CN105718432B - It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data - Google Patents
It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data Download PDFInfo
- Publication number
- CN105718432B CN105718432B CN201610147354.8A CN201610147354A CN105718432B CN 105718432 B CN105718432 B CN 105718432B CN 201610147354 A CN201610147354 A CN 201610147354A CN 105718432 B CN105718432 B CN 105718432B
- Authority
- CN
- China
- Prior art keywords
- data
- quality
- calibration
- operation equipment
- format
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/14—Tree-structured documents
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/151—Transformation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/174—Form filling; Merging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/186—Templates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/189—Automatic justification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
Abstract
The invention discloses the method for calibration of a kind of information excavating for grid operation equipment and the quality of data, (1) writes literature source file；(2) literature source file is executed；(3) report or the presentation file of specified format are generated；(4) data check；(5) visualization verification.Through the above way, the present invention is for the information excavating of grid operation equipment and the method for calibration of the quality of data by using literary programming, machine learning techniques, data visualization, improve analysis efficiency, save human cost, the objectivity for guaranteeing analysis verification report and trackability, is intuitive and easy to understand convenient for repeatable research, the checkability for improving abnormal data, analysis mode, the information excavating and quality of data for grid operation equipment method of calibration it is universal on have extensive market prospects.
Description
Technical field
The present invention relates to the field of information management of grid equipment, more particularly to a kind of information for grid operation equipment
Excavate the method for calibration with the quality of data.
Background technique
The production management of power grid, the relevant sorts of systems such as asset of equipments, operation and maintenance have it is a large amount of static with it is dynamic
State information, and the inaccuracy in these information, imperfection, non-timely equal is always that quite a few regional power grid is public
Take charge of the hard nut to crack faced in information management.With the construction of smart grid, a large amount of new equipment, intelligence sensor
Installation, mass data pours in so that the problem of electric network information quality it is more serious with it is urgent, do not grasp it is complete, accurately, and
When, the power grid asset information of high quality, the intelligent of power grid is run, and maintenance and management is not just known where to begin.
The prior art includes following defect or deficiency:
(1) data analysis report writes inefficiency: at present due to business there is an urgent need in order to understand device data
Internal feature improves data accuracy, the method taken manual analysis selective examination more, write report again.It specifically includes: system administration
Member's inquiry and preprocessed data, equipment manager or business expert combine professional knowledge to carry out Manual analysis to data, then each
A analysis result one by one " copy-paste " into report, not only efficiency is lower in this way, there is also problem of misalignment and data,
Method, result three update the problems such as asynchronous.Tedious due to operating, primary analysis can not cover data comprehensively, report
Update cycle is long, also more difficult to adhere to for a long time, therefore can not be known the real situation comprehensively running equipment information, and intractable can not be also eradicated
Data quality problem；
(2) data system entrance lacks advanced verifying function: the input interface in data management system is integrated with one at present
A little simple rules, lack in-depth analysis ability, are difficult integrated complex inspection rule and expertise；
(3) data visualization diagrammatic representation ability is limited: at present in data quality management, applying in report and system
Visual Chart is less, and currently existing scheme is mainly the fundamental figure using institute's band in some spreadsheet softwares and information system
Function lacks excavation to incidence relation complicated in multidimensional data and demonstrates one's ability.
Summary of the invention
The invention mainly solves the technical problem of providing a kind of information excavatings for grid operation equipment and data matter
The method of calibration of amount carries out data analysis and quality of data school by using the method based on repeatable research and literary programming
It tests, data processing and analysis work is realized using R language and its expansion plugin, can configure a variety of customized verification combination rule
Then, to meet the complicated check logic configuration needs for combining domain knowledge and historical problem, by machine learning model algorithm application
Into the verification of the grid equipment quality of data, data visualization method is applied in the verification of the grid equipment quality of data, is realized
The depth of the running equipment quality of data knows the real situation, mitigates the lengthy and tedious work proofreaded by hand, improves assets comprehensively in production management system
The quality of data, the efficiency for improving information system management reduce the relevant cost of labor of the quality of data in information system in turn, are also
Advanced analysis application based on asset data provides important leverage, in the information excavating and the quality of data for grid operation equipment
Method of calibration it is universal on have extensive market prospects.
In order to solve the above technical problems, the present invention provides a kind of information excavating and the quality of data for grid operation equipment
Method of calibration, comprising the following steps:
(1) literature source file is write:
The literature source file includes rnw format and Rmd format, and the literature source file includes document template and journey
Sequence；
(2) literature source file is executed:
Running tool executes literature source file and is automatically performed built-in program, executes reading data, pretreatment and data
Analytical procedure, and report text and the calculated result turn that is returned by described program of format description from the document module
It is changed to a kind of markup language, while the Visual Chart of Program Generating is saved as the picture file of specified format；
(3) report or the presentation file of specified format are generated:
Corresponding markup language crossover tool is run, picture is automatically inserted into and generates report or the demonstration text of specified format
Shelves；
(4) data check:
The verification of the grid equipment quality of data is carried out using machine learning model, the machine learning model includes local regression
Model and local outlier factor model,
The local regression model using etc. ranges estimation model come the Reasonable Parameters range of pre- measurement equipment, then and actual number
According to comparing,
The outlier indexs models such as the local outlier factor model use, calculate " outlier index " of each data sample,
The higher sample of outlier index has a possibility that data quality problem bigger；
(5) visualization verification:
The verification of the grid equipment quality of data is carried out using data visualization method.
In a preferred embodiment of the present invention, the literature source file of the rnw format in step (1) uses Sweave
Analysis report is automatically generated with pdfLaTeX crossover tool.
In a preferred embodiment of the present invention, the literature source file of the Rmd format in step (1) uses knitr
Analysis report is automatically generated with Pandoc crossover tool.
In a preferred embodiment of the present invention, the document template in step (1) includes document format and narrative
Text, the paragraph inside of the narrative text includes number and text that described program generates, in order to automatic according to data
The text paragraph containing statistical result is generated, the document module further includes that individual paragraph is reserved for program operation result, is used
In table and chart that insertion program generates.
In a preferred embodiment of the present invention, the described program in step (1) include automated data importing program,
Liquidation procedures, conversion program and analysis program, in conjunction with the device data quality indicator method of domain knowledge experience, in analytic process
The middle data detection rule for incorporating previous experiences, described program also call machine learning and visualization expanding packet to carry out high fraction
It analyses, the program output in the literature source file includes number, text, table and chart.
In a preferred embodiment of the present invention, the markup language in step (2) is LaTeX or Markdown.
In a preferred embodiment of the present invention, the markup language of LaTeX format is called in step (3)
PdfLaTeX crossover tool generates pdf formatted file.
In a preferred embodiment of the present invention, the markup language of Markdown format is called in step (3)
Pandoc crossover tool generates the report of a variety of file formats, including the docx file general with Word, pdf file and fits
Html file for browser.
In a preferred embodiment of the present invention, step (2) and step (3) use processing mode or batch processing one by one
Mode.
In a preferred embodiment of the present invention, the data visualization method in step (5) includes parallel coordinate system
Method.
The beneficial effects of the present invention are: the present invention is for the information excavating of grid operation equipment and the verification side of the quality of data
Method improves analysis efficiency, saves human cost, guarantees to divide by using literary programming, machine learning techniques, data visualization
It is the objectivity and trackability of analysis verification report, straight convenient for repeatable research, the checkability for improving abnormal data, analysis mode
See it is understandable, the information excavating and quality of data for grid operation equipment method of calibration it is universal on have extensive market
Prospect.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing, in which:
Fig. 1 is of the invention for the information excavating of grid operation equipment and the preferably implementation of method of calibration one of the quality of data
The flow chart that analysis report is automatically generated based on Sweave and LaTeX of the literature source file of the rnw format of example；
Fig. 2 is of the invention for the information excavating of grid operation equipment and the preferably implementation of method of calibration one of the quality of data
The literature source file of the Rmd format of example automatically generates the flow chart of analysis report or presentation file based on knitr and Pandoc；
Fig. 3 is of the invention for the information excavating of grid operation equipment and the preferably implementation of method of calibration one of the quality of data
The schematic diagram using local regression model identification abnormal data of example；
Fig. 4 is of the invention for the information excavating of grid operation equipment and the preferably implementation of method of calibration one of the quality of data
The schematic diagram using local outlier factor model identification abnormal data of example；
Fig. 5 is of the invention for the information excavating of grid operation equipment and the preferably implementation of method of calibration one of the quality of data
Example carries out visual schematic diagram to multidimensional grid equipment data using parallel coordinate system.
Specific embodiment
The technical scheme in the embodiments of the invention will be clearly and completely described below, it is clear that described implementation
Example is only a part of the embodiments of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, this field is common
Technical staff's all other embodiment obtained without making creative work belongs to the model that the present invention protects
It encloses.
Fig. 1-Fig. 5 is please referred to, the embodiment of the present invention includes:
It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data, comprising the following steps:
(1) literature source file is write:
The literature source file includes rnw format and Rmd format, and the literature source file includes document template and journey
Sequence；
(2) literature source file is executed:
Running tool executes literature source file and is automatically performed built-in program, executes reading data, pretreatment and data
Analytical procedure, and report text and the calculated result turn that is returned by described program of format description from the document module
It is changed to a kind of markup language, while the Visual Chart of Program Generating is saved as the picture file of specified format；
(3) report or the presentation file of specified format are generated:
Corresponding markup language crossover tool is run, picture is automatically inserted into and generates report or the demonstration text of specified format
Shelves；
(4) data check:
The verification of the grid equipment quality of data is carried out using machine learning model, the machine learning model includes local regression
Model and local outlier factor model,
The local regression model using etc. ranges estimation model come the Reasonable Parameters range of pre- measurement equipment, then and actual number
According to comparing,
The outlier indexs models such as the local outlier factor model use, calculate " outlier index " of each data sample,
The higher sample of outlier index has a possibility that data quality problem bigger；
(5) visualization verification:
The verification of the grid equipment quality of data is carried out using data visualization method.
Preferably, the literature source file of the rnw format in step (1) uses Sweave and pdfLaTeX crossover tool
Automatically generate analysis report.
Preferably, the literature source file of the Rmd format in step (1) uses knitr and Pandoc crossover tool certainly
It is dynamic to generate analysis report.
Preferably, the document template in step (1) includes document format and narrative text, the narrative text
Paragraph inside include described program generate number and text, in order to automatically generate the text containing statistical result according to data
Field is fallen, and the document module further includes reserving individual paragraph for program operation result, the table generated for insertion program
And chart.
Preferably, the described program in step (1) includes the importing program of automated data, liquidation procedures, conversion program
Previous experiences are incorporated in the analysis process in conjunction with the device data quality indicator method of domain knowledge experience with analysis program
Data detection rule, described program also call machine learning and visualization expanding packet to carry out advanced analysis, the literature source document
Program output in part includes number, text, table and chart.
Preferably, the markup language in step (2) is LaTeX or Markdown.
Preferably, pdfLaTeX crossover tool is called for the markup language of LaTeX format in step (3), generates pdf
Formatted file.
Preferably, Pandoc crossover tool is called for the markup language of Markdown format in step (3), generated more
The report of kind file format, including the docx file general with Word, pdf file and for viewing on the html file of device.
Preferably, step (2) and step (3) are using processing mode or batch processing mode one by one.
Preferably, the data visualization method in step (5) includes parallel coordinate system method.
In recent years, with the rise of big data research, academia and industrial circle the problem of the quality of data at home and abroad are all
High attention is obtained.For data analysis cleaning, data check, data exception analysis, data visualization, literature program with
And repeatable statistical research has in-depth study and is widely applied.Such as: using various statistical models, visualization means can
With the association and exception in flexible display data.Repeatable statistical research can also greatly improve the accuracy of data analysis, visitor
The property seen and trackability, the operation of automation, which is also convenient for the long-term follow quality of data, improves situation.
The present invention relates to background technique specifically include that
1, it repeats research (Reproducible research): referring in data analysis, be together with original number
It saves and issues together according to, process and code, convenient for verifying and trace in this way as a result, simultaneously improving on this basis.
2, literature programming (Literate programming): this is the programmed method proposed by Gao Dena, literature programming
Pattern is different from traditional computer program, but writes literature source file first, is then therefrom obtained using literature programming tool
Two kinds of expression ways, one kind are further compiled and are executed for computer, referred to as " lay out " code of (tangled), one
Kind is used for formatted document, and (woven) " is referred to as woven " from literature source code.Note: in the present invention, literature source file includes
Two kinds of formats of rnw and Rmd, corresponding two kinds of implementations.
3, a kind of R: language and operating environment for statisticalling analyze, drawing.
4, Sweave: being an expanding packet of R language, and function is that the function of R is integrated into LaTeX.So as to
Dynamic statement and document are generated, when data or analysis change, report and document can automatically derive update.
5, LaTeX: being a kind of composing system based on TeX, is highly suitable for generating the science and technology and mathematics of high printing quality
Class document.
6, pdfLaTeX: LaTeX is converted into the tool of pdf document.
7, a kind of knitr: R language extension packet of dynamic autoization report.
8, Markdown: a kind of lightweight markup language allows people to write text using the plain text format that readability is easily write
Shelves, are then converted into effective extended formatting document.
9, Pandoc: markup language crossover tool can also carry out difference, it can be achieved that by marking output for formatted document
Format conversion between markup language.
10, local regression model: it is a kind of nonparametric, nonlinear regression algorithm, combines traditional linear regression
The flexibility of terseness and nonlinear regression.
11, local outlier factor model: a kind of unsupervised learning model is detected for data exception, can be from detected number
Note abnormalities sample automatically in, without understanding the distribution characteristics of data in advance, does not carry out any hypothesis to data.
12, parallel coordinates: a kind of method for visualizing, suitable for the visualization to high dimensional data.
Beneficial effect of the present invention for the information excavating of grid operation equipment and the method for calibration of the quality of data is:
One, data analysis and quality of data school are carried out by using the method based on repeatable research and literary programming
It tests, improves analysis efficiency, save human cost, automatic binding analysis result and report, avoid after analysis manual Import Reports again
It malfunctions in the process, guarantee that the objectivity that analysis verification is reported, trackability convenient for repeatable research, ensure that data, analysis side
Method and the consistency of report, the readability for improving analysis program code, convenient for safeguarding and improving program in the future；
Two, by using machine learning techniques in quality of data verification, increase in existing Deterministic rules and in logic and examine
Dimension is tested, the identification ratio of Upgrade Problem data, reduces labor workload at the checkability for improving abnormal data, saves artificial
The cost of analysis；
Three, by using data visualization in the quality of data verifies, abnormal data is recognized using the help of visualization means,
The internal characteristics that analysis mode is intuitive and easy to understand, allows production management personnel to understand facility information rapidly by visualization means.
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 is applied directly or indirectly in other relevant technology necks
Domain is included within the scope of the present invention.
Claims (10)
1. a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data, which is characterized in that including following
Step:
(1) literature source file is write:
The literature source file includes rnw format and Rmd format, and the literature source file includes document template and program；
(2) literature source file is executed:
Running tool executes literature source file and is automatically performed built-in program, executes reading data, pretreatment and data analysis
Step, and from the document template report text and format describe to be converted to by the calculated result that described program returns
A kind of markup language, while the Visual Chart of Program Generating saved as the picture file of specified format；
(3) report or the presentation file of specified format are generated:
Corresponding markup language crossover tool is run, picture is automatically inserted into and generates report or the presentation file of specified format；
(4) data check:
The verification of the grid equipment quality of data is carried out using machine learning model, the machine learning model includes local regression model
With local outlier factor model,
The local regression model using etc. ranges estimation model come the Reasonable Parameters range of pre- measurement equipment, then with real data into
Row comparison,
The outlier indexs models such as the local outlier factor model use, calculate " outlier index " of each data sample, peel off
The higher sample of index has a possibility that data quality problem bigger；
(5) visualization verification:
The verification of the grid equipment quality of data is carried out using data visualization method.
2. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is that the literature source file of the rnw format in step (1) is automatically generated using Sweave and pdfLaTeX crossover tool
Analysis report, wherein Sweave: being an expanding packet of R language.
3. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is, the literature source file of the Rmd format in step (1) is automatically generated point using knitr and Pandoc crossover tool
A kind of analysis report, wherein knitr: R language extension packet of dynamic autoization report.
4. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is, the document template in step (1) includes document format and narrative text, in the paragraph of the narrative text
Portion includes the number and text that described program generates, in order to automatically generate the text paragraph containing statistical result according to data,
The document template further includes reserving individual paragraph for program operation result, the table and chart generated for insertion program.
5. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is that the described program in step (1) includes importing program, liquidation procedures, conversion program and the analysis journey of automated data
Sequence incorporates the data detection of previous experiences in conjunction with the device data quality indicator method of domain knowledge experience in the analysis process
Rule, described program also call machine learning and visualization expanding packet to carry out advanced analysis, the journey in the literature source file
Sequence output includes number, text, table and chart.
6. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is that the markup language in step (2) is LaTeX or Markdown.
7. it is according to claim 6 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is, for the markup language of LaTeX format in step (3), calls pdfLaTeX crossover tool, generates pdf formatted file.
8. it is according to claim 6 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is, for the markup language of Markdown format in step (3), calls Pandoc crossover tool, generates a variety of trays
The report of formula, including the docx file general with Word, pdf file and for viewing on the html file of device.
9. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is that step (2) and step (3) are using processing mode or batch processing mode one by one.
10. it is according to claim 1 for the information excavating of grid operation equipment and the method for calibration of the quality of data, it is special
Sign is that the data visualization method in step (5) includes parallel coordinate system method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610147354.8A CN105718432B (en) | 2016-03-16 | 2016-03-16 | It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610147354.8A CN105718432B (en) | 2016-03-16 | 2016-03-16 | It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105718432A CN105718432A (en) | 2016-06-29 |
| CN105718432B true CN105718432B (en) | 2019-02-01 |
Family
ID=56157737
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610147354.8A Active CN105718432B (en) | 2016-03-16 | 2016-03-16 | It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105718432B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108280561A (en) * | 2017-01-06 | 2018-07-13 | 重庆邮电大学 | A kind of discrete manufacture mechanical product quality source tracing method based on comentropy and Weighted distance |
| CN106980523A (en) * | 2017-04-06 | 2017-07-25 | 裴克铭管理咨询（上海）有限公司 | Visualization tool automates update mechanism |
| CN109873790A (en) * | 2017-12-04 | 2019-06-11 | 中国电信股份有限公司 | Network security detection method, device and computer readable storage medium |
| CN109145269A (en) * | 2018-06-27 | 2019-01-04 | 国网浙江省电力有限公司 | A kind of automatic generating method and system of power grid fortune prison data analysis report |
| CN109766536A (en) * | 2018-12-27 | 2019-05-17 | 国网上海市电力公司 | A kind of realization device based on model customizationization report |
| CN110399363B (en) * | 2019-06-25 | 2023-02-28 | 云南电网有限责任公司玉溪供电局 | Problem data full life cycle data quality management method and system |
| CN111125073A (en) * | 2019-12-05 | 2020-05-08 | 苏宁云计算有限公司 | Method, device and system for verifying data quality of big data platform |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1394313A (en) * | 2000-11-02 | 2003-01-29 | 密刻爱你有限公司 | Method for embedding and extracting text into/from electronic documents |
| US7305129B2 (en) * | 2003-01-29 | 2007-12-04 | Microsoft Corporation | Methods and apparatus for populating electronic forms from scanned documents |
| CN102918494A (en) * | 2010-04-06 | 2013-02-06 | 贾斯通数据库有限公司 | Data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data strorage and access models |
| JP2013061853A (en) * | 2011-09-14 | 2013-04-04 | Toshiba Corp | Process monitoring/diagnosis support device |
| CN103778234A (en) * | 2014-01-26 | 2014-05-07 | 北京恒华伟业科技股份有限公司 | Report form generating method and device |
| CN104267610A (en) * | 2014-08-29 | 2015-01-07 | 内蒙古科技大学 | High-precision blast furnace smelting process abnormal data detection and repair method |
-
2016
- 2016-03-16 CN CN201610147354.8A patent/CN105718432B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1394313A (en) * | 2000-11-02 | 2003-01-29 | 密刻爱你有限公司 | Method for embedding and extracting text into/from electronic documents |
| US7305129B2 (en) * | 2003-01-29 | 2007-12-04 | Microsoft Corporation | Methods and apparatus for populating electronic forms from scanned documents |
| CN102918494A (en) * | 2010-04-06 | 2013-02-06 | 贾斯通数据库有限公司 | Data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data strorage and access models |
| JP2013061853A (en) * | 2011-09-14 | 2013-04-04 | Toshiba Corp | Process monitoring/diagnosis support device |
| CN103778234A (en) * | 2014-01-26 | 2014-05-07 | 北京恒华伟业科技股份有限公司 | Report form generating method and device |
| CN104267610A (en) * | 2014-08-29 | 2015-01-07 | 内蒙古科技大学 | High-precision blast furnace smelting process abnormal data detection and repair method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105718432A (en) | 2016-06-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105718432B (en) | It is a kind of for the information excavating of grid operation equipment and the method for calibration of the quality of data | |
| CN110362894B (en) | Distribution line and transformer comprehensive loss reduction and energy saving calculation analysis method and system | |
| Münch et al. | Software project control centers: concepts and approaches | |
| CN108446190A (en) | interface test method and device | |
| Ali et al. | A design of an assessment system for UML class diagram | |
| CN108717356B (en) | Metering holographic visual display method and device | |
| CN110119272A (en) | A kind of human-machine interface configuration design method and device | |
| CN110134596A (en) | The generation method and terminal device of test document | |
| Coates et al. | New concepts of Post Occupancy Evaluation (POE) utilizing BIM benchmarking techniques and sensing devices | |
| Charfi et al. | RITA: a useR Interface evaluaTion frAmework | |
| CN116596483A (en) | Bridge construction organization method based on three-dimensional digital technology | |
| CN105653777A (en) | Intelligent mapping system of general survey of underground power line | |
| CN104281523A (en) | Demand testability analysis method and system | |
| CN108038332B (en) | On-line graph model rapid generation method for future-state power grid | |
| CN115686280A (en) | Deep learning model management system, method, computer device and storage medium | |
| CN104331361A (en) | A test device and method for performing white-box testing on coverage calculation visualization | |
| CN104123138A (en) | Rapid building method for ERP system | |
| CN109271691B (en) | Automatic extraction and quick labeling method for key characteristics | |
| CN111611665A (en) | Intelligent substation design method based on three-dimensional modular design | |
| Stinner et al. | Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams | |
| CN108205086A (en) | Monitoring method, device and system for power grid equipment | |
| Zorn et al. | Replacing energy simulations with surrogate models for design space exploration | |
| CN116029018A (en) | BIM-based interior decoration design and dynamic optimization method | |
| Ullah et al. | Industrial Energy Management System: Design of a Conceptual Framework Using IoT and Big Data | |
| CN112949003A (en) | Part measuring method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |