CN109299585A - A kind of architectural design method based on artificial intelligence - Google Patents
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- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
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Abstract
The present invention provides a kind of architectural design method based on artificial intelligence, by establishing database purchase building shape product data, carries out ground structure analysis using building of the peripheral hardware to required design, and compare qualifications built in correlation, completes architectural design method.
Description
Technical field
The present invention relates to field of artificial intelligence, in particular to a kind of architectural design method based on artificial intelligence.
Background technique
With the continuous propulsion of digitlization and IT application process, in existing detail design, designer usually can be applied
The design tool software of existing building decoration area is designed, and is accordingly generated and finally presented in the form of electronic data
Design result.
Building trade, which works, be unable to do without data information and Heuristics, including drawing, technical documentation, operating instruction and industry
Information etc..In current design workflow, architect generally uses traditionally on paper and electronic information document, and partial information is borrowed
Internet is helped, but lies substantially in the inefficient state of windows folder management, shows themselves in that data deficiencies genealogical classification, data
Amount is few, storage position dispersion, and information island, shortage system integration management join with outside network resource one by one for artificial formation
System is weak；Data check mode is single, and search efficiency is low, and data content shows not intuitive.In the information age, architectural design
It is the course of work that bulk items information was integrated and created processing by architect, electronic degree is high, and information exchange is frequent, low
The design data management mode of effect necessarily affects the promotion of design work efficiency.
Summary of the invention
To realize above-mentioned technical purpose and the technique effect, proposing a kind of architectural design side based on artificial intelligence
Method carries out ground structure analysis using building of the peripheral hardware to required design by establishing database purchase building shape product data, and
Qualifications built in comparison correlation, complete architectural design method, which is characterized in that specifically comprise the following steps:
Step 1: establishing server, the model data of building is collected by server, and be stored in advance alternative
Architectural modulus；
Step 2: acquisition map datum treats construction area and carries out terrain data typing, and carries out the circle on building ground online
It is fixed, upload the base CAD file；
Step 3: to the underlying parameter of server typing building, limiting building items basic data；
Step 4: carrying out data comparison in server, pass through the building of internal model data combination step 3 typing
Underlying parameter automatically generates building type product model, and generates electronic document output.
Specifically, the architectural modulus includes level-one architectural modulus, second level architectural modulus and three-level architectural modulus.
Specifically, the level-one architectural modulus includes axis net and buildings model.
Specifically, the earphone architectural modulus includes building series, D reconstruction and door and window tool.
Specifically, the three-level architectural modulus includes pillar, beam, floor, wall and stair, project name, door number, class
Type and fire-protection rating and lintel, terrace absolute altitude, door pocket pattern, door leaf thickness, door leaf height, door leaf width and remarks.
Specifically, the base CAD file includes the topography and geomorphology in area yet to be built, circle ground range and is building ground scheme again
Report.
Specifically, the peripheral hardware includes equipped with remote control equipment and with nobody of infrared sensing and camera shooting photographing device
Machine, field surveys equipment and telecommunication equipment.
Specifically, electronic document generated includes design general layout, each layer plane figure of building type, elevation, explanation
Book and bill of approximate estimate.
Specifically, the process for automatically generating building pattern type product model is carried out using deep learning model, utilize
Each sample that training sample is concentrated, is trained the initial deep learning model constructed in advance, obtains intermediate depth study
Model；Wherein, the initial deep learning model are as follows: be loaded with the deep learning model of class object function；
Using the intermediate deep learning model, the feature vector that the training sample concentrates each sample, and root are calculated
The feature vector of each sample is concentrated according to the training sample, calculates the initial of the intermediate parameters of central point distance objective function
Value；
Central point distance objective function is added in the intermediate deep learning model and loads the intermediate parameters
Initial value obtains target deep learning model；
The preset quantity sample of training sample concentration is imported as lot data；
Using current goal deep learning model, the feature vector of each sample in present lot data is calculated, and according to
The feature vector of each sample in present lot data, updates the parameter value of the intermediate parameters；
Based on the feature vector of each sample in present lot data, the function of the central point distance objective function is calculated
The functional value of value and the class object function, and judge whether the functional value for the central point distance objective function being calculated is received
Whether the functional value for the class object function held back to the first predetermined interval, and be calculated converges to the second predetermined interval；
If not, utilizing the back-propagation gradient of central point distance objective function and the reversed biography of the class object function
Gradient is broadcast, the parameter of current goal deep learning model is adjusted, and returns and executes the pre- of the importing training sample concentration
If the step of quantity sample is as lot data；
If so, terminating the training to current goal deep learning model.
It is different from the prior art, on the basis of existing design method, the artificial intelligence design based on deep learning is added
Mode, it is possible to reduce the manpower consumption in design process, designer only need to be audited and be modified on the basis of the drawing produced,
Intuitively, the carry out architectural design refined, provides more convenience.
Specific embodiment
Below in conjunction with the embodiment of the present invention, technical scheme in the embodiment of the invention is clearly and completely described,
Obviously, the described embodiments are merely a part of the embodiments of the present invention, instead of all the embodiments.Based in the present invention
Embodiment, every other embodiment obtained by those of ordinary skill in the art without making creative efforts, all
Belong to the scope of protection of the invention.
A kind of architectural design method based on artificial intelligence, by establishing database purchase building shape product data, using outer
If the building to required design carries out ground structure analysis, and compares qualifications built in correlation, architectural design method, tool are completed
Body includes the following steps:
Step 1: establishing server, the model data of building is collected by server, and be stored in advance alternative
Architectural modulus；
Step 2: acquisition map datum treats construction area and carries out terrain data typing, and carries out the circle on building ground online
It is fixed, upload the base CAD file；
Step 3: to the underlying parameter of server typing building, limiting building items basic data；
Step 4: carrying out data comparison in server, pass through the building of internal model data combination step 3 typing
Underlying parameter automatically generates building type product model, and generates electronic document output.
Wherein, the architectural modulus includes level-one architectural modulus, second level architectural modulus and three-level architectural modulus.
The level-one architectural modulus includes axis net and buildings model.
The earphone architectural modulus includes building series, D reconstruction and door and window tool.
The three-level architectural modulus includes pillar, beam, floor, wall and stair, project name, door number, type and prevents
Fiery grade and lintel, terrace absolute altitude, door pocket pattern, door leaf thickness, door leaf height, door leaf width and remarks.
The base CAD file includes the topography and geomorphology in area yet to be built, circle ground range and is building ground scheme report again.
The peripheral hardware includes equipped with remote control equipment and with infrared sensing and the unmanned plane, the scene survey that image photographing device
Equipment and telecommunication equipment are drawn, unmanned plane can set cruise route, and remote controlled drone is cruised, while pass through carrying
Remote sensing equipment on unmanned plane shoots regional neighboring area yet to be built in each monitoring position.
Electronic document generated includes design general layout, each layer plane figure of building type, elevation, specification and general
Calculate book.
Further, the process for automatically generating building pattern type product model is carried out using deep learning model, benefit
The each sample concentrated with training sample, is trained the initial deep learning model constructed in advance, obtains intermediate depth
Practise model；Wherein, the initial deep learning model are as follows: be loaded with the deep learning model of class object function；
Using the intermediate deep learning model, the feature vector that the training sample concentrates each sample, and root are calculated
The feature vector of each sample is concentrated according to the training sample, calculates the initial of the intermediate parameters of central point distance objective function
Value；
Central point distance objective function is added in the intermediate deep learning model and loads the intermediate parameters
Initial value obtains target deep learning model；
The preset quantity sample of training sample concentration is imported as lot data；
Using current goal deep learning model, the feature vector of each sample in present lot data is calculated, and according to
The feature vector of each sample in present lot data, updates the parameter value of the intermediate parameters；
Based on the feature vector of each sample in present lot data, the function of the central point distance objective function is calculated
The functional value of value and the class object function, and judge whether the functional value for the central point distance objective function being calculated is received
Whether the functional value for the class object function held back to the first predetermined interval, and be calculated converges to the second predetermined interval；
If not, utilizing the back-propagation gradient of central point distance objective function and the reversed biography of the class object function
Gradient is broadcast, the parameter of current goal deep learning model is adjusted, and returns and executes the pre- of the importing training sample concentration
If the step of quantity sample is as lot data；
If so, terminating the training to current goal deep learning model.
Server is used to store the architectural modulus for user setting；Wherein server is stored with building for user setting
The parameters such as frame, architectural design details are built, service implement body can be using any proper data storage type or storage rack
The database of structure.
Preferably, can scheme constructs hardware system according to the present invention, including one or more processors and deposit
Reservoir.Wherein, processor and memory can be connected by bus or other modes,
Memory as a kind of non-volatile computer readable storage medium storing program for executing, can be used for storing non-volatile software program,
Non-volatile computer executable program and module, such as the architectural design based on Building Information Model in the embodiment of the present invention
Corresponding program instruction/the module of method.Processor by run non-volatile software program stored in memory, instruction with
And module, thereby executing the various function application and data processing of server, i.e., realization above method embodiment based on building
Build the architectural design method of information model.
Memory may include storing program area and storage data area, wherein storing program area can storage program area, extremely
Application program required for a few function；Storage data area, which can be stored, uses created number according to architectural design system
According to etc..In addition, memory may include high-speed random access memory, it can also include nonvolatile memory, for example, at least
One disk memory, flush memory device or other non-volatile solid state memory parts.In some embodiments, memory can
Choosing includes the memory remotely located relative to processor, these remote memories can be by network connection to based on building letter
Cease the architectural design system of model.The example of above-mentioned network includes but is not limited to internet, intranet, local area network, movement
Communication network and combinations thereof.
One or more of module storages in the memory, are executed when by one or more of processors
When, execute above-mentioned architectural design method.
By adopting the above technical scheme, by unmanned plane place surrounding enviroment can be carried out with the acquisition of image, and be based on
The analysis that image includes color is handled, with the dominant hue of environment and each position institute of building where determination area yet to be built
Corresponding details tone (i.e. selection tone)；Based on the analysis of above-mentioned tone data, so that the tone of building can be with periphery
Primary climate be consistent, and may make place relative to component environment details carry out tone fitting so that place and peripheral ring
The total tune degree in border is significantly improved.At the same time, the above-mentioned large size regional architecture yet to be built based on mobile platform analysis
Design method, also can personnel for surrounding enviroment and vehicle flow while the tone to place surrounding enviroment is monitored
It is monitored, so that designer would know that the magnitude of traffic flow numerical value of regional periphery each region yet to be built, and is based on above-mentioned number
Value carries out the roading of public place, so that the quick circulation of the achievable personnel in area yet to be built planned, so that its
Service efficiency is obviously improved
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright description, or direct or brief introduction are used in other correlative technology fields,
It is included within the scope of the present invention.
Claims (9)
1. a kind of architectural design method based on artificial intelligence utilizes peripheral hardware by establishing database purchase building shape product data
Ground structure analysis is carried out to the building of required design, and compares qualifications built in correlation, completes architectural design method, it is special
Sign is, specifically comprises the following steps:
Step 1: establishing server, the model data of building is collected by server, and alternative building is stored in advance
Parameter；
Step 2: acquisition map datum treats construction area and carries out terrain data typing, and carries out the delineation on building ground online, on
Pass the base CAD file；
Step 3: to the underlying parameter of server typing building, limiting building items basic data；
Step 4: carrying out data comparison in server, pass through the basis of the building of internal model data combination step 3 typing
Parameter automatically generates building type product model, and generates electronic document output.
2. a kind of architectural design method based on artificial intelligence according to claim 1, it is characterised in that: the building ginseng
Number includes level-one architectural modulus, second level architectural modulus and three-level architectural modulus.
3. a kind of architectural design method based on artificial intelligence according to claim 2, it is characterised in that: the level-one is built
Building parameter includes axis net and buildings model.
4. a kind of architectural design method based on artificial intelligence according to claim 2, it is characterised in that: the earphone is built
Building parameter includes building series, D reconstruction and door and window tool.
5. a kind of architectural design method based on artificial intelligence according to claim 2, it is characterised in that: the three-level is built
Build parameter include pillar, beam, floor, wall and stair, project name, door number, type and fire-protection rating and lintel,
Level ground absolute altitude, door pocket pattern, door leaf thickness, door leaf height, door leaf width and remarks.
6. a kind of architectural design method based on artificial intelligence according to claim 1, it is characterised in that: the CAD base
Ground file includes the topography and geomorphology in area yet to be built, circle ground range and is building ground scheme report again.
7. a kind of architectural design method based on artificial intelligence according to claim 1, it is characterised in that: the peripheral hardware packet
Include unmanned plane, field surveys equipment and the telecommunication equipped with remote control equipment and with infrared sensing and camera shooting photographing device
Equipment.
8. a kind of architectural design method based on artificial intelligence according to claim 1, it is characterised in that: electricity generated
Subfile includes design general layout, each layer plane figure of building type, elevation, specification and bill of approximate estimate.
9. it is according to claim 1 it is a kind of based on manually can only architectural design method, it is characterised in that: described is automatic
The process for generating building pattern type product model is carried out using deep learning model, and each sample concentrated using training sample is right
The initial deep learning model constructed in advance is trained, and obtains intermediate deep learning model；Wherein, initial deep learning model
Are as follows: it is loaded with the deep learning model of class object function；
Using the intermediate deep learning model, the feature vector that the training sample concentrates each sample is calculated, and according to institute
The feature vector that training sample concentrates each sample is stated, the initial value of the intermediate parameters of central point distance objective function is calculated；
Central point distance objective function is added in intermediate deep learning model and is loaded the initial value of the intermediate parameters, is obtained
To target deep learning model；
The preset quantity sample of training sample concentration is imported as lot data；
Using current goal deep learning model, the feature vector of each sample in present lot data is calculated, and according to current
The feature vector of each sample in lot data, updates the parameter value of intermediate parameters；
Based on the feature vector of each sample in present lot data, calculate the central point distance objective function functional value and
The functional value of class object function, and judge whether the functional value for the central point distance objective function being calculated converges to first
Predetermined interval, and whether the functional value for the class object function being calculated converges to the second predetermined interval；
If not, utilizing the back-propagation gradient of central point distance objective function and the backpropagation ladder of the class object function
Degree, adjusts the parameter of current goal deep learning model, and returns and execute the preset quantity for importing training sample concentration
The step of sample is as lot data；
If so, terminating the training to current goal deep learning model.
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| CN110096835A (en) * | 2019-05-14 | 2019-08-06 | 上海荷福人工智能科技（集团）有限公司 | A kind of arrangement and method for construction optimum management method based on artificial intelligence engineering design |
| CN114641753A (en) * | 2019-11-18 | 2022-06-17 | 欧特克公司 | Composite data generation and Building Information Model (BIM) element extraction from floor plan drawings using machine learning |
| WO2024079761A1 (en) * | 2022-10-13 | 2024-04-18 | Visava Labs Private Limited | A system and method for generating architectural designs and specifications for buildings |
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Application publication date: 20190201 |