CN109598085A - One kind being based on artificial intelligence construction project time management method - Google Patents
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- CN109598085A CN109598085A CN201811549477.XA CN201811549477A CN109598085A CN 109598085 A CN109598085 A CN 109598085A CN 201811549477 A CN201811549477 A CN 201811549477A CN 109598085 A CN109598085 A CN 109598085A
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- 238000010276 construction Methods 0.000 title claims abstract description 78
- 238000007726 management method Methods 0.000 title claims abstract description 29
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 14
- 238000012550 audit Methods 0.000 claims abstract description 9
- 238000013461 design Methods 0.000 claims abstract description 5
- 230000006870 function Effects 0.000 claims description 29
- 230000002452 interceptive effect Effects 0.000 claims description 28
- 238000013136 deep learning model Methods 0.000 claims description 23
- 238000012549 training Methods 0.000 claims description 15
- 238000000034 method Methods 0.000 claims description 13
- 230000002354 daily effect Effects 0.000 claims description 7
- 239000012141 concentrate Substances 0.000 claims description 4
- 238000013135 deep learning Methods 0.000 claims description 3
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Abstract
The present invention provides a kind of based on artificial intelligence construction project time management method, establish management database, BIM model is established according to design and construction drawing, and its BIM model data is imported into management database, pass through the daily construction speed report of site operation personnel, next construction task is adjusted by database audits construction speed, and reassigns to each construction group.
Description
Technical field
The present invention relates to field of artificial intelligence, in particular to a kind of to be based on artificial intelligence construction project time management method.
Background technique
With the development of building civil engineering construction, construction industry Construction management is also constantly being sent out with method, technology
Exhibition progress.
During building cost management, to the way to manages such as progress, quality, cost, safety, method also continuous
Innovation.In the management process of construction speed, the construction schedule for working out engineering project is one of construction project time management
Major tasks.
Traditional schedule preparation method, in general, being used according to construction drawing on the basis of construction experience
The software of project etc carries out the authorized strength work of construction schedule.The method, there are a large amount of defects, such as: being worked out
Construction schedule be not able to satisfy practice of construction demand；Largely there are in terms of working procedure for construction schedule
Wrong, missing, touch, lack the problems such as.In addition to this, worked out construction schedule can not be simulated visually, and into
The adjustment work for spending plan is inconvenient.
Summary of the invention
To realize above-mentioned technical purpose and the technique effect, proposing a kind of based on artificial intelligence construction project time management
Method establishes management database, establishes BIM model according to design and construction drawing, and its BIM model data is imported management data
Library is reported by the daily construction speed of site operation personnel, is appointed by the next construction of database audits construction speed adjustment
Business, and reassign to each construction group, which is characterized in that specifically comprise the following steps:
Step 1: establishing management database, while the BIM model established according to construction drawing, and the BIM model established
Light-weight technologg is carried out, integrates BIM model and progress control software in database server, it is special to generate corresponding construction
The BIM model of industry classification；
Step 2: scene, which is set up, can interact supervision equipment, supervise current construction speed and to may deposit in current work progress
Security risk warned；
Step 3: after daily construction terminates, the project progress on the same day is uploaded by the way that supervision equipment can be interacted, and after having
Platform is audited；
Step 4: according to current construction speed and remaining workload and time restriction after audit, redistributing and connect down
The work plan come, and transfer to each construction group；
Step 5: for the job schedule of every day, supervising log and task distribution carries out unified log layout and protects
It deposits, is audited convenient for the later period.
Preferably, the supervision equipment that interacts includes including the first interactive interface, the second interactive interface and third interaction
Interface, and between the first interactive interface and the second interactive interface, setting jump between the second interactive interface and third interactive interface
Turn link.
Preferably, the generating process of the BIM model of the professional classification is by the way of deep learning, in management data
It is pre-stored the BIM model of all kinds of professions in library, and the data parameters of wherein each model are pre-processed, including time ginseng
Number, architectural modulus and construction classification parameter；When the data parameters of the BIM model of required building meet condition, automatic structure
It builds one and meets the BIM model of condition, and assign corresponding data to it.
Preferably, first interactive interface shows the construction task on the same day.
Preferably, second interactive interface shows the warning information of current construction day, including environmental information and construction
The security warning information of points for attention and current construction task in the process.
Preferably, the third interactive interface shows subsequent task adjustment and interim work adjustment and arranges.
Preferably, the 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 intermediate deep learning model and loads the initial of the intermediate parameters
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 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 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 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 present count for importing training sample and concentrating
Measure a step of sample is as lot data；
If so, terminating the training to current goal deep learning model.
It is different from the prior art, the application carries out daily task by artificial intelligence technology and supervises, while according to the same day
Task Progress and engineering time limitation, subsequent construction task is rearranged, and be issued to construction group, together
When, execution conditions and weather condition to the same day construct in safe early warning.
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.
One kind being based on artificial intelligence construction project time management method, establishes management database, is established according to design and construction drawing
BIM model, and its BIM model data is imported into management database, it is reported by the daily construction speed of site operation personnel, by
Database audits construction speed adjusts next construction task, and reassigns to each construction group, which is characterized in that
Specifically comprise the following steps:
Step 1: establishing management database, while the BIM model established according to construction drawing, and the BIM model established
Light-weight technologg is carried out, integrates BIM model and progress control software in database server, it is special to generate corresponding construction
The BIM model of industry classification；
Step 2: scene, which is set up, can interact supervision equipment, supervise current construction speed and to may deposit in current work progress
Security risk warned；
Step 3: after daily construction terminates, the project progress on the same day is uploaded by the way that supervision equipment can be interacted, and after having
Platform is audited；
Step 4: according to current construction speed and remaining workload and time restriction after audit, redistributing and connect down
The work plan come, and transfer to each construction group；
Step 5: for the job schedule of every day, supervising log and task distribution carries out unified log layout and protects
It deposits, is audited convenient for the later period.
Preferably, the supervision equipment that interacts includes including the first interactive interface, the second interactive interface and third interaction
Interface, and between the first interactive interface and the second interactive interface, setting jump between the second interactive interface and third interactive interface
Turn link.
Preferably, the generating process of the BIM model of the professional classification is by the way of deep learning, in management data
It is pre-stored the BIM model of all kinds of professions in library, and the data parameters of wherein each model are pre-processed, including time ginseng
Number, architectural modulus and construction classification parameter；When the data parameters of the BIM model of required building meet condition, automatic structure
It builds one and meets the BIM model of condition, and assign corresponding data to it.
Preferably, first interactive interface shows the construction task on the same day.
Preferably, second interactive interface shows the warning information of current construction day, including environmental information and construction
The security warning information of points for attention and current construction task in the process.
Preferably, the third interactive interface shows subsequent task adjustment and interim work adjustment and arranges.
Preferably, the 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 intermediate deep learning model and loads the initial of the intermediate parameters
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 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 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 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 present count for importing training sample and concentrating
Measure a step of sample is as lot data；
If so, terminating the training to current goal deep learning model.
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 (7)
1. one kind is based on artificial intelligence construction project time management method, management database is established, BIM is established according to design and construction drawing
Model, and its BIM model data is imported into management database, it is reported by the daily construction speed of site operation personnel, by counting
Next construction task is adjusted according to library audit construction speed, and reassigns to each construction group, which is characterized in that tool
Body includes the following steps:
Step 1: establishing management database, while the BIM model established according to construction drawing, and the BIM model established carries out
Light-weight technologg integrates BIM model and progress control software in database server, generates corresponding construction profession point
The BIM model of class；
Step 2: scene, which is set up, can interact supervision equipment, supervise current construction speed and to that may be present in current work progress
Security risk is warned；
Step 3: after daily construction terminates, by can interact supervision equipment upload the same day project progress, and have backstage into
Row audit；
Step 4: according to current construction speed and remaining workload and time restriction after audit, redistributing next
Work plan, and transfer to each construction group；
Step 5: for the job schedule of every day, supervises log and task distribution carries out unified log layout and saves,
Convenient for later period audit.
2. according to claim 1 a kind of based on artificial intelligence construction project time management method, it is characterised in that: described to hand over
Mutually supervision equipment include include the first interactive interface, the second interactive interface and third interactive interface, and in the first interactive interface and
Redirected link is set between second interactive interface, between the second interactive interface and third interactive interface.
3. according to claim 1 a kind of based on artificial intelligence construction project time management method, it is characterised in that: described is special
The generating process of the BIM model of industry classification is pre-stored the BIM of all kinds of professions by the way of deep learning in management database
Model, and the data parameters of wherein each model are pre-processed, including time parameter, architectural modulus and construction classification
Parameter；When the data parameters of the BIM model of required building meet condition, automatic building one meets the BIM model of condition,
And corresponding data are assigned to it.
4. according to claim 2 a kind of based on artificial intelligence construction project time management method, it is characterised in that: described first
Interactive interface shows the construction task on the same day.
A kind of be based on artificial intelligence construction project time management method 5. according to claim 2, it is characterised in that:, described the
Two interactive interfaces show the warning information of current construction day, including the points for attention in environmental information and work progress and work as
The security warning information of preceding construction task.
6. according to claim 2 a kind of based on artificial intelligence construction project time management method, it is characterised in that: the third
Interactive interface shows subsequent task adjustment and interim work adjustment and arranges.
7. it is according to claim 1 it is a kind of based on manually can only architectural design method, it is characterised in that: the depth
Practise 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 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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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112819261A (en) * | 2021-04-19 | 2021-05-18 | 中数通信息有限公司 | Wisdom engineering cooperative management system |
| CN114065336A (en) * | 2021-09-28 | 2022-02-18 | 广州优比建筑咨询有限公司 | Revit-based high formwork region inspection method, device, medium and equipment |
| CN115878872A (en) * | 2023-02-08 | 2023-03-31 | 一智科技(成都)有限公司 | Construction progress visualization method and system |
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| US20140316837A1 (en) * | 2013-04-19 | 2014-10-23 | Trimble Navigation Limited | Method and system of construction project management |
| CN108460231A (en) * | 2018-03-23 | 2018-08-28 | 中交公路长大桥建设国家工程研究中心有限公司 | A kind of bridge builds foster overall process intellectual monitoring assessment early warning decision system and method |
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2018
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| US20140316837A1 (en) * | 2013-04-19 | 2014-10-23 | Trimble Navigation Limited | Method and system of construction project management |
| CN108460231A (en) * | 2018-03-23 | 2018-08-28 | 中交公路长大桥建设国家工程研究中心有限公司 | A kind of bridge builds foster overall process intellectual monitoring assessment early warning decision system and method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112819261A (en) * | 2021-04-19 | 2021-05-18 | 中数通信息有限公司 | Wisdom engineering cooperative management system |
| CN112819261B (en) * | 2021-04-19 | 2021-08-03 | 中数通信息有限公司 | Wisdom engineering cooperative management system |
| CN114065336A (en) * | 2021-09-28 | 2022-02-18 | 广州优比建筑咨询有限公司 | Revit-based high formwork region inspection method, device, medium and equipment |
| CN115878872A (en) * | 2023-02-08 | 2023-03-31 | 一智科技(成都)有限公司 | Construction progress visualization method and system |
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Application publication date: 20190409 |