CN111415035A - Method and device for pre-estimating building function house type ratio - Google Patents
Method and device for pre-estimating building function house type ratio Download PDFInfo
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Abstract
The invention discloses a method and a device for pre-estimating the building function house type ratio, wherein the method comprises the following steps: receiving training data of building conditions, building types and maximum arrangement quantity; performing machine learning model training on training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio; receiving the estimation conditions of the building to be estimated and the alternative building types of the functional house type ratio and the selling price and cost information, and estimating the alternative building types according to the prediction model to obtain the influence range data of each alternative building type; respectively distributing target weight values by a preset target proportion weight configuration strategy by taking the building conditions, selling price and cost information and influence range data of the alternative building types as single factors; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method. The invention enables the measurement result of the functional house type ratio to be closer to the real forced elimination result, and improves the accuracy of the measurement of the functional house type ratio.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for pre-estimating a building function house type ratio.
Background
Building discipline is the general diagram of the highest profit intensity arrangement building, which is a way for the control design of the property developers, and aims to find the building state combination with maximized profit after tax. The quality of the final forced-ventilated scheme is influenced by different building types and the combination of the number of the different building types. In the land taking and forced-ventilated stages of residential building design, the target land needs to be preliminarily estimated, so that the general direction of the forced-ventilated scheme, namely the selection of the residential building type and the estimation of the number of the residential building type can be given on the premise of meeting the set building conditions, and the estimation is called functional house type ratio measurement and calculation.
Through the estimation of the building function house type ratio, the information such as the goods value, the profit, the coverage rate and the like of the whole forced-ventilated scheme can be estimated for the estimation of the area of different buildings, the house type and the number of buildings. At present, the building forced-ventilated and the estimation of the whole economic index are generally carried out by simply adding according to information such as the area, the cost, the selling price and the like of a building type.
At present, simple addition estimation of building area, cost and profit can greatly cause unreasonable estimation results, namely, the estimated forced drainage scheme cannot be realized or still has a space for improvement under the condition of established building indexes, so that economic targets such as user goods value maximization or profit maximization cannot be met, and the estimation method is more likely to generate wrong estimation of the whole economic indexes and wrong judgment of the value of the forced drainage scheme.
Therefore, how to provide a reasonable and most efficient solution for estimating the house type ratio of building functions is a technical problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The invention provides a method and a device for estimating a building function house type ratio, which aim to solve the problem that the prior art has no reasonable building function house type ratio estimation with the highest utilization efficiency.
The invention provides a method for estimating the building function house type ratio, which comprises the following steps:
receiving training data of building conditions, building types and maximum arrangement quantity; performing machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio;
receiving the alternative building types of the pre-estimation conditions and the functional house type ratios of the building to be pre-estimated and the selling price and cost information, and estimating the alternative building types according to the prediction model to obtain the influence range data of each alternative building type;
respectively distributing target weight values by using a preset target proportion weight configuration strategy by taking the building condition, selling price and cost information and influence range data of the alternative building type as single factors; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
Optionally, the receiving of the candidate building types of the estimation conditions and the functional house type ratios of the building to be estimated, the selling price and the cost information, and the estimating of the candidate building types according to the prediction model to obtain the influence range data of each candidate building type are as follows:
receiving the longitude and latitude position information, the shape information, the mountain land information, the peripheral poi information, the height limit information, the total plot volume rate information, the maximum plot coverage rate information, the sunlight information, the maximum plot building density, the state proportion and the selected building type information of the to-be-estimated building;
and estimating the alternative building types with the function house type ratio, the selling price and the cost information through the prediction model to obtain the standard influence range, the sunshine influence range and the coverage influence range of each alternative building type.
Optionally, the preset target proportion weight configuration policy is used to respectively assign the weight values of the targets, where:
taking the maximum goods value, the maximum profit and the maximum coverage rate as a single target or a plurality of comprehensive targets;
and distributing target weight values to the single target or the multiple comprehensive targets by using a preset target proportion weight configuration strategy.
Optionally, the building conditions, selling price and cost information and the influence range data of the alternative building types are used as single factors, and target weight values are respectively distributed by a preset target proportion weight configuration strategy; the optimal functional house type ratio measurement and calculation combination scheme under different targets is obtained by using an integer programming method, and the method comprises the following steps:
the house type, the building area, the selling price, the cost, the standard influence range, the sunshine influence range or the coverage influence range contained in the alternative building type are taken as single factors;
the method is characterized in that the preset total volume rate, the maximum coverage rate, the maximum building density, the state proportion, the minimum proportion of the capital buildings and the minimum proportion of the capital houses are taken as limiting conditions;
respectively distributing the weight values of the targets by a preset target proportion weight configuration strategy; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
Optionally, the training data of the building conditions, the building types and the maximum number of arrangements is received as:
receiving original data of the maximum arrangement quantity of building types in plots with different cities and different shapes;
and corresponding the building conditions, the building types and the maximum arrangement number in the original data to form training data.
In another aspect, the present invention further provides a device for estimating a building function house type ratio, including: the device comprises a prediction model training module, an influence range estimation module and a functional house type ratio prediction module; wherein the content of the first and second substances,
the prediction model training module is connected with the influence range estimation module and used for receiving training data of building conditions, building types and the maximum arrangement number; performing machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio;
the influence range estimation module is connected with the prediction model training module and the functional house type ratio prediction module, receives the estimation conditions of the building to be estimated, the alternative building types of the functional house type ratio, the selling price and the cost information, and estimates the alternative building types according to the prediction model to obtain the influence range data of each alternative building type;
the functional house type ratio prediction module is connected with the influence range estimation module, and respectively distributes target weight values by a preset target proportion weight configuration strategy by taking the building conditions, the selling price and cost information and the influence range data of the alternative building types as single factors; and obtaining the optimal functional house type ratio prediction combination scheme under different targets by using an integer programming method.
Optionally, wherein the influence range estimation module includes: a building information receiving unit to be estimated and an influence range predicting unit; wherein the content of the first and second substances,
the building information receiving unit to be estimated is connected with the prediction model training module and the influence range prediction unit and is used for receiving the longitude and latitude position information, the shape information, the mountain land information, the peripheral poi information, the height limit information, the total plot volume ratio information, the maximum plot coverage rate information, the sunlight information, the maximum plot building density, the state proportion and the selected building type information of the building to be estimated;
the influence range prediction unit is connected with the building information receiving unit to be predicted and the functional house type ratio prediction module, and estimates the received predicted building information and the alternative building types of the functional house type ratio, the selling price and the cost information through the prediction model to obtain the standard influence range, the sunshine influence range and the coverage influence range of each alternative building type.
Optionally, wherein the functional subscriber type ratio predicting module includes: a prediction factor setting unit and a functional house type ratio prediction unit;
the prediction factor setting unit is connected with the influence range estimation module and the functional house type ratio prediction unit, and takes the building conditions, the selling price and the cost information of the alternative building types and the influence range data as a single factor;
the functional house type ratio prediction unit is connected with the prediction factor setting unit and takes the maximum goods value, the maximum profit and the maximum coverage rate as a single target or a plurality of comprehensive targets;
and distributing target weight values to the single target or the multiple comprehensive targets by using a preset target proportion weight configuration strategy.
Optionally, wherein the functional subscriber type ratio predicting module includes: a prediction factor setting unit and a functional house type ratio prediction unit; wherein the content of the first and second substances,
the prediction factor setting unit is connected with the influence range estimation module and the functional house type ratio prediction unit, and uses the house type, the building area, the selling price, the cost, the standard influence range, the sunshine influence range or the coverage influence range contained in the alternative building type as a single factor;
the method is characterized in that the preset total volume rate, the maximum coverage rate, the maximum building density, the state proportion, the minimum proportion of the capital buildings and the minimum proportion of the capital houses are taken as limiting conditions;
the functional house type ratio prediction unit is connected with the prediction factor setting unit and respectively distributes the weight values of the targets according to a preset target proportion weight configuration strategy; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
Optionally, wherein the predictive model training module includes: a training data collection unit and a prediction model training unit; wherein the content of the first and second substances,
the training data collection unit is connected with the prediction model training unit and used for receiving the original data of the maximum arrangement quantity of building types in plots with different cities and different shapes;
building conditions, building types and the maximum arrangement number in the original data are corresponded to form training data;
and the prediction model training unit is connected with the training data collection unit and the influence range estimation module, and performs machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio.
The method and the device for estimating the building functional house type ratio add factors such as building type related information, land block related information, city related information, set building conditions and the like into the functional house type ratio measurement and calculation, so that the influence of the factors such as longitude and latitude information, the contour and the shape of a land block, mountain land information, the height limit of a land block building, the total volume ratio of the land block, the maximum coverage rate of the land block, the maximum building density of the land block, the attitude ratio, building type lighting, building type contour, city specifications, city sunshine and the like on the quality of the integral strong-row scheme of different building types and different building type building number combinations is also considered, and the measurement and calculation result of the functional house type ratio is closer to a real strong-row result.
The functional household ratio measurement adopts various targets such as maximum goods value, maximum profit, maximum coverage rate and the like as guidance, and provides optimal strategy selection under various different targets for users. The maximum number of the alternative building types under different blocks of different cities can be predicted through the machine learning model, so that the accuracy of measuring and calculating the functional house type ratio can be improved by taking an actual forced-ventilated data result as a guide.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic flow chart illustrating a method for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a second method for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a third method for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a fourth method for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 5 is a schematic flow chart illustrating a fifth method for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an apparatus for estimating a building function house type ratio according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating the configuration of a plot city and a plot contour shape in a pre-estimated building function house type ratio according to an embodiment of the present invention;
FIG. 8 is a diagram illustrating the configuration of an overall index of a block in a pre-estimated building function house type ratio according to an embodiment of the present invention;
FIG. 9 is a diagram illustrating the configuration of the base height limit, building density, and business status ratio indicators in the pre-estimated building function/house type ratio according to the embodiment of the present invention;
FIG. 10 is a diagram illustrating the configuration of a building type selection indicator in the pre-estimated building function house type ratio according to an embodiment of the present invention;
FIG. 11 is a diagram illustrating the result of measuring and calculating a functional house type ratio of the pre-estimated building functional house type ratios according to the embodiment of the present invention;
FIG. 12 is a diagram showing the result of measuring the number of buildings and buildings according to the functional house type ratio of the building in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In this embodiment, the building function house type ratio is estimated, and more geographical and building type information is considered, so that an optimal strategy under each target can be generated according to different information such as building types, land parcels, cities, building conditions and the like, and the strategy effect can be continuously improved to approach to real strong emission, thereby improving the generation probability, speed and effect of the strong emission scheme.
Specifically, as shown in fig. 1, a schematic flow chart of a method for estimating a building function house type ratio in this embodiment is shown, and the method includes the following steps:
And 102, receiving the estimation conditions of the building to be estimated and the alternative building types of the functional house type ratio and the selling price and cost information, estimating the alternative building types according to the prediction model, and obtaining the influence range data of each alternative building type.
103, respectively distributing target weight values by a preset target proportion weight configuration strategy by taking the building conditions, selling price and cost information and influence range data of the alternative building types as single factors; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
In some optional embodiments, as shown in fig. 2, which is a schematic flow chart of a second method for estimating a building functional house type ratio in this embodiment, different from fig. 1, the method receives an estimated condition of a building to be estimated, an alternative building type of the functional house type ratio, and selling price and cost information, estimates the alternative building type according to a prediction model, and obtains influence range data of each alternative building type, where the method is as follows:
And step 202, estimating the alternative building types and the selling price and the cost information of the function house type ratio through a prediction model to obtain the standard influence range, the sunshine influence range and the coverage influence range of each alternative building type.
In some optional embodiments, as shown in fig. 3, which is a schematic flow chart of a third method for estimating a building function house type ratio in this embodiment, different from that in fig. 1, target weight values are respectively assigned by a preset target proportion weight configuration policy, where the target weight values are:
In some optional embodiments, as shown in fig. 4, which is a schematic flow chart of a fourth method for estimating a building function house type ratio in this embodiment, different from fig. 1, building conditions, selling price and cost information, and influence range data of an alternative building type are used as a single factor, and a preset target proportion weight configuration policy is used to respectively assign target weight values; the optimal functional house type ratio measurement and calculation combination scheme under different targets is obtained by using an integer programming method, and the method comprises the following steps:
In some optional embodiments, as shown in fig. 5, which is a schematic flow chart of a fifth method for estimating a building function house type ratio in this embodiment, different from fig. 1, the training data of the building conditions, the building type, and the maximum arrangement number is received as follows:
and 501, receiving the original data of the maximum arrangement quantity of building types in different city landforms with different shapes.
And 502, corresponding the building conditions, the building types and the maximum arrangement number in the original data to form training data.
In some optional embodiments, as shown in fig. 6, which is a schematic structural diagram of a first apparatus for estimating a building function house type ratio in this embodiment, the method for estimating a building function house type ratio may be implemented, and specifically, the apparatus includes: a prediction model training module 601, an influence range estimation module 602, and a functional subscriber type ratio prediction module 603.
The prediction model training module 601 is connected to the influence range estimation module 602, and receives training data of building conditions, building types and maximum arrangement number; and performing machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio.
And an influence range estimation module 602, connected to the prediction model training module 601 and the functional house type ratio prediction module 603, for receiving the estimation conditions of the building to be estimated, the alternative building types of the functional house type ratio, the selling price and the cost information, and estimating the alternative building types according to the prediction model to obtain influence range data of each alternative building type.
The functional house type ratio prediction module 603 is connected with the influence range estimation module 602, and distributes target weight values by a preset target proportion weight configuration strategy by taking the building conditions, the selling price and cost information of the alternative building types and the influence range data as single factors; and obtaining the optimal functional house type ratio prediction combination scheme under different targets by using an integer programming method.
In some optional embodiments, in the structural schematic diagram of the second apparatus for estimating a building function house type ratio in this embodiment, different from that in fig. 6, the influence range estimation module includes: a building information receiving unit to be estimated and an influence range predicting unit.
The building information receiving unit to be estimated is connected with the prediction model training module and the influence range prediction unit and is used for receiving the longitude and latitude position information, the shape information, the mountain land information, the peripheral poi information, the height limit information, the total plot volume ratio information, the maximum plot coverage rate information, the sunlight information, the maximum plot building density, the state proportion and the selected building type information of the building to be estimated.
And the influence range prediction unit is connected with the building information receiving unit to be predicted and the functional house type ratio prediction module, estimates the received predicted building information and the alternative building types of the functional house type ratio, the selling price and the cost information through a prediction model, and obtains the standard influence range, the sunlight influence range and the coverage influence range of each alternative building type.
In some optional embodiments, in the structural schematic diagram of the third apparatus for estimating a building functional house type ratio in this embodiment, different from fig. 6, the functional house type ratio predicting module includes: a prediction factor setting unit and a function house type ratio prediction unit.
And the prediction factor setting unit is connected with the influence range estimation module and the functional house type ratio prediction unit, and takes the building conditions, the selling price and the cost information of the alternative building types and the influence range data as a single factor.
The functional house type ratio prediction unit is connected with the prediction factor setting unit and takes the maximum goods value, the maximum profit and the maximum coverage rate as a single target or a plurality of comprehensive targets; and distributing target weight values to a single target or a plurality of comprehensive targets by using a preset target proportion weight configuration strategy.
In some optional embodiments, the prediction factor setting unit takes the house type, the building area, the selling price, the cost, the standard influence range, the sunshine influence range or the coverage influence range contained in the optional building type as a single factor; the preset total volume rate, the maximum coverage rate, the maximum building density, the state proportion, the minimum proportion of the capital building type and the minimum proportion of the capital house type are taken as limiting conditions.
The functional house type ratio prediction unit distributes the weight values of the targets respectively according to a preset target proportion weight configuration strategy; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
In some optional embodiments, in this embodiment, a schematic structural diagram of a fourth apparatus for estimating a building function house type ratio is different from that in fig. 6, where the predictive model training module includes: a training data collection unit and a prediction model training unit.
The system comprises a prediction model training unit, a training data collecting unit, a prediction model training unit and a data processing unit, wherein the training data collecting unit is connected with the prediction model training unit and receives the original data of the maximum arrangement quantity of building types in plots with different cities and different shapes; and corresponding the building conditions, the building types and the maximum arrangement number in the original data to form training data.
And the prediction model training unit is connected with the training data collection unit and the influence range estimation module, and performs machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio.
Fig. 7-12 show an application example of the pre-estimated building function house type ratio in the embodiment, fig. 7 is a setting and displaying diagram of a plot city and a plot outline shape in the pre-estimated building function house type ratio in the embodiment of the present invention; FIG. 8 is a diagram illustrating the configuration of an overall index of a block in a pre-estimated building function house type ratio according to an embodiment of the present invention; FIG. 9 is a diagram illustrating the configuration of the base height limit, building density, and business status ratio indicators in the pre-estimated building function/house type ratio according to the embodiment of the present invention; FIG. 10 is a diagram illustrating the configuration of a building type selection indicator in the pre-estimated building function house type ratio according to an embodiment of the present invention; FIG. 11 is a diagram illustrating the result of measuring and calculating a functional house type ratio of the pre-estimated building functional house type ratios according to the embodiment of the present invention; FIG. 12 is a diagram showing the result of measuring the number of buildings and buildings according to the functional house type ratio of the building in the embodiment of the present invention.
The maximum arrangement quantity of a certain building type in the plots with any shape and any longitude and latitude can be predicted by carrying out machine learning model training on the collected data about the maximum arrangement quantity of the certain building type in the plots with different cities and different shapes.
And estimating the standard influence range, the sunlight influence range, the coverage influence range and the like of each alternative building type through the prediction model with the maximum arrangement quantity according to the parameters of the longitude and latitude position information of the land block, the shape of the land block, the mountain land information where the land block is located, the peripheral poi information, the building height limit of the land block, the total volume rate of the land block, the maximum coverage rate of the land block, the sunlight, the maximum building density of the land block, the business proportion, the information of the selected building type and the like input by the user.
The method is characterized in that the house type, the building area, the selling price, the cost, the standard influence range, the sunlight influence range, the coverage influence range and the like of each alternative building type are taken as single factors, one or more of single targets such as the maximum goods value, the maximum profit, the maximum coverage rate and the like are taken as comprehensive targets by an integer programming method through taking the established total volume rate, the maximum coverage rate, the maximum building density, the business state ratio, the minimum ratio of the main building type and the like as limiting conditions, and different single targets are given different empirical proportion weights to obtain the optimal solution of the building type selection and the building type number estimation. In general, the following operation steps can be included: a user selects the city position and the outline shape of the land parcel; the user selects the total building area and the total volume rate of the base, whether the sunshine is considered or not, whether the indexes of mountain land and the like are considered or not; the user selects the alternative building type for carrying out functional house type ratio measurement and calculation and sets information such as unit cost, selling price and the like of the building type; according to the input information of the user, estimating the sunshine, the standard and the coverage influence range of the alternative building type through a machine learning model; obtaining an optimal combination scheme under different targets by using integer programming; and displaying the measurement result of the functional house type ratio to the user.
In this embodiment, a computer device may further be included, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the method for estimating the building function house type ratio as described above.
A readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for estimating a building function subscriber size ratio as described above.
It will be understood by those of ordinary skill in the art that all or a portion of the processes of the methods of the embodiments described above may be implemented by a computer program that may be stored in a non-volatile computer-readable storage medium, which, when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A method for estimating the building function house type ratio is characterized by comprising the following steps:
receiving training data of building conditions, building types and maximum arrangement quantity; performing machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio;
receiving the alternative building types of the pre-estimation conditions and the functional house type ratios of the building to be pre-estimated and the selling price and cost information, and estimating the alternative building types according to the prediction model to obtain the influence range data of each alternative building type;
respectively distributing target weight values by using a preset target proportion weight configuration strategy by taking the building condition, selling price and cost information and influence range data of the alternative building type as single factors; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
2. The method according to claim 1, wherein the method comprises receiving the estimation conditions of the building to be estimated, the alternative building types of the functional house type ratio, and the selling price and cost information, estimating the alternative building types according to the prediction model to obtain the influence range data of each alternative building type, and comprises:
receiving the longitude and latitude position information, the shape information, the mountain land information, the peripheral poi information, the height limit information, the total plot volume rate information, the maximum plot coverage rate information, the sunlight information, the maximum plot building density, the state proportion and the selected building type information of the to-be-estimated building;
and estimating the alternative building types with the function house type ratio, the selling price and the cost information through the prediction model to obtain the standard influence range, the sunshine influence range and the coverage influence range of each alternative building type.
3. The method of claim 1, wherein the weight values of the targets are respectively assigned according to a preset target proportion weight configuration strategy, and the method comprises the following steps:
taking the maximum goods value, the maximum profit and the maximum coverage rate as a single target or a plurality of comprehensive targets;
and distributing target weight values to the single target or the multiple comprehensive targets by using a preset target proportion weight configuration strategy.
4. The method of claim 1, wherein the building conditions, selling price and cost information and the influence range data of the alternative building types are used as single factors, and weight values of targets are respectively distributed by a preset target proportion weight configuration strategy; the optimal functional house type ratio measurement and calculation combination scheme under different targets is obtained by using an integer programming method, and the method comprises the following steps:
the house type, the building area, the selling price, the cost, the standard influence range, the sunshine influence range or the coverage influence range contained in the alternative building type are taken as single factors;
the method is characterized in that the preset total volume rate, the maximum coverage rate, the maximum building density, the state proportion, the minimum proportion of the capital buildings and the minimum proportion of the capital houses are taken as limiting conditions;
respectively distributing the weight values of the targets by a preset target proportion weight configuration strategy; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
5. The method for estimating the building functional house type ratio as claimed in claim 1, wherein the training data of building conditions, building types and maximum arrangement number are received as follows:
receiving original data of the maximum arrangement quantity of building types in plots with different cities and different shapes;
and corresponding the building conditions, the building types and the maximum arrangement number in the original data to form training data.
6. An apparatus for estimating a building function house type ratio, comprising: the device comprises a prediction model training module, an influence range estimation module and a functional house type ratio prediction module; wherein the content of the first and second substances,
the prediction model training module is connected with the influence range estimation module and used for receiving training data of building conditions, building types and the maximum arrangement number; performing machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio;
the influence range estimation module is connected with the prediction model training module and the functional house type ratio prediction module, receives the estimation conditions of the building to be estimated, the alternative building types of the functional house type ratio, the selling price and the cost information, and estimates the alternative building types according to the prediction model to obtain the influence range data of each alternative building type;
the functional house type ratio prediction module is connected with the influence range estimation module, and respectively distributes target weight values by a preset target proportion weight configuration strategy by taking the building conditions, the selling price and cost information and the influence range data of the alternative building types as single factors; and obtaining the optimal functional house type ratio prediction combination scheme under different targets by using an integer programming method.
7. The apparatus of claim 6, wherein the influence range estimation module comprises: a building information receiving unit to be estimated and an influence range predicting unit; wherein the content of the first and second substances,
the building information receiving unit to be estimated is connected with the prediction model training module and the influence range prediction unit and is used for receiving the longitude and latitude position information, the shape information, the mountain land information, the peripheral poi information, the height limit information, the total plot volume ratio information, the maximum plot coverage rate information, the sunlight information, the maximum plot building density, the state proportion and the selected building type information of the building to be estimated;
the influence range prediction unit is connected with the building information receiving unit to be predicted and the functional house type ratio prediction module, and estimates the received predicted building information and the alternative building types of the functional house type ratio, the selling price and the cost information through the prediction model to obtain the standard influence range, the sunshine influence range and the coverage influence range of each alternative building type.
8. The apparatus for estimating building functional house type ratio as claimed in claim 6, wherein the functional house type ratio prediction module comprises: a prediction factor setting unit and a functional house type ratio prediction unit;
the prediction factor setting unit is connected with the influence range estimation module and the functional house type ratio prediction unit, and takes the building conditions, the selling price and the cost information of the alternative building types and the influence range data as a single factor;
the functional house type ratio prediction unit is connected with the prediction factor setting unit and takes the maximum goods value, the maximum profit and the maximum coverage rate as a single target or a plurality of comprehensive targets;
and distributing target weight values to the single target or the multiple comprehensive targets by using a preset target proportion weight configuration strategy.
9. The apparatus for estimating building functional house type ratio as claimed in claim 6, wherein the functional house type ratio prediction module comprises: a prediction factor setting unit and a functional house type ratio prediction unit; wherein the content of the first and second substances,
the prediction factor setting unit is connected with the influence range estimation module and the functional house type ratio prediction unit, and uses the house type, the building area, the selling price, the cost, the standard influence range, the sunshine influence range or the coverage influence range contained in the alternative building type as a single factor;
the method is characterized in that the preset total volume rate, the maximum coverage rate, the maximum building density, the state proportion, the minimum proportion of the capital buildings and the minimum proportion of the capital houses are taken as limiting conditions;
the functional house type ratio prediction unit is connected with the prediction factor setting unit and respectively distributes the weight values of the targets according to a preset target proportion weight configuration strategy; and (4) obtaining the optimal functional household type ratio measurement and calculation combination scheme under different targets by using an integer programming method.
10. The apparatus for estimating building function house type ratio as claimed in claim 6, wherein the prediction model training module comprises: a training data collection unit and a prediction model training unit; wherein the content of the first and second substances,
the training data collection unit is connected with the prediction model training unit and used for receiving the original data of the maximum arrangement quantity of building types in plots with different cities and different shapes;
building conditions, building types and the maximum arrangement number in the original data are corresponded to form training data;
and the prediction model training unit is connected with the training data collection unit and the influence range estimation module, and performs machine learning model training on the training data according to a preset functional house type ratio measuring and calculating strategy to obtain a prediction model of the building functional house type ratio.
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