and device location, and each point in this list has its specific functional attributes and spatial coordinates.

[0076] S208. Convert the minimum spacing requirement in the preset building code into a constraint condition between devices, set the structural requirement as a fixed boundary, and determine the movable range of the key functional point and the device position.

[0077] In this step, the system first extracts specific minimum spacing requirements from the building code database. For example, the minimum distance between the stove and the sink in the kitchen is set to 600mm, and the minimum distance between the center of the toilet and the side wall is 450mm. The system converts these specific numerical requirements into mathematical relationships in the spatial coordinate system. For example, if the coordinates of the sink are (x1, y1) and the coordinates of the stove are (x2, y2), then the system generates the following constraint: √((x2-x1)^2+(y2-y1)^2)≥600. At the same time, the system identifies fixed structural elements in the 3D model, such as walls, doors and windows, and uses their coordinates as fixed boundaries for the layout. For example, if the coordinate range of the wall is x∈[0, 3000], y∈[0, 4000], then the x and y coordinates of all equipment must be within this range. Based on these specific constraints and boundary restrictions, the system calculates the movable range of each functional point and equipment. This range is represented as a series of coordinate intervals, for example, the movable range of the sink is x∈[500, 2500], y∈[1000, 3000].

[0078] S209: Generate a plurality of fixed function pre-selected positions based on the constraint condition, the fixed boundary and the movable range.

[0079] In this step, a grid system is first set up. The size of the grid is 100mmx100mm. The system samples the position in units of this grid within the movable range of each device. For each sampling point, the system checks whether it meets all the constraints. For example, for a possible position of the sink (1500, 2000), the system will check whether it is within the movable range, whether it meets the minimum spacing requirements with other devices, whether it does not conflict with fixed structures, etc. The system will calculate a score for each combination of positions that meet the conditions. This score considers factors such as: the actual distance between devices (the closer to the minimum requirement, the better), the distance from the fixed structure (reserving appropriate operating space), the uniformity of the distribution of devices, etc. The score is calculated using a weighted summation method, for example: Score=w1*(actual distance / minimum required distance)+w2*(distance from the fixed structure / ideal distance)+w3*(distribution uniformity index), where w1, w2, w3 are the weights of different factors. The system finally selects several combinations with the highest scores as pre-selected solutions, each of which contains the specific coordinate positions of all devices and function points.

[0080] S210, calculating the space utilization rate and assembly rate of each fixed function pre-selected position, wherein the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules used.

[0081] In this step, the system first calculates the space utilization rate for each fixed-function pre-selected location. The system accurately measures the effective use area in each pre-selected location plan, which includes the area occupied by all functional areas and equipment, as well as the necessary operating space. For example, in a kitchen layout, the effective use area includes the area of ​​equipment such as the stove, sink, refrigerator, and the work area around them. The system also calculates the total area, which is the area of ​​the entire fixed-function area. The space utilization rate is obtained by dividing the effective use area by the total area, and the result is expressed as a percentage. For example, if the effective use area is 8 square meters and the total area is 10 square meters, the space utilization rate is 80%.

[0082] For the calculation of the modularity, the system identifies the number of standardized modules used in each pre-selected location. Standardized modules include prefabricated cabinet units, standard-sized bathroom fixtures, etc. The system divides the number of standardized modules used by the total number of modules to calculate the modularity. For example, if there are 10 modules in a kitchen solution, 8 of which are standardized modules, the modularity is 80%.

[0083] S211. Based on the preset key moving line path, measure the actual length of the preset key moving line path in each of the fixed function pre-selected positions, compare the actual length of the preset key moving line path with the preset ideal length, and obtain the moving line efficiency ratio corresponding to each of the fixed function pre-selected positions.

[0084] In this step, the system first reads the preset key moving line path information. These paths are usually pre-defined based on ergonomics and frequency of use, such as the "work triangle" path in the kitchen (refrigerator-sink-stove), or the "washing path" in the bathroom (door-toilet-sink). For each fixed function pre-selected position, the system simulates these key moving line paths in three-dimensional space and calculates the actual length. For example, in the kitchen layout, the system calculates the actual walking distance from the refrigerator to the sink and then to the stove.

[0085] When calculating the actual length, the system takes into account obstacles and necessary detours. For example, if there is an island between the refrigerator and the sink, the system will calculate the actual path length around the island instead of a simple straight-line distance. The system also takes into account the opening direction of the door to ensure that the movement line is not blocked by the open door.

[0086] The system compares the calculated actual length with the preset ideal length. The preset ideal length is usually the optimal value based on ergonomic research and usage efficiency analysis. The calculation formula for the moving line efficiency ratio is: efficiency ratio = ideal length / actual length. For example, if the ideal length of the kitchen "working triangle" is 4 meters, and the actual length of a pre-selected position is 5 meters, then the moving line efficiency ratio of this pre-selected position is 0.8 or 80%.

[0087] The system will calculate the efficiency ratio of all preset key traffic lines for each pre-selected location, and calculate a weighted average as the overall traffic line efficiency index of the pre-selected location.

[0088] S212, allocating weight coefficients to the space utilization, the assembly rate and the moving line efficiency, and calculating a comprehensive performance index based on the weight coefficients, the space utilization, the assembly rate and the moving line efficiency.

[0089] In this step, the system first assigns weight coefficients to space utilization, assembly rate, and movement efficiency. These weight coefficients reflect the relative importance of different factors in the overall evaluation. The weights are assigned based on the specific needs of the project, design concepts, or user preferences. For example, in projects that emphasize space efficiency, space utilization is assigned a higher weight such as 0.5; while in projects that focus on construction efficiency, assembly rate is assigned a higher weight such as 0.4. The weight of movement efficiency varies in different types of spaces, such as higher in kitchen design and lower in living room design. Assume that the weights are assigned as follows: space utilization weight w1=0.4, assembly rate weight w2=0.3, and movement efficiency weight w3=0.3. The system then uses these weights and the indicators calculated in the previous steps to calculate the comprehensive performance index for each fixed function pre-selected position. The calculation formula is: comprehensive performance index = w1*space utilization + w2*assembly rate + w3*moving line efficiency ratio. For example, for a specific pre-selected location, if the space utilization rate is 85%, the assembly rate is 70%, and the moving line efficiency ratio is 90%, then its comprehensive performance index will be: 0.4*85+0.3*70+0.3*90=82. The system calculates this comprehensive performance index for each pre-selected location and sorts all pre-selected locations according to this index.

[0090] S213. The fixed function pre-selected position with the highest comprehensive performance index is used as the fixed function area position distribution.

[0091] In this key step, the system first sorts the comprehensive performance indicators of all previously calculated fixed function pre-selected locations. This sorting process is based on the comprehensive performance indicators calculated in the previous step, which have taken into account multiple important factors such as space utilization, assembly rate and traffic flow efficiency. After the sorting is completed, the system will select the pre-selected location with the highest comprehensive performance index as the final fixed function area location distribution plan. This selection process is not just a simple selection of the highest score. The system will also conduct a series of verifications and checks. The system will once again confirm whether the highest score plan meets all design constraints and specification requirements. For example, check whether the spacing between all equipment and function points meets the minimum spacing requirements, and whether any equipment or function points conflict with fixed structures (such as walls and columns). Secondly, the system will generate a detailed 3D model of this optimal solution, including the precise location and size of all equipment and function points in the fixed function area. This 3D model not only includes the plane layout, but also takes into account the height information to ensure that there is no conflict in the vertical direction. For example, in the kitchen design, the system will ensure that there is enough operating space between the upper and lower cabinets, and the height of the wall cabinets is suitable for most users. In addition, the system will generate a visual representation of this optimal solution, including floor plans, elevations and 3D renderings.

[0092] The following is a more detailed description of the process of the method provided by this implementation. Figure 3 , is another flow chart of the method for generating a variable space residential design solution in an embodiment of the present application.

[0093] S301. Import the initial residential three-dimensional model into the computational simulation tool. For each variable functional position, simulate the spatial change process of the variable functional position under different life scenarios to obtain the operation time and operation complexity required for converting one function to another. Each life scenario corresponds to each functional layout of all the variable functional positions.

[0094] The system first imports the 3D model of the initial residence into a dedicated computational simulation tool. This tool can simulate the movement, deformation and interaction of objects in space. For each variable function pre-selected position generated in S301, the system simulates its spatial change process in different life scenarios. These life scenarios include: daily living, work and office, leisure and entertainment, sleep, dining, etc. During the simulation process, the system will consider the specific movement path, rotation angle, folding process, etc. of furniture and equipment. For example, for a space that can be converted from a living room to a bedroom, the system will simulate a series of actions such as how the sofa unfolds into a bed, how the coffee table folds and stores, and how the curtains are closed. During the simulation process, the system will record the time required for each transformation step, which is calculated based on the preset standard operation time and space size. At the same time, the system will also evaluate the complexity of each transformation step, which takes into account factors such as the number of items to be moved, the moving distance, and whether special tools are required. For example, simply pulling out a folding bed is assigned a lower complexity, while large furniture movements that require the collaboration of multiple people are assigned a higher complexity. The system creates a transition matrix for each variable function position, recording all transition paths from one function to another and their corresponding operation time and complexity.

[0095] S302: Calculate the space conversion efficiency according to the operation time and the operation complexity.

[0096] In this step, the system calculates the spatial conversion efficiency of each variable functional position based on the operation time and operation complexity data obtained in the previous step. The calculation process uses a comprehensive scoring formula that takes into account multiple factors. The system assigns a basic score to each functional conversion, which reflects the importance and frequency of the conversion in daily life. For example, the conversion from the living room to the bedroom receives a high basic score because it is a common and important conversion. The system adjusts the basic score based on the operation time. The shorter the operation time, the higher the score. A nonlinear calculation method, such as an exponential decay function, is used here to better reflect the impact of time on efficiency. The system will make further adjustments based on the complexity of the operation. The lower the complexity, the higher the score. The impact of complexity is reflected by a weighting coefficient, and different types of complexity (such as required manpower, tools, etc.) have different weights. The system also considers the reliability and stability of the conversion. For example, a conversion mechanism that requires precise adjustment will reduce the score due to its potential risk of failure. In addition, the system evaluates the functional integrity of the converted space to ensure that the converted space can fully meet its intended function. The system calculates a comprehensive spatial conversion efficiency score. This score not only reflects the efficiency of a single conversion, but also takes into account the cumulative effect of multiple different conversions over a day or week.

[0097] S303. Based on the spatial change process, the functional fitness of each variable functional position under each functional layout is evaluated. The functional fitness is calculated by space utilization and user efficiency. The space utilization is obtained by evaluating the spatial changes in the simulation, and the user efficiency is obtained by evaluating the time it takes for users to complete specific tasks in the simulation.

[0098] In this step, the system evaluates the functional fitness of each functional layout for each variable functional position. Functional fitness is an indicator that measures the degree to which the spatial layout supports a specific function. It consists of two sub-indicators: space utilization and user efficiency. The system analyzes the spatial change simulation data to evaluate space utilization. It calculates the ratio of actual used space to total available space, considering three-dimensional space utilization. For example, in the layout of a living room to an office, the system evaluates whether the placement of office equipment and furniture effectively utilizes the available space, including walls, corners, and vertical space. The calculation of space utilization uses the following formula: Space utilization = functional use area / total available area. Secondly, the system evaluates user efficiency. It sets standard tasks related to specific functions, such as completing a day's workflow in an office layout. The system uses virtual character models to simulate users' movements and operations in the space and calculates the time required to complete these tasks. User efficiency is calculated by the following formula: User efficiency = standard task completion time / actual task completion time. The system combines space utilization and user efficiency to obtain a functional fitness score. The calculation formula is: Functional fitness = w1 * space utilization + w2 * user efficiency, where w1 and w2 are weight coefficients, reflecting the relative importance of the two sub-indicators. The system generates a functional fitness report for each functional layout of each variable functional location, including the overall score, sub-indicator score and specific evaluation data.

[0099] S304: Obtain a variability parameter value by weighted calculation according to the spatial conversion efficiency and the functional fitness.

[0100] In this step, the system combines the previously calculated spatial conversion efficiency and functional fitness, and obtains a comprehensive variability parameter value through weighted calculation. This parameter value is a key indicator for measuring the overall performance of variable functional locations. The calculation process first determines the weights of spatial conversion efficiency and functional fitness. These weights reflect the priority of the design goals and will be adjusted according to different user needs or project requirements. For example, for users who frequently need to change the use of space, spatial conversion efficiency is given a higher weight; while for users who pay more attention to the functional quality of space, functional fitness is given a higher weight. The system adopts a flexible weight allocation mechanism that allows the relative importance of the two indicators to be adjusted between 0 and 1. The system evaluates all functional layouts for each variable functional location. For each layout, the system calculates its weighted average score, which combines the spatial conversion efficiency of the layout (taking into account all possibilities of conversion to other layouts) and its functional fitness. The system calculates the average of these layout scores to obtain the overall variability parameter value of the variable functional location.

[0101] It is understandable that steps S301 to S304 may be executed after step S101 or after step S207, which is not limited here.

[0102] S305. Establish a spatial layout optimization model according to the spatial variability parameter values ​​of each variable functional position.

[0103] The system uses the spatial variability parameter values ​​of each variable function location calculated previously to build a comprehensive spatial layout optimization model. The goal of this model is to find the best variable function layout solution in the overall residential space. The system defines the optimization objective function, which is the weighted sum of the variability parameter values ​​of each variable function location, with the weights based on the area of ​​each location or the importance of the overall space. The optimization model also needs to consider a series of constraints, including building structural limitations (such as load-bearing walls, pipe locations), regulatory requirements (such as minimum aisle width, emergency evacuation routes), and user-specific needs (such as certain functions must be adjacent or separated). The system uses optimization techniques such as mixed integer linear programming (MILP) or genetic algorithms to solve this complex optimization problem. During the modeling process, the system treats each variable function location as a decision variable, whose possible values ​​include different functional configurations and location options. The goal of the model is to find the best combination of these variables to maximize the overall variability parameter value while satisfying all constraints. During the optimization process, the system considers the mutual influence between different variable function locations, for example, the function selection at one location affects the available options at adjacent locations. The system will also evaluate the performance of different layout options in terms of overall spatial flow, natural lighting, ventilation, etc. These factors will be included in the optimization model as additional evaluation indicators.

[0104] S306: setting an optimization objective function based on the spatial layout optimization model, wherein the optimization objective function includes preset constraints, and the preset constraints include a minimum area requirement for the variable functional position and a minimum spacing requirement between functional areas.

[0105] In this step, the system sets a comprehensive optimization objective function based on the previously established spatial layout optimization model. The core of this objective function is to maximize the variability parameter value of the overall space while satisfying a series of preset constraints. The objective function takes the following form: MaxZ=Σ(wi*Vi), where Vi represents the variability parameter value of the i-th variable functional position, and wi is the corresponding weight coefficient, reflecting the importance of the position in the overall layout. The weight is determined based on the size of the area or the frequency of use of the position. At the same time, the objective function contains key preset constraints. The first is the minimum area requirement, for example, for the bedroom function, an area of ​​at least 10 square meters is required; for the living room function, at least 15 square meters is required. These constraints can be expressed as: Ai≥Amin,i, where Ai is the actual area of ​​the i-th functional area, and Amin,i is the minimum area requirement of the function. The second is the minimum spacing requirement between functional areas, for example, the kitchen and the living room are required to maintain a distance of at least 1.5 meters to ensure sufficient activity space. This type of constraint can be expressed as: Dij ≥ Dmin, ij, where Dij is the distance between the i-th and j-th functional areas, and Dmin, ij is the minimum distance required between them. In addition, the system considers other constraints, such as building structure restrictions (such as the location of load-bearing walls), equipment layout requirements (such as the location of pipelines and electrical lines), etc.

[0106] S307: Use the optimization algorithm to iteratively optimize the layout of the variable functional area to obtain a new layout solution.

[0107] In this step, the system applies advanced optimization algorithms to iteratively optimize the layout of the variable functional areas to obtain new and better layout solutions. Considering the complexity and nonlinear characteristics of the problem, the system uses heuristic algorithms such as genetic algorithms (GA) or particle swarm optimization algorithms (PSO). Taking the genetic algorithm as an example, the system first generates a set of initial layout solutions, each of which is encoded as a "chromosome" containing the location, size and function information of each variable functional position. The algorithm improves these solutions through multiple iterations. In each iteration, the algorithm performs the following operations: selection (selecting solutions with better performance), crossover (combining the features of different solutions) and mutation (randomly changing certain features to increase diversity). Each newly generated solution is evaluated for its fitness, that is, its variability parameter value is calculated by optimizing the objective function. In this process, the system strictly abides by the constraints set in S307 to ensure that the generated solutions are feasible. For example, if a newly generated solution violates the minimum area requirement, the system will adjust it or directly eliminate it. The iterative process will continue until the preset termination condition is reached, such as reaching the maximum number of iterations or there is no significant improvement after multiple consecutive iterations. In order to improve optimization efficiency, the system uses parallel computing technology to evaluate multiple solutions simultaneously.

[0108] S308 , performing spatial variability simulation on each of the new layout solutions, and calculating a variability parameter value of each of the new layout solutions.

[0109] In this step, the system performs a detailed spatial variability simulation on each new layout scheme generated in S308 to calculate its specific variability parameter value. This process is a verification and refinement of the previous optimization results. For each new layout scheme, the system first builds its detailed three-dimensional model, including the precise geometric information and functional attributes of all variable functional positions, and the system simulates the use of this layout in different life scenarios. For example, the system simulates the process of switching from daytime work mode to nighttime rest mode, or from daily life mode to family gathering mode. In each conversion scenario, the system calculates the efficiency of spatial conversion, which includes the time required for conversion, the complexity of operation, and possible interference factors during the conversion process. At the same time, the system also evaluates the space utilization and user efficiency in each functional mode. The calculation of space utilization takes into account the ratio of the actual use area of ​​the functional area to the total available area, as well as the utilization of vertical space. User efficiency simulates the time and difficulty of users completing specific tasks in space through virtual character models. The system combines these factors and uses predefined formulas to calculate the overall variability parameter value of each layout scheme. This parameter value reflects the comprehensive performance of the layout scheme in terms of flexibility, efficiency and practicality. To ensure the accuracy and comprehensiveness of the evaluation, the system will conduct multiple simulations to consider different usage scenarios and user behavior patterns. In addition, the system also conducts sensitivity analysis to evaluate the impact of different factors on the variability parameter value. The system generates a detailed evaluation report for each new layout solution, including the overall variability parameter value, the scores of each sub-indicator, and specific simulation data and analysis results.

[0110] S309: Use the layout solution with the variability parameter value greater than the preset parameter threshold as the variable functional area position distribution.

[0111] The variability parameter value is a quantitative indicator after evaluating the spatial variability capability of each candidate layout scheme generated for the variable functional area. This indicator is obtained by digitally simulating different layout schemes, recording the flexibility of spatial transformation, the difficulty of conversion, and the efficiency of use under various functional layouts, etc., and then comprehensively calculated. The preset parameter threshold is the minimum acceptable level of spatial variability of the variable functional area, which is pre-set by the designer according to actual needs when the system is initialized. The layout schemes with variability parameter values ​​higher than the threshold are retained to ensure that the obtained position distribution of the variable functional area can meet the basic requirements of flexible transformation. This operation is equivalent to a screening process, which deletes layout schemes with weaker variability capabilities and only retains layout schemes with variability capabilities stronger than the standard as the final spatial position distribution results of the variable functional area.

[0112] It is understandable that steps S305 to S309 may be executed after step S104 or after step S304, which is not limited here.

[0113] S310: Based on the position distribution of the fixed functional area, a preset fixed module building is placed in the fixed functional area, and based on the position distribution of the variable functional area, a preset movable module is placed in the variable functional area to generate a three-dimensional residential design model.

[0114] After obtaining the location distribution of fixed function areas and variable function areas, it is necessary to use standardized functional building modules to construct three-dimensional scenes according to the spatial layout requirements of these two areas. The location distribution of fixed function areas gives the final layout plan of the space in the area, reflecting the specific layout of non-variable space; the preset fixed module building refers to standardized building components that match fixed functions, such as bathroom and kitchen decoration units. The location distribution of variable function areas gives the final layout plan of the space in the area, reflecting the specific layout of adjustable space; the preset movable module refers to flexible and adjustable building components that match variable functions, such as foldable furniture, movable partitions, etc. This step requires the optimization of the final layout of the functional area to be associated with the corresponding standardized building modules, and three-dimensional modeling is performed according to the spatial layout requirements to finally generate a complete residential three-dimensional scene. In this process, it is necessary to ensure the logical correlation and rationality between the functional modules, such as the connection of details such as door and window positions and pipeline layout. The final output three-dimensional scene can intuitively reflect the functional division and layout design of the space.

[0115] S311, sending the residential design three-dimensional model to a preset client for display.

[0116] The preset client refers to the target device or platform that is designated to receive the generated design results after the 3D model design is completed. The client needs to have the ability to parse and display 3D model files. The purpose of sending 3D models is to allow designers or users to browse interactive 3D scenes on the client and to visually check and evaluate the design effects. Specifically, the generated 3D model file can be sent to the client in a standardized format (such as FBX), and then the client loads and presents the model through the included 3D browser software.

[0117] The following describes the generation system of the variable space residential design scheme in the embodiment of the present invention from the perspective of hardware processing. Figure 4 , which is a schematic diagram of a physical device structure of a system for generating a variable space residential design solution in an embodiment of the present application.

[0118] It should be noted that Figure 4The structure of the variable space residential design scheme generation system shown is only an example and should not bring any limitation to the function and scope of use of the embodiment of the present invention.

[0119] like Figure 4 As shown, the system for generating a variable space residential design solution includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In RAM403, various programs and data required for system operation are also stored. CPU401, ROM402 and RAM403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0120] The following components are connected to the I / O interface 405: an input section 306 including an audio input device, a button switch, etc.; an output section 407 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0121] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the present invention are performed.

[0122] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0123] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0124] Specifically, the system for generating a variable space residential design scheme in this embodiment includes a processor and a memory, and a computer program is stored in the memory. When the computer program is executed by the processor, the method for generating a variable space residential design scheme provided in the above embodiment is implemented.

[0125] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the variable space residential design scheme generation system described in the above embodiment; or may exist independently without being assembled into the variable space residential design scheme generation system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the variable space residential design scheme generation system, the variable space residential design scheme generation system implements the variable space residential design scheme generation method provided in the above embodiment.

[0126] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0127] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0128] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for generating a variable space residential design scheme, characterized in that: A system for generating a design scheme for a variable-space residential building, the method comprising: Acquire an initial residential three-dimensional model of a target designed residence, wherein the initial residential three-dimensional model includes a fixed functional area and a variable functional area; In the fixed function area, based on preset building specifications and structural requirements, multiple fixed function pre-selected positions are generated, and the comprehensive performance index corresponding to each fixed function pre-selected position is calculated, and the fixed function pre-selected position with the highest comprehensive performance index is used as the fixed function area position distribution, and the comprehensive performance index is obtained by weighted calculation of space utilization rate, assembly rate and moving line efficiency ratio; In the variable function area, based on user demand parameters, spatial variability rules and the position distribution of the fixed function area, a plurality of variable function pre-selected positions are generated; Using a computational simulation tool, based on the initial residential three-dimensional model, a spatial variability simulation is performed on each variable functional position to obtain a spatial variability parameter value corresponding to each variable functional position, wherein the spatial variability parameter value is obtained by weighted calculation of spatial conversion efficiency and functional fitness; According to the spatial variability parameter value, the initial layout of the variable functional area is optimized to obtain the position distribution of the variable functional area; Based on the position distribution of the fixed functional areas, the preset fixed module buildings are placed in the fixed functional areas, and based on the position distribution of the variable functional areas, the preset movable modules are placed in the variable functional areas to generate a three-dimensional residential design model.

2. The method according to claim 1, characterized in that: Before the step of obtaining an initial residential three-dimensional model of the target designed residential building, wherein the initial residential three-dimensional model includes fixed functional areas and variable functional areas, the method further includes: Receiving personal information and design requirements input by a user, and building a user portrait based on the personal information and the design requirements, the user portrait including family structure, living habits and space preferences; Generate multiple typical life scenarios based on the user portrait, each of the life scenarios corresponds to a set of functional elements; Conducting a space requirement analysis for each group of functional elements to determine the minimum space size and form requirements required to realize each functional element; Designing a plurality of space modules according to the minimum space size and the form requirements, wherein the space modules include fixed function modules and variable function modules; Based on a preset space combination rule library, a plurality of the space modules are combined to obtain a module space combination scheme, wherein the preset space combination rule library includes module connection rules, module orientation rules, proximity rules and module variability rules; The fixed function modules in the module space combination scheme are divided into fixed function areas, and the variable function modules are divided into variable function areas, and an initial residential three-dimensional model is generated based on the fixed function areas and the variable function areas.

3. The method according to claim 1 or 2, characterized in that: The step of generating a plurality of fixed function pre-selected positions within the fixed function area based on preset building specifications and structural requirements specifically includes: Within the fixed functional area, identifying key functional points and equipment locations within the fixed functional area; Based on the minimum spacing requirements in the preset building code, the minimum spacing requirements are converted into constraints between devices, and the structural requirements are set as fixed boundaries to determine the movable range of the key functional points and the equipment positions; A plurality of fixed function pre-selected positions are generated based on the constraint conditions, the fixed boundary and the movable range.

4. The method according to claim 1, characterized in that: The step of calculating the comprehensive performance index corresponding to each fixed function pre-selected position, taking the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution, wherein the comprehensive performance index is obtained by weighted calculation of the space utilization rate and the assembly rate, specifically includes: Calculating the space utilization rate and assembly rate of each of the fixed function pre-selected positions, wherein the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules adopted; Based on the preset key moving line path, measuring the actual length of the preset key moving line path in each of the fixed function pre-selected positions, comparing the actual length of the preset key moving line path with the preset ideal length, and obtaining the moving line efficiency ratio corresponding to each of the fixed function pre-selected positions; Assigning weight coefficients to the space utilization rate, the assembly rate, and the moving line efficiency, and calculating a comprehensive performance index based on the weight coefficients, the space utilization rate, the assembly rate, and the moving line efficiency; The fixed function pre-selected position with the highest comprehensive performance index is used as the fixed function area position distribution.

5. The method according to claim 1, characterized in that The use of the computational simulation tool to simulate the spatial variability of each variable functional position based on the initial residential three-dimensional model to obtain the spatial variability parameter value corresponding to each variable functional position specifically includes: Importing the initial residential three-dimensional model into a computational simulation tool, for each of the variable functional positions, simulating the spatial change process of the variable functional position in different life scenarios, and obtaining the operation time and operation complexity required for converting one function to another, wherein each of the life scenarios corresponds to each functional layout of all the variable functional positions; Calculating the spatial conversion efficiency according to the operation time and the operation complexity; Based on the spatial change process, the functional fitness of each variable functional position under each functional layout is evaluated, wherein the functional fitness is calculated by space utilization and user efficiency, wherein the space utilization is obtained by evaluating the spatial change in the simulation, and the user efficiency is obtained by evaluating the time it takes for the user to complete a specific task in the simulation; The variability parameter value is obtained by weighted calculation based on the spatial conversion efficiency and the functional fitness.

6. The method according to claim 1, characterized in that The step of optimizing the initial layout of the variable functional area according to the spatial variability parameter value to obtain the position distribution of the variable functional area specifically includes: According to the spatial variability parameter values ​​of each variable functional position, a spatial layout optimization model is established; An optimization objective function is set based on the spatial layout optimization model, wherein the optimization objective function includes preset constraints, and the preset constraints include a minimum area requirement for the variable functional position and a minimum spacing requirement between functional areas; Iteratively optimize the layout of the variable functional area using the optimization algorithm to obtain a new layout solution; Performing spatial variability simulation on each of the new layout schemes, and calculating a variability parameter value of each of the new layout schemes; The layout scheme whose variability parameter value is greater than a preset parameter threshold is used as the variable functional area position distribution.

7. The method according to claim 6, characterized in that After the step of placing a preset fixed module building into the fixed functional area based on the position distribution of the fixed functional area, and placing a preset movable module into the variable functional area based on the position distribution of the variable functional area, and generating a three-dimensional residential design model, the method further includes: The residential design three-dimensional model is sent to a preset client for display.

8. A system for generating a variable space residential design scheme, characterized in that: The system for generating the variable space residential design solution includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the system for generating the variable space residential design solution to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a system for generating a variable-space residential design solution, the system for generating a variable-space residential design solution executes the method as described in any one of claims 1-7.

10. A computer program product, characterized in that When the computer program product is run on a system for generating a variable-space residential design solution, the system for generating a variable-space residential design solution executes the method as described in any one of claims 1-7.

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