CN109816228A - A kind of enterprise B IM technical application ability quantitative evaluation system and method - Google Patents
A kind of enterprise B IM technical application ability quantitative evaluation system and method Download PDFInfo
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Abstract
The invention belongs to enterprise B IM technical fields, a kind of enterprise B IM technical application ability quantitative evaluation system and method is disclosed, the enterprise B IM technical application ability quantitative evaluation system includes: data acquisition module, central control module, data-optimized module, quantitative model building module, ability rating division module, management module, print module, assessment data memory module, assessment display module.The present invention can adapt to the processing requirement of large-scale corporation's BIM technology application-dependent data collection by data-optimized module, simultaneously by distributed storage mode, promotion in terms of data set process performance, united analysis and processing are carried out to the multi-class data collection in big data, are convenient for efficient storage and analysis；Meanwhile work collaboration, quantitative management can be realized with decision Analysis by management module, Risk Pre-control ability is improved, realizes management and the accumulation of technical experience.
Description
Technical field
The invention belongs to enterprise B IM technical field more particularly to a kind of enterprise B IM technical application ability quantitative evaluation systems
And method.
Background technique
BIM (Building Information Modeling) technology is that autodesk, inc. took the lead in proposing in 2002,
Being widely recognized as industry is obtained in the world at present, it can help to realize the integrated of architecture information, from building
Until building the termination of life cycle management, various information are integrated and a three-dimensional model information data always for design, construction, operation
In library, all parties such as design team, unit in charge of construction, installation fishery department and owner can be cooperated based on BIM, be had
Effect improves working efficiency, saves resource, reduces cost, to realize sustainable development.The core of BIM is by establishing virtual build
Engineering threedimensional model is built, using digitizing technique, the consistent architectural engineering of complete and actual conditions is provided for this model and believes
Cease library.The information bank includes not only geological information, professional attributes and the status information for describing building member, further comprises non-structure
The status information of part object (such as space, motor behavior).Include the threedimensional model of architectural engineering information by this, greatly improves
The Information Integration degree of architectural engineering, so that the relevant benefit side for construction-engineering project provides an engineering information and hands over
The platform for changing and sharing.BIM has the following characteristics that it can not only be applied in the design, applies also for construction project
In life cycle management；It is designed with BIM and belongs to Design of digital；The database of BIM is dynamic change, in application process
Constantly update, it is abundant and substantial；Each side, which is participated in, for project provides the platform of collaborative work.China's BIM standard is being studied
In formulation, research group has achieved initial success.However, the enterprise B IM technical application related data of existing acquisition is with big
The application demand for measuring small documents processing, there is a large amount of heterogeneous data sources, the unified specifications of data deficiency in different information systems
Change method for organizing, in certain fields, a large amount of script files are difficult to effectively analysis and efficient storage and retrieval；Meanwhile existing enterprise
Industry BIM technology is only capable of providing auxiliary support to engineering project in sport technique segment, can not connect with the information for supporting enterprise of overall importance
Change management to need.
In conclusion problem of the existing technology is:
(1) application demand that the enterprise B IM technical application related data of existing acquisition is handled with large amount of small documents is different
There is a large amount of heterogeneous data sources in information system, the unified standardisation body method of data deficiency, in certain fields, big foot-measuring
This document is difficult to effectively analysis and efficient storage and retrieval；Meanwhile existing enterprise's BIM technology is only capable of in sport technique segment to engineering
Project provides auxiliary and supports, can not connect with the information system management needs for supporting enterprise of overall importance.
(2) network interface card connection network retrieval acquisition enterprise B IM is needed using during relevant initial data in the prior art
The excavation that data are carried out to mass data cannot be improved the peak focus performance of data mining and be looked into using traditional algorithm
Quasi- rate improve the optimization access of database and data dispatching cannot effectively.
(3) during memory is data cached to the progress of relevant data in the prior art, using traditional algorithm pair
Data carry out caching process, and the loss of redundant operation bring performance cannot be effectively reduced, and reduce the robustness of reservoir and steady
It is qualitative.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of enterprise B IM technical application ability quantitative evaluation systems
System and method.
The invention is realized in this way a kind of enterprise B IM technical application ability quantitative estimation method, the enterprise B IM skill
Art application power quantitative estimation method includes:
Step 1 connects network retrieval using network interface card by data acquisition module and acquires enterprise B IM using relevant original
Data；
Step 2, central control module remove acquisition initial data using data-optimized algorithm by data-optimized module
The optimization of extraneous data operates；
Step 3 utilizes data processing software according to the collected data by quantization model construction module, determines and apply energy
The weight of each factor of power carries out the mathematical model that BIM application power project evaluation chain is established in refinement to each factor；
Step 4, handling capacity grade classification module using data processing software enterprise B IM technical application ability successively
It is divided into five Preliminary Applications stage, growth stage, raising stage, the stage of ripeness and constantly improve stage grades；
Step 5 is managed operation to the informationization of enterprise using management program by management module；Pass through impression block
Block prints enterprise B IM technical application ability quantitative evaluation result using printer；
Step 6 utilizes the initial data and enterprise B IM technology of memory storage acquisition by assessment data memory module
Application power quantitative evaluation result；
Step 7 shows enterprise B IM technical application ability quantitative evaluation result using display by assessment display module.
Further, data acquisition module connects network retrieval by network interface card and acquires enterprise B IM using relevant initial data
During, it is specifically included using improved database mass data method for digging:
Binary vector description obtains mass data information flow auto-correlation function C (τ), as follows:
In formula, τ is auto-correlation time delay coefficient；UiIt introduces the attributes correlation estimation technique and extracts mass data information flow auto-correlation
Database massive information stream sequence { x in functioni}:
In formula, N > 1；
Mass data feature clustering result is brought into, to database massive information stream sequence { xiCarry out attributes correlation estimate
Meter, utilizes Xi+jτ(τ)={ xi}×hi(τ)+ni(τ) × C (j τ) obtains mass data feature Fuzzy subtractive clustering dispersion；Formula
Middle h (τ) is X (τ) in cloud computing database mass data library index function, and n (τ) is the original of mass data in cloud computing database
Function, h (τ) and n (τ) are the information gain of mass data；
Utilize formula Xi+jτ(τ)={ xi}×hi(τ)+niThe cluster dispersion of (τ) × C (j τ) to mass data information from
Scattered attribute is analyzed, and is merged attributes correlation method and established high-volume database efficient information data mining model, realizes cloud meter
Calculate the data mining of database:
r′i(t)=Sri(t)*Xri(- t)=S (t) * X (- t) * h 'i(t)*hi(-t)+n1i(t)；
Wherein, attributes correlation estimated result are as follows:
Further, initial data and enterprise B IM technical application that assessment data memory module passes through memory storage acquisition
Ability quantitative evaluation as a result, using consistency Hash distributed caching data redundancy algorithm, specifically includes the following steps:
Step 1, request is data cached, generates data key values, carries out hash operation to key assignments；
Step 2, data pass through main Hash ring, search main Hash ring, judge whether to find corresponding dummy node, "Yes"
Obtaining main storage address, "No" enters hash from ring,
Step 3 judges whether to connect central control module；"Yes" obtain data cached, end；"No" enters
From hash ring；
Step 4 is searched from hash ring, and corresponding dummy node is found, and is obtained storage address, is connected central control module,
Obtain data cached, end.
The enterprise B IM technical application ability quantitative estimation method is realized another object of the present invention is to provide a kind of
Enterprise B IM technical application ability quantitative evaluation system, the enterprise B IM technical application ability quantitative evaluation system include:
Data acquisition module is connect with central control module, is answered for connecting network retrieval acquisition enterprise B IM by network interface card
With relevant initial data；
Central control module is drawn with data acquisition module, data-optimized module, quantitative model building module, ability rating
Sub-module, management module, print module, assessment data memory module, assessment display module connection, for being controlled by single-chip microcontroller
Modules work normally；
Data-optimized module, connect with central control module, for being gone by data-optimized algorithm to acquisition initial data
Except the optimization operation of extraneous data；
Quantitative model constructs module, connect with central control module, for the number by data processing software according to acquisition
According to determining the weight of each factor of application power, carry out refinement to each factor and establish the mathematical modulo of BIM application power project evaluation chain
Type；
Ability rating division module, connect with central control module, for passing through data processing software enterprise B IM technology
Application power is in turn divided into Preliminary Applications stage, growth stage, raising stage, the stage of ripeness and constantly improve stage five
A grade；
Management module is connect with central control module, for being managed behaviour to the informationization of enterprise by management program
Make；
Print module is connect with central control module, for printing the quantization of enterprise B IM technical application ability by printer
Assessment result；
Data memory module is assessed, is connect with central control module, for the initial data by memory storage acquisition
And enterprise B IM technical application ability quantitative evaluation result；
Display module is assessed, is connect with central control module, for showing enterprise B IM technical application ability by display
Quantitative evaluation result.
Another object of the present invention is to provide a kind of using the enterprise B IM technical application ability quantitative estimation method
Enterprise B IM collaborative platform.
Advantages of the present invention and good effect are as follows: the present invention can adapt to large-scale corporation BIM by data-optimized module
The processing requirement of technical application associated data set, while by distributed storage mode, mentioning in terms of data set process performance
It rises, united analysis and processing is carried out to the multi-class data collection in big data, are convenient for efficient storage and analysis；Meanwhile passing through management
Module can realize work collaboration, quantitative management with decision Analysis, improve Risk Pre-control ability, realize management and technology warp
The accumulation tested.
Data acquisition module connects network retrieval by network interface card and acquires enterprise B IM using relevant initial data in the present invention
During, it needs to carry out mass data the excavation of data, improves the peak focus performance and precision ratio of data mining, change
Optimization access and the data dispatching of database have been apt to it, using a kind of improved database mass data method for digging.
Data memory module is assessed in the present invention passes through the initial data and enterprise B IM technical application of memory storage acquisition
In ability quantitative evaluation outcome procedure, need to relevant data carry out it is data cached, brought in order to which redundant operation is effectively reduced
Performance loss, improve the robustness and stability of reservoir, using consistency Hash distributed caching data redundancy calculate
Method.
Detailed description of the invention
Fig. 1 is enterprise B IM technical application ability quantitative estimation method flow chart provided in an embodiment of the present invention.
Fig. 2 is enterprise B IM technical application ability quantitative evaluation system structure diagram provided in an embodiment of the present invention.
In Fig. 2: 1, data acquisition module；2, central control module；3, data-optimized module；4, quantitative model constructs mould
Block；5, ability rating division module；6, management module；7, print module；8, data memory module is assessed；9, assessment display mould
Block.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, enterprise B IM technical application ability quantitative estimation method provided by the invention the following steps are included:
Step S101 connects network retrieval using network interface card by data acquisition module and acquires enterprise B IM using relevant original
Beginning data；
Step S102, central control module go acquisition initial data using data-optimized algorithm by data-optimized module
Except the optimization operation of extraneous data；
Step S103 utilizes data processing software according to the collected data by quantization model construction module, determines application
The weight of each factor of ability carries out the mathematical model that BIM application power project evaluation chain is established in refinement to each factor；
Step S104, handling capacity grade classification module using data processing software enterprise B IM technical application ability according to
It is secondary to be divided into five Preliminary Applications stage, growth stage, raising stage, the stage of ripeness and constantly improve stage grades；
Step S105 is managed operation to the informationization of enterprise using management program by management module；Pass through printing
Module prints enterprise B IM technical application ability quantitative evaluation result using printer；
Step S106 utilizes the initial data and enterprise B IM skill of memory storage acquisition by assessment data memory module
Art application power quantitative evaluation result；
Step S107 shows enterprise B IM technical application ability quantitative evaluation knot using display by assessment display module
Fruit.
As shown in Fig. 2, enterprise B IM technical application ability quantitative evaluation system provided by the invention includes: data acquisition module
Block 1, central control module 2, data-optimized module 3, quantitative model construct module 4, ability rating division module 5, management module
6, print module 7, assessment data memory module 8, assessment display module 9.
Data acquisition module 1 is connect with central control module 2, acquires enterprise B IM for connecting network retrieval by network interface card
Using relevant initial data；
Central control module 2 constructs module 4, ability etc. with data acquisition module 1, data-optimized module 3, quantitative model
Grade division module 5, management module 6, print module 7, assessment data memory module 8, assessment display module 9 connect, for passing through
Single-chip microcontroller controls modules and works normally；
Data-optimized module 3, connect with central control module 2, is used for through data-optimized algorithm to acquisition initial data
Remove the optimization operation of extraneous data；
Quantitative model constructs module 4, connect with central control module 2, for passing through data processing software according to acquisition
Data determine the weight of each factor of application power, carry out the mathematics that BIM application power project evaluation chain is established in refinement to each factor
Model；
Ability rating division module 5 is connect with central control module 2, for passing through data processing software enterprise B IM skill
Art application power is in turn divided into Preliminary Applications stage, growth stage, raising stage, the stage of ripeness and constantly improve stage
Five grades；
Management module 6 is connect with central control module 2, for being managed by management program to the informationization of enterprise
Operation；
Print module 7 is connect with central control module 2, for printing enterprise B IM technical application ability amount by printer
Change assessment result；
Data memory module 8 is assessed, is connect with central control module 2, for the original number by memory storage acquisition
According to and enterprise B IM technical application ability quantitative evaluation result；
Display module 9 is assessed, is connect with central control module 2, for showing enterprise B IM technical application energy by display
Strength assessment result.
The data acquisition module 1 connects network retrieval by network interface card and acquires enterprise B IM using relevant initial data
In the process, the excavation for needing to carry out mass data data, improves the peak focus performance and precision ratio of data mining, improves
The optimization access of database and data dispatching, using a kind of improved database mass data method for digging, specific mistake
Journey is as follows:
Binary vector description obtains mass data information flow auto-correlation function C (τ), as follows:
In formula, τ is auto-correlation time delay coefficient；UiIt introduces the attributes correlation estimation technique and extracts mass data information flow auto-correlation
Database massive information stream sequence { x in functioni}:
In formula, N > 1；
Above-mentioned mass data feature clustering result is brought into, to database massive information stream sequence { xiCarry out attribute phase
Guan Du estimation, utilizes Xi+jτ(τ)={ xi}×hi(τ)+niIt is discrete that (τ) × C (j τ) obtains mass data feature Fuzzy subtractive clustering
Degree；H (τ) is X (τ) in cloud computing database mass data library index function in formula, and n (τ) is magnanimity number in cloud computing database
According to original function, h (τ) and n (τ) are the information gain of mass data；
Utilize formula Xi+jτ(τ)={ xi}×hi(τ)+niThe cluster dispersion of (τ) × C (j τ) to mass data information from
Scattered attribute is analyzed, and is merged attributes correlation method and established high-volume database efficient information data mining model, realizes cloud meter
Calculate the data mining of database:
r′i(t)=Sri(t)*Xri(- t)=S (t) * X (- t) * h 'i(t)*hi(-t)+n1i(t)；
Wherein, attributes correlation estimated result is
The initial data and enterprise B IM technical application energy that the assessment data memory module 8 passes through memory storage acquisition
During strength assessment result, need to relevant data carry out it is data cached, in order to which redundant operation bring is effectively reduced
Performance loss, improves the robustness and stability of reservoir, using the distributed caching data redundancy algorithm of consistency Hash,
Specifically includes the following steps:
Step 1, request is data cached, generates data key values, carries out hash operation to key assignments；
Step 2, data pass through main Hash ring, search main Hash ring, judge whether to find corresponding dummy node, "Yes"
Obtaining main storage address, "No" enters hash from ring,
Step 3 judges whether to connect central control module；"Yes" obtain data cached, end；"No" enters
From hash ring；
Step 4 is searched from hash ring, and corresponding dummy node is found, and is obtained storage address, is connected central control module,
Obtain data cached, end.
Enterprise B IM technical application ability is in turn divided by the ability rating division module 5 by data processing software
Preliminary Applications stage, growth stage during improving five stage, the stage of ripeness and constantly improve stage grades, have
The enterprise B IM technical application ability assessment method of body, specifically includes the following steps:
Step 1 chooses evaluation index, and the constituent element of BIM application power is more, what is be related in extensive range, application power
The selection of index must be correct, and each capacity index cannot have too many information overlap；
Step 2 constructs appraisement system, after ensuring that the subordinate relation between each application power is accurate, according to
BIM technology feature, is based oneself upon and actual use situation of the BIM in engineering project, layering building BIM application power evaluation index body
System；
Step 3 determines the weight of evaluation index, the subjective weight of evaluation index is determined first with analytic hierarchy process (AHP), so
The objective weight for determining evaluation index using entropy assessment afterwards, finally determines the combining weights of index using root Evaluation formula,
Make every effort to weigh；Determining accuracy and reliability again；
Evaluation model is established and verified to step 4, according to the composition situation of assessment indicator system, selects element method
The degree of strength of each application power of BIM technology is calculated, and proof analysis is carried out to the applicable cases of projects BIM technology,
To verify the feasibility of evaluation model, new method is provided for the evaluation of engineering project BIM application power.
3 optimization method of data-optimized module provided by the invention is as follows:
(1) it searches and meets most using a large amount of Frequent Sets generated in relevant initial data optimization process for enterprise B IM
The Frequent Set that small support requires removes the proper subclass of the data set item, and circulation, which executes, searches and delete, until whole set of data
Until lookup finishes, and retain maximum data Frequent Set, reduces data search range；
(2) maximum data Frequent Set is pre-processed, removes the attribute unrelated with its, rejected relevant high branch and belong to
Property, then induction-arrangement Numeric Attributes, and generate corresponding training sample；
(3) when being trained to sample, the information gain and ratio of profit increase of each nodal community is calculated separately, is then found out
Meet information gain-ratio maximum value and information gain-ratio is more than or equal to the node of average value attribute, as current trunk section
Point, the step of front then is executed to the sample loops of trunk child node, when the master attribute value of branch is all equal or does not belong to
Property optional time, generate initial decision tree；
(4) central point information in decision tree data set is read, distinguishes records center point information using two files, and deposit
Storage is in system files.
In step (3) provided by the invention, when the information gain-ratio to each nodal community calculates, to node
Key-value pair is grouped and is sorted according to key, and the key-value pair with same keys is then sent to Reduce function and is handled, and
Exported as a result, in the Reduce function stage, if the attribute value of data set be it is continuous, be just ranked up, and for belonging to
Property be worth discrete data set can without sequence.
In step (4) provided by the invention, all central point informations in two files are read in run function, then
Whether same or similar compare the central point of front and back twice, if the same stops iterative process.
6 management method of management module provided by the invention is as follows:
1) BIM model is constructed；BIM model include geological information, physical message, Rule Information and building change it is later
Physical presence information；
2) using BIM model as data medium, project indicator management tool, digital asset library, enterprise's cloud platform etc. are utilized
Tool establishes three-level management system；
3) pass through virtual construction line, target control line, practical construction four line, evaluation line project data mining processes
Carry out the information system management of construction enterprises；
Wherein, the three-level is three-level management main body: being divided into of company level, branch company according to project management main body
Grade, project level respectively correspond as decision-making level, management level, execution level, and each level relies on enterprise's tertiary management system according to pipes at different levels
It manages responsibility and carries out linkage from top to bottom, common finished item threedimensional model and building for project data are safeguarded and fallen based on same model
The work such as real technical application point is implemented, Project Process is managed and digitlization is delivered；
Four lines are four project data mining processes, are to be divided into virtually to build according to project data process management
Make line, target control line, it is practical build four line, evaluation line project data mining processes, data mining generally refer to from
Past empirical method (is relied on by statistics, online analysis and processing, information retrieval, machine learning, expert system in a large amount of data
Then) and pattern-recognition scheduling algorithm searches for the process for being hidden in wherein information；
The virtual construction line is upload enterprise's cloud plateform system after establishing project BIM model, is according to what is worked out
Embedded algorithm general rule of uniting (i.e. embedded rule), adjusts project model specificity parameter and sets, transferred by virtual construction
Experience data in mathematic for business asset library simulate standardized project and build route, provide item construction management ginseng
In the same old way originally；
The target control line is to take classification to handle virtual construction line number evidence, of company level to be carried out just with general parameter
Step setting, branch company's grade adjust general parameter according to project difference, management objectives.
It is described it is practical build line, be integrated use mobile Internet, Internet of Things, bio-identification, cloud computing, Noise reducing of data with
And artificial intelligence technology, for acquisition convenience, data accuracy, process standard expansion research, to realize project scene sea
It measures effective acquisition of real data and utilizes；
The evaluation line is to the practical comparison point for building line, target control line progress process, two dimension of result
Analysis establishes traceable correction management and performance based on " PDCA circulation " and evaluates mechanism.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. a kind of enterprise B IM technical application ability quantitative estimation method, which is characterized in that the enterprise B IM technical application ability
Quantitative estimation method includes:
Step 1 connects network retrieval using network interface card by data acquisition module and acquires enterprise B IM using relevant initial data；
Step 2, central control module remove acquisition initial data using data-optimized algorithm by data-optimized module unrelated
The optimization of data operates；
Step 3 utilizes data processing software according to the collected data by quantization model construction module, determines that application power is each
The weight of factor carries out the mathematical model that BIM application power project evaluation chain is established in refinement to each factor；
Step 4, handling capacity grade classification module successively divide enterprise B IM technical application ability using data processing software
For the Preliminary Applications stage, growth stage, improve five stage, the stage of ripeness and constantly improve stage grades；
Step 5 is managed operation to the informationization of enterprise using management program by management module；Pass through print module benefit
Enterprise B IM technical application ability quantitative evaluation result is printed with printer；
Step 6 utilizes the initial data and enterprise B IM technical application of memory storage acquisition by assessment data memory module
Ability quantitative evaluation result；
Step 7 shows enterprise B IM technical application ability quantitative evaluation result using display by assessment display module.
2. enterprise B IM technical application ability quantitative estimation method as described in claim 1, which is characterized in that data acquisition module
During block applies relevant initial data by network interface card connection network retrieval acquisition enterprise B IM, using improved database
Mass data method for digging specifically includes:
Binary vector description obtains mass data information flow auto-correlation function C (τ), as follows:
In formula, τ is auto-correlation time delay coefficient；UiIt introduces the attributes correlation estimation technique and extracts mass data information flow auto-correlation function
In database massive information stream sequence { xi}:
In formula, N > 1；
Mass data feature clustering result is brought into, to database massive information stream sequence { xiCarry out attributes correlation estimation, benefit
Use Xi+jτ(τ)={ xi}×hi(τ)+ni(τ) × C (j τ) obtains mass data feature Fuzzy subtractive clustering dispersion；N (τ) in formula
Function is indexed in cloud computing database mass data library for X (τ), n (τ) is the original function of mass data in cloud computing database, n
(τ) and n (τ) are the information gain of mass data；
Utilize formula Xi+jτ(τ)={ xi}×hi(τ)+niThe cluster dispersion of (τ) × C (j τ) is to mass data information Category Attributes
It is analyzed, and merges attributes correlation method and establish high-volume database efficient information data mining model, realize cloud computing data
The data mining in library:
r′i(t)=Sri(t)*Xri(- t)=S (t) * X (- t) * h 'i(t)*hi(-t)+n1i(t)；
Wherein, attributes correlation estimated result are as follows:
3. enterprise B IM technical application ability quantitative estimation method as described in claim 1, which is characterized in that assessment data are deposited
Module is stored up by the initial data and enterprise B IM technical application ability quantitative evaluation of memory storage acquisition as a result, using consistent
The distributed caching data redundancy algorithm of property Hash, specifically includes the following steps:
Step 1, request is data cached, generates data key values, carries out hash operation to key assignments；
Step 2, data pass through main Hash ring, search main Hash ring, judge whether to find corresponding dummy node, "Yes" obtains
Main storage address, "No" enter hash from ring,
Step 3 judges whether to connect central control module；"Yes" obtain data cached, end；"No" enter from
Hash ring；
Step 4 is searched from hash ring, and corresponding dummy node is found, and is obtained storage address, is connected central control module, obtains
It is data cached, terminate.
4. a kind of enterprise B IM technical application energy for realizing enterprise B IM technical application ability quantitative estimation method described in claim 1
Strength assessment system, which is characterized in that the enterprise B IM technical application ability quantitative evaluation system includes:
Data acquisition module is connect with central control module, acquires enterprise B IM application phase for connecting network retrieval by network interface card
The initial data of pass；
Central control module divides mould with data acquisition module, data-optimized module, quantitative model building module, ability rating
Block, management module, print module, assessment data memory module, assessment display module connection, it is each for being controlled by single-chip microcontroller
Module works normally；
Data-optimized module, connect with central control module, for removing nothing to acquisition initial data by data-optimized algorithm
Close the optimization operation of data；
Quantitative model constructs module, connect with central control module, for passing through data processing software according to the collected data, really
The weight for determining each factor of application power carries out the mathematical model that BIM application power project evaluation chain is established in refinement to each factor；
Ability rating division module, connect with central control module, for passing through data processing software enterprise B IM technical application
Ability is in turn divided into Preliminary Applications stage, growth stage, raising stage, the stage of ripeness and the constantly improve stage five etc.
Grade；
Management module is connect with central control module, for being managed operation to the informationization of enterprise by management program；
Print module is connect with central control module, for printing enterprise B IM technical application ability quantitative evaluation by printer
As a result；
Data memory module is assessed, is connect with central control module, initial data and enterprise for being acquired by memory storage
Industry BIM technology application power quantitative evaluation result；
Display module is assessed, is connect with central control module, for showing the quantization of enterprise B IM technical application ability by display
Assessment result.
5. a kind of enterprise using enterprise B IM technical application ability quantitative estimation method described in claims 1 to 3 any one
BIM collaborative platform.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106682809A (en) * | 2016-11-16 | 2017-05-17 | 上海建工集团股份有限公司 | Enterprise BIM technology application capability quantification assessment method |
| KR20180010679A (en) * | 2016-07-22 | 2018-01-31 | 공주대학교 산학협력단 | System for evaluating technology of company |
| CN108520039A (en) * | 2018-04-02 | 2018-09-11 | 河南大学 | A kind of big data method for optimization analysis |
-
2019
- 2019-01-16 CN CN201910039082.3A patent/CN109816228A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20180010679A (en) * | 2016-07-22 | 2018-01-31 | 공주대학교 산학협력단 | System for evaluating technology of company |
| CN106682809A (en) * | 2016-11-16 | 2017-05-17 | 上海建工集团股份有限公司 | Enterprise BIM technology application capability quantification assessment method |
| CN108520039A (en) * | 2018-04-02 | 2018-09-11 | 河南大学 | A kind of big data method for optimization analysis |
Non-Patent Citations (2)
| Title |
|---|
| 张兵;: "一种用于云计算数据库的数据挖掘方法研究", 控制工程, no. 06, pages 956 - 960 * |
| 李宁;: "基于一致性Hash算法的分布式缓存数据冗余", 软件导刊, no. 01, pages 47 - 50 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110188024A (en) * | 2019-05-30 | 2019-08-30 | 普元信息技术股份有限公司 | The system and method for data managing capacity assessment are realized under big data environment |
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