Decoration construction scheme optimization system based on artificial intelligence

Abstract

The invention relates to the technical field of decoration construction, and discloses an artificial intelligence-based decoration construction scheme optimization system, which comprises a user side, a program side and a construction side, the program end comprises a data collection module, a data preprocessing module, a decoration scheme calibration module, a decoration scheme optimization module and a construction scheme selection module; through arrangement of a decoration scheme calibration module, a decoration scheme optimization module and a construction scheme selection module, a decoration scheme conforming to a user objective function is marked as a calibration decoration scheme by setting the user objective function, the spatial layout is optimized in combination with a spatial simulation technology, and then based on the overall decoration scheme, the construction efficiency is improved. Obtaining a corresponding construction scheme and selecting an optimal construction scheme; on the premise that the decoration cost requirement is met, the space layout of the decoration scheme is optimized, so that the decoration scheme obtains the maximum space utilization rate under different house space basic conditions, and reasonable utilization of the space is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of decoration construction, and more specifically to a decoration construction scheme optimization system based on artificial intelligence. Background Art

[0002] Decoration construction project refers to the design, construction, decoration and renovation of the interior and exterior decoration of a building after the completion of the construction project. The optimization of the construction plan is a key factor in improving construction efficiency, reducing costs and ensuring construction quality. The decoration construction plan must also meet the user's personal preferences and needs, not just consider the cost.

[0003] A public document with publication number CN111047339B discloses a method, device and system for processing house decoration information, the system comprising: a first client, used to provide a communication medium for a house decoration plan associated with a first user identifier, the house decoration plan comprising a 3D house model created according to a specified apartment type, and a 3D commodity object model within the 3D house model; a second client, used to obtain the house decoration plan associated with the first user identifier through a communication medium, obtain the house decoration plan after editing the house decoration plan associated with the first user identifier, and provide it to the first client; multi-role collaborative optimization of the house decoration plan can be achieved, which is conducive to helping the first user obtain a better house decoration plan.

[0004] However, relying solely on users to optimize the construction plan by themselves inevitably lacks a certain degree of professionalism. It is difficult to ensure the rational use of space in the layout of the decoration construction space, and there is a phenomenon of space redundancy and waste. At the same time, in the traditional decoration construction process, the optimization method of the construction plan usually relies mainly on manual experience and historical data, which is difficult to adapt to the complex and changeable construction environment and the actual needs of different users, resulting in low construction efficiency and serious waste of resources. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a decoration construction plan optimization system based on artificial intelligence to solve the problems existing in the above-mentioned background technology.

[0006] The present invention provides the following technical solutions: an artificial intelligence-based decoration construction plan optimization system, comprising a user end, a program end, and a construction end;

[0007] The user terminal is used for the user to input information, perform user terminal operations and synchronously display data for the user;

[0008] The program end is used to optimize the decoration construction plan, including:

[0009] The data collection module is used to collect user data and decoration data and transmit them to the data preprocessing module;

[0010] The data preprocessing module is used to preprocess the user data and the decoration data to obtain the user data and the decoration data that can be directly used;

[0011] The decoration scheme calibration module is used to receive the data preprocessed by the data preprocessing module and obtain the calibration decoration scheme based on the user objective function;

[0012] The decoration scheme optimization module is used to receive the decoration scheme calibrated by the decoration scheme calibration module, optimize the space layout by combining the space simulation technology, and obtain the final overall decoration scheme;

[0013] The construction plan selection module obtains the corresponding construction plan based on the overall decoration plan and selects the best construction plan to form the final decoration construction plan and transmit it to the user end and the construction end;

[0014] The construction end is used to display the final decoration construction plan and carry out construction based on it, and at the same time, the construction progress is updated in real time at the construction end.

[0015] Preferably, the user information input by the user terminal includes user decoration area information and the style, brand, color, material, size and shape of the selected furniture, tiles, lamps and accessories. The user decoration area information is the area information where the user needs to carry out decoration construction, specifically the area location, area and apartment type; the user terminal obtains a three-dimensional map of the area to be decorated based on the user decoration area information for display.

[0016] Preferably, the data collection module is used to collect user data and decoration data, the user data is information input by a user at the user end, and the decoration data is data corresponding to the information input by the user at the user end;

[0017] The decoration scheme calibration module marks the decoration scheme that meets the user objective function as a calibrated decoration scheme by setting the user objective function;

[0018] If the current decoration scheme does not meet the user's objective function, the result will be fed back to the user end, and the user will choose whether to modify the current decoration scheme on the user end. If not, the current decoration scheme will be transmitted to the decoration scheme optimization module for optimization. If modified, the modified decoration scheme will be transmitted back to the data collection module as the new current decoration scheme, and the corresponding decoration data will be recollected. The decoration scheme calibration module will again determine whether it meets the user's objective function. If it does, the current decoration scheme will be directly marked as the calibrated decoration scheme and transmitted to the decoration scheme optimization module for optimization.

[0019] Preferably, the expression of the user objective function is expressed as follows: MB = COS max , where MB is the objective function value, COS max The maximum decoration cost acceptable to users;

[0020] The decoration scheme calibration module estimates the total cost of the current decoration scheme through the acquired decoration data to obtain COS g , if COS g >MB, the current decoration scheme does not meet the user's objective function, and the result is fed back to the user end; if COS g ≤MB, the current decoration scheme meets the user objective function, and the current decoration scheme is directly marked as the calibration decoration scheme.

[0021] Preferably, the decoration scheme optimization module optimizes the space layout by combining space simulation technology, including the following steps:

[0022] Step S01: Obtain multiple spatial layout graphs, encode them, encode them as O, O is the chromosome, obtain the chromosome, and construct the initial population A = {O1, O2, O3, ..., O k};

[0023] Step S02: Determine the fitness function;

[0024] Step S03: Perform natural selection on chromosomes in the population;

[0025] Step S04: performing crossover recombination on chromosomes in the population;

[0026] Step S05: mutating the chromosomes in the population;

[0027] Step S06: Obtain a new population, preset the population generation number to be L, the fitness threshold to be Q, L is an integer greater than 0, and Q is a real number greater than 0; loop from step S03 to step S05 until the generation number corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold Q, the loop ends, and obtain the spatial layout diagram corresponding to the chromosome with the maximum fitness in the new population, which is the optimal spatial layout;

[0028] Combine the optimal space layout with the calibrated decoration plan to form the final overall decoration plan.

[0029] Preferably, the spatial layout diagram is obtained in the following manner:

[0030] The furniture, tiles, lamps and accessories selected by the user are placed in the three-dimensional display diagram, and the three-dimensional display diagram is placed in the spatial coordinate system. The entire three-dimensional display diagram is located in the first quadrant, and the boundary of the floor plan coincides with the boundary of the spatial coordinate system. The movable accessories among the selected furniture, tiles, lamps and accessories are marked as layout items, and the center point coordinates of the layout items are used as item coordinate points. The position of the item coordinate point can be adjusted, that is, the position of the layout items in the three-dimensional display diagram is moved to form a variety of different spatial layouts to form a spatial layout diagram, and digital labels 1 to N are set for the layout items, and corresponding labels Bij are set for the item coordinate point positions; wherein, i=1, 2, 3, ..., N; j=1, 2, 3, ..., M; M is the M coordinate positions of the layout items;

[0031] Each spatial layout diagram can be expressed as: KB j ={B1j,B2j,B3j,...,BNj}, where KB j It is the spatial layout diagram during the j-th move; when the j-th move occurs, if there are items in the layout that have not been moved, then Bij=Bi(j-1).

[0032] Preferably, the fitness function is expressed as: r =RM r , where f r is the fitness corresponding to the rth chromosome, RM r is the spatial layout merit ratio corresponding to the rth chromosome; r = 1, 2, 3, ..., k;

[0033] The natural selection is carried out by combining the elite method and the rotation method; the elite method produces F1 offspring chromosomes, and for a population with a capacity of k, the fitness corresponding to the k chromosomes is arranged from large to small, and each of the F1 chromosomes at the front produces a offspring chromosome; the rotation method produces F2 offspring chromosomes, that is, k chromosomes produce F2 offspring chromosomes according to the corresponding rotation probability; F1+F2=k, so as to keep the offspring population capacity k unchanged and the population generation increases;

[0034] The expression of the rotation probability is: Among them, r is the rotation probability corresponding to the rth chromosome.

[0035] Preferably, the calculation formula of the spatial layout merit ratio is expressed as: Among them, RM r is the spatial layout merit ratio of the spatial layout graph corresponding to the rth chromosome, LY r is the space utilization rate of the spatial layout graph corresponding to the rth chromosome, YD r is the spatial congestion rate of the spatial layout graph corresponding to the rth chromosome;

[0036] The space utilization rate is the average of the ratios of the actual use area of ​​each functional area to the total area, and the formula is:

[0037] Among them, GN c is the ratio of the actual use area of ​​the cth functional area to the total area, and C is the total number of functional areas;

[0038] The spatial congestion rate is the average of the sum of the congestion losses of each functional area, and the congestion loss is the ratio of the difference between the maximum number of people that each functional area can accommodate at the same time and the total number of family members to the total number of family members; the formula is:

[0039] Among them, X c is the maximum number of people that the cth functional area can accommodate at the same time, and JT is the total number of users’ families.

[0040] Preferably, the specific method for the construction scheme selection module to select the best construction scheme is:

[0041] Step S11: Initialize the population, define the size of the population and the optimal number of iterations λ; randomly generate an initial population ZQ, where each individual in the population ZQ represents a construction plan;

[0042] Step S12: define blooming function: ZF=μ1×f1(CB)+μ2×f2(TIME)+μ3×f3(WR); wherein ZF is blooming function, μ1 is cost weight, μ2 is time weight, and μ3 is pollution weight; f1(CB) is cost function, f2(TIME) is time function, and f3(WR) is pollution function;

[0043] Step S13: Calculate the value of the blooming function of each individual, record it as the blooming value, sort the current population ZQ based on the blooming value, select the H individuals with the highest blooming value as elite individuals, record the remaining individuals except the elite individuals as non-elite individuals, and for each non-elite individual, explode it with itself as the center to obtain a new exploded individual;

[0044] Step S14: Calculate the bloom values ​​of all new exploded individuals, retain H′ individuals with the highest bloom values, and mutate the individuals retained after the explosion to obtain mutated individuals;

[0045] Step S15: Merge the elite individuals, the individuals retained after the explosion, and the individuals after the mutation to form a new generation population ZQ′; repeat the iteration until the optimal number of iterations λ is reached to obtain the final population; select the individual with the highest bloom value from the final population as the best construction plan;

[0046] The final overall decoration plan obtained by the decoration plan optimization module is combined with the best construction plan to form the final decoration construction plan.

[0047] Preferably, the formulas of the cost function, time function and pollution function in the bloom function are respectively expressed as:

[0048]

[0049] Among them, COS sg is the total cost of the construction plan, T fin is the end time of the construction plan, T aga is the start time of the construction plan, out tan The carbon emissions of all decorative materials in the final overall decoration scheme;

[0050] The formula for performing the explosion in step S13 is:

[0051] BM=hf+a1×(H max -hf)×(1+a2×||hf-H max ||)×rd(Y,nB)+a3×(g′-hf); where BM is the bloom value of the new explosion individual, hf is the bloom value of the non-elite individual, and H max is the bloom value of the individual with the highest bloom value in the current population, rd(Y,nB) is a Y×nB standard normal distribution random matrix, g′ is the individual with the highest bloom value found so far; a1 and a2 are both explosion constants, a3 is the offset weight parameter, which controls the degree of deviation of the explosion individual to the global optimal solution; Y is the dimension of the individual, and nB is the number of new explosion individuals generated for each individual;

[0052] The formula for mutation in step S14 is:

[0053] Among them, V I is the bloom value of the individual after mutation, GS is a Gaussian distribution random number, fd is the variation amplitude, which is an adjustable parameter, and t is the variation control parameter, which adjusts the attenuation rate of the variation amplitude; I ZF is the bloom value of individual I retained after the explosion; avg is the average bloom value of the current population, max is the maximum bloom value of the current population, and min is the minimum bloom value of the current population.

[0054] Technical effects and advantages of the present invention:

[0055] The present invention is provided with a decoration scheme calibration module, a decoration scheme optimization module and a construction scheme selection module, which is conducive to setting a user objective function, marking the decoration scheme that meets the user objective function as a calibrated decoration scheme, combining with space simulation technology to optimize the space layout, and obtaining the final overall decoration scheme. Based on the overall decoration scheme, the corresponding construction scheme is obtained and the best construction scheme is selected to form a final decoration construction scheme; by setting the user objective function, the needs of different users for decoration costs can be obtained, and on the premise of meeting the decoration cost requirements, the most satisfactory decoration scheme for the user is obtained, and then the spatial layout of the decoration scheme is optimized, so that the decoration scheme can obtain the maximum space utilization rate under different basic conditions of the house space, ensuring the reasonable use of the space, and based on this, the fireworks optimization algorithm is used to obtain the best construction plan, and the characteristics of the fireworks optimization algorithm with strong evolutionary ability, fast search speed and strong optimization ability are utilized, and the construction plan cost, construction plan time and pollution conditions are comprehensively considered to optimize the construction plan and obtain the optimal solution, which can well cope with the complex and changeable construction environment and the actual needs of different users. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a structural diagram of the artificial intelligence-based decoration construction plan optimization system of the present invention.

[0057] Figure 2 It is a program end structure diagram of the present invention.

[0058] Figure 3 This is a flow chart of the decoration scheme calibration module of the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The artificial intelligence-based decoration construction solution optimization system involved in the present invention is not limited to the various structures recorded in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0060] like Figure 1 As shown, the present invention provides a decoration construction plan optimization system based on artificial intelligence, including a user end, a program end and a construction end;

[0061] The user terminal is used for the user to input information, perform user terminal operations and synchronously display data for the user;

[0062] The program end is used to optimize the decoration construction plan, including a data collection module, a data preprocessing module, a decoration plan calibration module, a decoration plan optimization module and a construction plan selection module; the data collection module is used to collect user data and decoration data, and transmit them to the data preprocessing module; the data preprocessing module is used to preprocess the user data and decoration data to obtain user data and decoration data that can be directly used; the decoration plan calibration module is used to receive the data preprocessed by the data preprocessing module, and obtain a calibrated decoration plan based on the user objective function; the decoration plan optimization module is used to receive the calibrated decoration plan of the decoration plan calibration module, optimize the space layout in combination with the space simulation technology, and obtain the final overall decoration plan; the construction plan selection module obtains the corresponding construction plan based on the overall decoration plan and selects the best construction plan to form a final decoration construction plan and transmit it to the user end and the construction end;

[0063] The construction end is used to display the final decoration construction plan and carry out construction based on it, and at the same time, the construction progress is updated in real time at the construction end.

[0064] In this embodiment, it should be specifically explained that the user information input by the user terminal includes but is not limited to the user decoration area information and the style, brand, color, material, size and shape of the selected furniture, tiles, lamps, accessories and other accessories, and the user decoration area information is the area information where the user needs to carry out decoration construction, specifically the area location, area and apartment type, etc.; the user terminal obtains a three-dimensional map of the area to be decorated based on the user decoration area information for display; for example, if the area information of the decoration construction is A community B building, the apartment type is three bedrooms and two living rooms, and the area is C, then the overall three-dimensional display map is formed by obtaining the corresponding apartment type map and performing an overall three-dimensional display of the area information content;

[0065] The user terminal provides relevant information for the user to choose. The user selects the corresponding option in the selection interface according to his or her own preferences, and the selected option is displayed on the overall three-dimensional display map at the same time. The selected furniture, tiles, lamps, accessories and other accessories can be comprehensively displayed on the three-dimensional display map according to their style, brand, color, material, size and shape. For example, if the user selects a gray square glass coffee table of brand A, the three-dimensional image of the gray square glass coffee table of brand D is placed in the overall three-dimensional display map according to the corresponding zoom ratio, and the zoom ratio is the same as the zoom ratio of the overall three-dimensional display map.

[0066] The user operation is that the user selects the corresponding option operation in the selection interface according to his or her own preferences at the user end, that is, selects the style, brand, color, material, size and shape of furniture, tiles, lamps, accessories and other accessories.

[0067] In this embodiment, it should be specifically explained that the data collection module is used to collect user data and decoration data, the user data is the user input information of the user end, and the decoration data is the data corresponding to the user input information of the user end, that is, the style, brand, color, material, size and shape of the selected furniture, tiles, lamps, accessories and other accessories corresponding to the price of the items; the decoration data is obtained through web crawlers and big data technology;

[0068] The data preprocessing module is used to receive data from the data collection module and perform preprocessing operations on the data, and the preprocessing operations include but are not limited to cleaning and normalizing operations on the data;

[0069] The decoration scheme calibration module sets a user objective function and marks the decoration scheme that meets the user objective function as a calibrated decoration scheme; based on the user information input by the user end, the style, brand, color, material, size and shape of the furniture, tiles, lamps, accessories and other accessories selected by the user are obtained to form a decoration scheme. If the current decoration scheme does not meet the user objective function, the result is fed back to the user end, and the user chooses whether to modify the current decoration scheme at the user end. If not, the current decoration scheme is transmitted to the decoration scheme optimization module for optimization. If modified, the modified decoration scheme is sent back to the data collection module as the new current decoration scheme, and the corresponding decoration data is re-collected. The decoration scheme calibration module again determines whether it meets the user objective function. If it does, the current decoration scheme is directly marked as the calibrated decoration scheme and transmitted to the decoration scheme optimization module for optimization.

[0070] In this embodiment, it should be specifically explained that the expression of the user objective function is expressed by the formula: MB = COS max , where MB is the objective function value, COS max The maximum value of the decoration cost that the user can accept is the upper limit of the total cost of the selected furniture, tiles, lamps, accessories and other accessories. Different users can accept different maximum values ​​of decoration costs. Therefore, the user objective function can be set in advance according to the specific situation of different users.

[0071] The decoration scheme calibration module estimates the total cost of the current decoration scheme through the acquired decoration data to obtain COS g , if COS g >MB, the current decoration scheme does not meet the user's objective function, and the result is fed back to the user end; if COS g ≤MB, the current decoration scheme meets the user objective function, and the current decoration scheme is directly marked as the calibration decoration scheme.

[0072] In this embodiment, it should be specifically explained that the decoration scheme optimization module optimizes the space layout by combining the space simulation technology, including the following steps:

[0073] Step S01: Obtain multiple spatial layout graphs, encode them, encode them as O, O is the chromosome, obtain the chromosome, and construct the initial population A = {O1, O2, O3, ..., O k};

[0074] Step S02: Determine the fitness function;

[0075] Step S03: Perform natural selection on chromosomes in the population;

[0076] Step S04: performing crossover recombination on chromosomes in the population;

[0077] Step S05: mutating the chromosomes in the population;

[0078] Step S06: obtain a new population, the preset population generation number is L, the fitness threshold is Q, L is an integer greater than 0, and Q is a real number greater than 0; loop step S03 to step S05 until the generation number corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold Q, the loop ends, and the spatial layout diagram corresponding to the chromosome with the maximum fitness in the new population is obtained, which is the optimal spatial layout; illustratively, if the preset population generation number is 1, the chromosomes in the initial population are subjected to natural selection, crossover recombination, and mutation to obtain a new population, and the generation number corresponding to the new population is 1 at this time, so the loop ends;

[0079] The fitness threshold Q is preset by a person skilled in the art according to the algorithm accuracy, and the population algebra L is obtained by a person skilled in the art using a genetic algorithm multiple times under multiple sets of different spatial layout diagrams to obtain the corresponding optimal operation category. In each process of using the genetic algorithm, when the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold Q, the cycle ends and the algebra corresponding to the new population is obtained; the largest algebra among the multiple algebras is taken as the population algebra L;

[0080] Combine the optimal space layout with the calibrated decoration plan to form the final overall decoration plan.

[0081] In this embodiment, it should be specifically explained that the spatial layout diagram is obtained in the following manner:

[0082] Place the furniture, tiles, lamps, accessories and other accessories selected by the user in the three-dimensional display diagram, place the three-dimensional display diagram in the spatial coordinate system, the entire three-dimensional display diagram is located in the first quadrant, the boundary of the floor plan coincides with the boundary of the spatial coordinate system, mark the movable accessories among the selected furniture, tiles, lamps, accessories and other accessories as layout items, use the center point coordinates of the layout items as the item coordinate points, and adjust the position of the item coordinate points, that is, move the position of the layout items in the three-dimensional display diagram to form a variety of different spatial layouts to form a spatial layout diagram, set digital labels 1 to N for the layout items, and set corresponding labels Bi for the item coordinate point positions j; where i = 1, 2, 3, ..., N; j = 1, 2, 3, ..., M; M is the M coordinate positions of the layout items; for example, when the digital label of the dining table is 1, the label corresponding to the first coordinate point position is B11. When the coordinate position of the dining table is changed by moving the dining table, the label of the new coordinate point position is B12. When the table is moved for the Mth time, the label of the coordinate point position is B1M. The same operation is performed for N items to obtain the M coordinate point position labels of each layout item. The coordinate point position labels of all layout items are arranged and combined to form all spatial layout diagrams. Each spatial layout diagram can be expressed as: KB j ={B1j,B2j,B3j,…,BNj}, where KB j is the spatial layout diagram for the jth move; in particular, when the jth move occurs, if there are items in the layout that have not been moved, then Bij = Bi(j-1);

[0083] The fitness function is expressed as: r =RM r , where f r is the fitness corresponding to the rth chromosome, RM r is the spatial layout merit ratio corresponding to the rth chromosome; r = 1, 2, 3, ..., k;

[0084] The natural selection is carried out by combining the elite method and the rotation method; the elite method produces F1 offspring chromosomes, and for a population with a capacity of k, the fitness corresponding to the k chromosomes is arranged from large to small, and each of the F1 chromosomes at the front produces a offspring chromosome; the rotation method produces F2 offspring chromosomes, that is, k chromosomes produce F2 offspring chromosomes according to the corresponding rotation probability; F1+F2=k, so as to keep the offspring population capacity k unchanged and the population generation increases;

[0085] The expression of the rotation probability is: Among them, r is the rotation probability corresponding to the rth chromosome;

[0086] In the step S04, E chromosomes are randomly selected from the population for crossover recombination to obtain E new chromosomes; the crossover recombination adopts the PMX method, which is a prior art method and is not described in detail in this embodiment; after the chromosome crossover recombination, the fitness of the E new chromosomes is calculated, and the fitness of the E new chromosomes and the fitness of the E chromosomes are sorted from large to small to generate a sorting table, and the E new chromosomes in the sorting table replace the E chromosomes for crossover recombination in the population in positive order; in this embodiment, E=0.7k is preferred, and if the calculated E is not an integer, E is rounded up to ensure that the calculated E is an integer;

[0087] In step S05, the mutation probability is preset to V, and the k chromosomes in the population are mutated according to the mutation probability. The mutation method is to randomly select the positions of two genes in the chromosome and exchange the values ​​of the two genes. In this embodiment, V=0.02 is preferred. The mutation probability is preset by technicians in this field according to the algorithm efficiency and algorithm accuracy.

[0088] In this embodiment, it should be specifically explained that the calculation formula of the spatial layout merit ratio is expressed as: Among them, RM r is the spatial layout merit ratio of the spatial layout graph corresponding to the rth chromosome, LY r is the space utilization rate of the spatial layout graph corresponding to the rth chromosome, YD r is the spatial congestion rate of the spatial layout graph corresponding to the rth chromosome;

[0089] The space utilization rate is the average of the ratio of the actual use area of ​​each functional area to the total area. The functional area is the living room area, kitchen area, bedroom area, corridor and other areas in the house. The actual use area is the area where people can move around. The formula is:

[0090] Among them, GN c is the ratio of the actual use area of ​​the cth functional area to the total area, and C is the total number of functional areas;

[0091] The spatial congestion rate is the average of the sum of the congestion losses of each functional area, and the congestion loss is the ratio of the difference between the maximum number of people that each functional area can accommodate at the same time and the total number of family members to the total number of family members; the formula is:

[0092] Among them, X c is the maximum number of people that the cth functional area can accommodate at the same time, and JT is the total number of users’ families.

[0093] In this embodiment, it should be specifically explained that the specific manner in which the construction scheme selection module selects the best construction scheme is:

[0094] Step S11: Initialize the population, define the size of the population and the optimal number of iterations λ; randomly generate an initial population ZQ, where each individual in the population ZQ represents a construction plan;

[0095] The construction plan can be obtained by a technician in the field according to the final overall decoration plan, by obtaining several historical construction plans and modifying them in combination with the actual construction situation and professional knowledge in the field. The construction plan includes construction technology, construction personnel, construction time, etc.;

[0096] Step S12: define blooming function: ZF=μ1×f1(CB)+μ2×f2(TIME)+μ3×f3(WR); wherein ZF is blooming function, μ1 is cost weight, μ2 is time weight, and μ3 is pollution weight; f1(CB) is cost function, f2(TIME) is time function, and f3(WR) is pollution function;

[0097]

[0098] Among them, COS sg is the total cost of the construction plan, T fin is the end time of the construction plan, T aga is the start time of the construction plan, out tan The carbon emissions of all decorative materials in the final overall decoration scheme;

[0099] Step S13: Calculate the value of the blooming function of each individual, record it as the blooming value, sort the current population ZQ based on the blooming value, select the H individuals with the highest blooming value as elite individuals, record the remaining individuals except the elite individuals as non-elite individuals, and for each non-elite individual, explode it with itself as the center to obtain a new exploded individual;

[0100] The formula for explosion is:

[0101] BM=hf+a1×(H max -hf)×(1+a2×||hf-H max ||)×rd(Y,nB)+a3×(g′-hf); where BM is the bloom value of the new explosion individual, hf is the bloom value of the non-elite individual, and H max is the bloom value of the individual with the highest bloom value in the current population, rd(Y,nB) is a Y×nB standard normal distribution random matrix, g′ is the individual with the highest bloom value found so far; a1 and a2 are both explosion constants, a3 is the offset weight parameter, which controls the degree of deviation of the explosion individual to the global optimal solution; Y is the dimension of the individual, and nB is the number of new explosion individuals generated for each individual;

[0102] Step S14: Calculate the bloom values ​​of all new exploded individuals, retain H′ individuals with the highest bloom values, and mutate the individuals retained after the explosion to obtain mutated individuals;

[0103] The formula for mutation is:

[0104] Among them, V I is the bloom value of the individual after mutation, GS is a Gaussian distribution random number, fd is the variation amplitude, which is an adjustable parameter, and t is the variation control parameter, which adjusts the attenuation rate of the variation amplitude; I ZF is the bloom value of individual I retained after the explosion; avg is the average bloom value of the current population, max is the maximum bloom value of the current population, and min is the minimum bloom value of the current population;

[0105] Step S15: Merge the elite individuals, the individuals retained after the explosion, and the individuals after the mutation to form a new generation population ZQ′; repeat the iteration until the optimal number of iterations λ is reached to obtain the final population; select the individual with the highest bloom value from the final population as the best construction plan;

[0106] The final overall decoration plan obtained by the decoration plan optimization module is combined with the best construction plan to form the final decoration construction plan.

[0107] In this embodiment, it should be specifically explained that the construction end displays the final decoration construction plan, including the construction time arrangement, construction process arrangement and construction personnel arrangement, etc.; and the construction is carried out based on this. If the user needs to make partial adjustments to the construction plan, technical personnel in this field can make fine adjustments on this basis.

[0108] In this embodiment, it should be specifically explained that the difference between this embodiment and the prior art lies in that this embodiment has a decoration scheme calibration module, a decoration scheme optimization module and a construction scheme selection module. By setting the user objective function, the decoration scheme that meets the user objective function is marked as a calibrated decoration scheme, and the spatial layout is optimized in combination with the space simulation technology to obtain the final overall decoration scheme. Based on the overall decoration scheme, the corresponding construction scheme is obtained and the best construction scheme is selected to form the final decoration construction scheme. By setting the user objective function, the needs of different users for decoration costs can be obtained. On the premise of meeting the decoration cost requirements, the most satisfactory decoration scheme for the user is obtained, and then the spatial layout of the decoration scheme is optimized, so that the decoration scheme can obtain the maximum space utilization rate under different basic conditions of the house space, ensuring the reasonable use of the space, and based on this, the fireworks optimization algorithm is used to obtain the best construction scheme. The fireworks optimization algorithm has the characteristics of strong evolutionary ability, fast search speed and strong optimization ability, and comprehensively considers the construction scheme cost, construction scheme time and pollution conditions, and optimizes the construction scheme to obtain the optimal solution, which can well cope with the complex and changeable construction environment and the actual needs of different users.

[0109] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0110] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A decoration construction plan optimization system based on artificial intelligence, characterized by: Including user side, program side and construction side; The user terminal is used for the user to input information, perform user terminal operations and synchronously display data for the user; The program end is used to optimize the decoration construction plan, including: The data collection module is used to collect user data and decoration data and transmit them to the data preprocessing module; The data preprocessing module is used to preprocess the user data and the decoration data to obtain the user data and the decoration data that can be directly used; The decoration scheme calibration module is used to receive the data preprocessed by the data preprocessing module and obtain the calibration decoration scheme based on the user objective function; The decoration scheme optimization module is used to receive the decoration scheme calibrated by the decoration scheme calibration module, optimize the space layout by combining the space simulation technology, and obtain the final overall decoration scheme; The construction plan selection module obtains the corresponding construction plan based on the overall decoration plan and selects the best construction plan to form the final decoration construction plan and transmit it to the user end and the construction end; The construction end is used to display the final decoration construction plan and carry out construction based on it, and at the same time, the construction progress is updated in real time at the construction end.

2. The decoration construction plan optimization system based on artificial intelligence according to claim 1, characterized in that: The user information input by the user terminal includes user decoration area information and the style, brand, color, material, size and shape of the selected furniture, tiles, lamps and accessories. The user decoration area information is the area information where the user needs to carry out decoration construction, specifically the area location, area and house type; the user terminal obtains a three-dimensional map of the area to be decorated based on the user decoration area information for display.

3. The decoration construction plan optimization system based on artificial intelligence according to claim 2 is characterized by: The data collection module is used to collect user data and decoration data, the user data is user input information at the user end, and the decoration data is data corresponding to the user input information at the user end; The decoration scheme calibration module marks the decoration scheme that meets the user objective function as a calibrated decoration scheme by setting the user objective function; If the current decoration scheme does not meet the user's objective function, the result will be fed back to the user end, and the user will choose whether to modify the current decoration scheme on the user end. If not, the current decoration scheme will be transmitted to the decoration scheme optimization module for optimization. If modified, the modified decoration scheme will be transmitted back to the data collection module as the new current decoration scheme, and the corresponding decoration data will be recollected. The decoration scheme calibration module will again determine whether it meets the user's objective function. If it does, the current decoration scheme will be directly marked as the calibrated decoration scheme and transmitted to the decoration scheme optimization module for optimization.

4. The decoration construction plan optimization system based on artificial intelligence according to claim 3 is characterized by: The expression of the user objective function is expressed as follows: MB = COS max , where MB is the objective function value, COS max The maximum decoration cost acceptable to users; The decoration scheme calibration module estimates the total cost of the current decoration scheme through the acquired decoration data to obtain COS g , if COS g >MB, the current decoration scheme does not meet the user's objective function, and the result is fed back to the user end; if COS g ≤MB, the current decoration scheme meets the user objective function, and the current decoration scheme is directly marked as the calibration decoration scheme.

5. The decoration construction plan optimization system based on artificial intelligence according to claim 4 is characterized in that: The decoration scheme optimization module optimizes the space layout by combining the space simulation technology, including the following steps: Step S01: Obtain multiple spatial layout graphs, encode them, encode them as O, O is the chromosome, obtain the chromosome, and construct the initial population A = {O1, O2, O3, ..., O k }; Step S02: Determine the fitness function; Step S03: Perform natural selection on chromosomes in the population; Step S04: performing crossover recombination on chromosomes in the population; Step S05: mutating the chromosomes in the population; Step S06: Obtain a new population, preset the population generation number to be L, the fitness threshold to be Q, L is an integer greater than 0, and Q is a real number greater than 0; loop from step S03 to step S05 until the generation number corresponding to the new population is L or the fitness corresponding to the chromosome in the new population is greater than or equal to the fitness threshold Q, the loop ends, and obtain the spatial layout diagram corresponding to the chromosome with the maximum fitness in the new population, which is the optimal spatial layout; Combine the optimal space layout with the calibrated decoration plan to form the final overall decoration plan.

6. The decoration construction plan optimization system based on artificial intelligence according to claim 5 is characterized by: The spatial layout diagram is obtained in the following manner: The furniture, tiles, lamps and accessories selected by the user are placed in the three-dimensional display diagram, and the three-dimensional display diagram is placed in the spatial coordinate system. The entire three-dimensional display diagram is located in the first quadrant, and the boundary of the floor plan coincides with the boundary of the spatial coordinate system. The movable accessories among the selected furniture, tiles, lamps and accessories are marked as layout items, and the center point coordinates of the layout items are used as item coordinate points. The position of the item coordinate point can be adjusted, that is, the position of the layout items in the three-dimensional display diagram is moved to form a variety of different spatial layouts to form a spatial layout diagram, and digital labels 1 to N are set for the layout items, and corresponding labels Bij are set for the item coordinate point positions; wherein, i=1, 2, 3, ..., N; j=1, 2, 3, ..., M; M is the M coordinate positions of the layout items; Each spatial layout diagram can be expressed as: KB j ={B1j,B2j,B3j,...,BNj}, where KB j It is the spatial layout diagram during the j-th move; when the j-th move occurs, if there are items in the layout that have not been moved, then Bij=Bi(j-1).

7. The decoration construction plan optimization system based on artificial intelligence according to claim 6 is characterized by: The fitness function is expressed as: r =RM r , where f r is the fitness corresponding to the rth chromosome, RM r is the spatial layout merit ratio corresponding to the rth chromosome; r = 1, 2, 3, ..., k; The natural selection is carried out by combining the elite method and the rotation method; the elite method produces F1 offspring chromosomes, and for a population with a capacity of k, the fitness corresponding to the k chromosomes is arranged from large to small, and each of the F1 chromosomes at the front produces a offspring chromosome; the rotation method produces F2 offspring chromosomes, that is, k chromosomes produce F2 offspring chromosomes according to the corresponding rotation probability; F1+F2=k, so as to keep the offspring population capacity k unchanged and the population generation increases; The expression of the rotation probability is: Among them, r is the rotation probability corresponding to the rth chromosome.

8. The decoration construction plan optimization system based on artificial intelligence according to claim 7 is characterized by: The calculation formula of the spatial layout merit ratio is expressed as: Among them, RM r is the spatial layout merit ratio of the spatial layout graph corresponding to the rth chromosome, LY r is the space utilization rate of the spatial layout graph corresponding to the rth chromosome, YD r is the spatial congestion rate of the spatial layout graph corresponding to the rth chromosome; The space utilization rate is the average of the ratios of the actual use area of ​​each functional area to the total area, and the formula is: Among them, GN c is the ratio of the actual use area of ​​the cth functional area to the total area, and C is the total number of functional areas; The spatial congestion rate is the average of the sum of the congestion losses of each functional area, and the congestion loss is the ratio of the difference between the maximum number of people that each functional area can accommodate at the same time and the total number of family members to the total number of family members; the formula is: Among them, X c is the maximum number of people that the cth functional area can accommodate at the same time, and JT is the total number of users’ families.

9. The decoration construction plan optimization system based on artificial intelligence according to claim 8 is characterized by: The specific method for the construction scheme selection module to select the best construction scheme is: Step S11: Initialize the population, define the size of the population and the optimal number of iterations λ; randomly generate an initial population ZQ, where each individual in the population ZQ represents a construction plan; Step S12: define blooming function: ZF=μ1×f1(CB)+μ2×f2(TIME)+μ3×f3(WR); wherein ZF is blooming function, μ1 is cost weight, μ2 is time weight, and μ3 is pollution weight; f1(CB) is cost function, f2(TIME) is time function, and f3(WR) is pollution function; Step S13: Calculate the value of the blooming function of each individual, record it as the blooming value, sort the current population ZQ based on the blooming value, select the H individuals with the highest blooming value as elite individuals, record the remaining individuals except the elite individuals as non-elite individuals, and for each non-elite individual, explode it with itself as the center to obtain a new exploded individual; Step S14: Calculate the bloom values ​​of all new exploded individuals, retain H′ individuals with the highest bloom values, and mutate the individuals retained after the explosion to obtain mutated individuals; Step S15: Merge the elite individuals, the individuals retained after the explosion, and the individuals after the mutation to form a new generation population ZQ′; repeat the iteration until the optimal number of iterations λ is reached to obtain the final population; select the individual with the highest bloom value from the final population as the best construction plan; The final overall decoration plan obtained by the decoration plan optimization module is combined with the best construction plan to form the final decoration construction plan.

10. The decoration construction plan optimization system based on artificial intelligence according to claim 9 is characterized in that: The formulas of the cost function, time function and pollution function in the bloom function are respectively expressed as: Among them, COS sg is the total cost of the construction plan, T fin is the end time of the construction plan, T aga is the start time of the construction plan, out tan The carbon emissions of all decorative materials in the final overall decoration scheme; The formula for performing the explosion in step S13 is: BM=hf+a1×(H max -hf)×(1+a2×||hf-H max ||)×rd(Y,nB)+a3×(g′-hf); where BM is the bloom value of the new explosion individual, hf is the bloom value of the non-elite individual, and H max is the bloom value of the individual with the highest bloom value in the current population, rd(Y,nB) is a Y×nB standard normal distribution random matrix, g′ is the individual with the highest bloom value found so far; a1 and a2 are both explosion constants, a3 is the offset weight parameter, which controls the degree of deviation of the explosion individual to the global optimal solution; Y is the dimension of the individual, and nB is the number of new explosion individuals generated for each individual; The formula for mutation in step S14 is: Among them, V I is the bloom value of the individual after mutation, GS is a Gaussian distribution random number, fd is the variation amplitude, which is an adjustable parameter, and t is the variation control parameter, which adjusts the attenuation rate of the variation amplitude; I ZF is the bloom value of individual I retained after the explosion; avg is the average bloom value of the current population, max is the maximum bloom value of the current population, and min is the minimum bloom value of the current population.

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