CN109766331A - Method for processing abnormal data and device - Google Patents
Method for processing abnormal data and device Download PDFInfo
- Publication number
- CN109766331A CN109766331A CN201811487113.3A CN201811487113A CN109766331A CN 109766331 A CN109766331 A CN 109766331A CN 201811487113 A CN201811487113 A CN 201811487113A CN 109766331 A CN109766331 A CN 109766331A
- Authority
- CN
- China
- Prior art keywords
- data
- range
- pending
- abnormal
- exceptional value
- 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.)
- Pending
Links
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000012545 processing Methods 0.000 title claims abstract description 40
- 238000001514 detection method Methods 0.000 claims abstract description 14
- 238000004590 computer program Methods 0.000 claims description 18
- 230000015654 memory Effects 0.000 claims description 17
- 238000012360 testing method Methods 0.000 claims description 11
- 238000012937 correction Methods 0.000 claims description 7
- 238000010586 diagram Methods 0.000 description 14
- 230000006870 function Effects 0.000 description 9
- 230000008569 process Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
Landscapes
- Debugging And Monitoring (AREA)
Abstract
The present invention provides a kind of method for processing abnormal data and device, this method is applied to technical field of data processing, which comprises obtains pending data；Normal data range is determined according to the pending data and default abnormal index；The exceptional value of the pending data is determined according to the normal data range；The exceptional value is modified according to the normal data range.Method for processing abnormal data and device provided by the invention can be realized the quick detection and amendment of pending data exceptional value.
Description
Technical field
The invention belongs to technical field of data processing, are to be related to a kind of method for processing abnormal data and dress more specifically
It sets.
Background technique
In reality, since mistake or natural mistake will lead to generation data outliers, in the environment of multi-data source
Under, there is data exception and generate the probability of data collision greatly increasing.How to handle these exceptional values is data cleansing institute
The important topic faced.
In data handling, especially when making Function Fitting, the appearance of abnormal point not only can significantly change function
The effect of fitting, and the gradient of function can also be made unusual gradient occur sometimes, it is easy to lead to the termination of algorithm, thus shadow
Ring the functional relation between research variable.In order to effectively avoid loss caused by these abnormal points, it would be desirable to take certain
Method it is handled.But in the case where multi-data source, big data quantity, lack a kind of detection exceptional value in the prior art
And to the method that exceptional value is quickly handled.
Summary of the invention
The purpose of the present invention is to provide a kind of method for processing abnormal data and devices, existing in the prior art to solve
The technical issues of dealing of abnormal data can not quickly be carried out.
The embodiment of the present invention in a first aspect, providing a kind of method for processing abnormal data, which comprises
Obtain pending data；
Normal data range is determined according to the pending data and default abnormal index；
The exceptional value of the pending data is determined according to the normal data range；
The exceptional value is modified according to the normal data range.
The second aspect of the embodiment of the present invention, provides a kind of dealing of abnormal data device, and described device includes:
Data acquisition module, for obtaining pending data；
Range determination module, for determining normal data range according to the pending data and default abnormal index；
Detection module, for determining the exceptional value of the pending data according to the normal data range；
Correction module, for being modified according to the normal data range to the exceptional value.
The third aspect of the embodiment of the present invention, provides a kind of terminal device, including memory, processor and is stored in
In the memory and the computer program that can run on the processor, when the processor executes the computer program
The step of realizing above-mentioned method for processing abnormal data.
The fourth aspect of the embodiment of the present invention, provides a kind of computer readable storage medium, described computer-readable to deposit
Storage media is stored with computer program, and the computer program realizes above-mentioned method for processing abnormal data when being executed by processor
The step of.
The beneficial effect of method for processing abnormal data and device provided by the invention is: abnormal data provided by the invention
Processing method and processing device first passes through pending data and default abnormal index establishes normal data range, further according to normal data model
It encloses and exceptional value is screened and is corrected, to realize the quick detection and processing to abnormal data.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without creative efforts, can also be attached according to these
Figure obtains other attached drawings.
Fig. 1 is the flow diagram for the method for processing abnormal data that one embodiment of the invention provides；
Fig. 2 be another embodiment of the present invention provides method for processing abnormal data flow diagram；
Fig. 3 is the flow diagram for the method for processing abnormal data that yet another embodiment of the invention provides；
Fig. 4 is the flow diagram for the method for processing abnormal data that further embodiment of this invention provides；
Fig. 5 is the flow diagram for the method for processing abnormal data that further embodiment of this invention provides；
Fig. 6 is the structural block diagram for the dealing of abnormal data device that one embodiment of the invention provides；
Fig. 7 is the schematic block diagram for the terminal device that one embodiment of the invention provides.
Specific embodiment
In order to which technical problems, technical solutions and advantages to be solved are more clearly understood, tie below
Accompanying drawings and embodiments are closed, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein is only
To explain the present invention, it is not intended to limit the present invention.
Referring to FIG. 1, the flow diagram of the method for processing abnormal data provided for one embodiment of the invention.This method packet
It includes:
S101: pending data is obtained.
In the present embodiment, the method for pending data is obtained are as follows: obtain first according to the structure setting of pending data
Label obtains pending data further according to label is obtained.For example, database can be used directly for structural data
The data major key name of middle storage is referred to as obtaining label progress data acquisition.For semi-structured and unstructured data, directly
Data are carried out in batches, carry out data acquisition using batch number as label is obtained.
S102: normal data range is determined according to pending data and default abnormal index.
In the present embodiment, it is first determined the first quantile of pending data Q1With the second quantile Q2, wherein first point
Digit, which meets, has the data value of a% less than the first quantile in pending data, the second quantile meets in pending data
There is the data value of a% to be greater than the second quantile.QrFor quantile spacing, meet Qr=Q2-Q1.If default abnormal index K table
Show, then normal data range is [Q1-KQr, Q2+KQr].Wherein, the value of a is set according to specific needs.
S103: the exceptional value of pending data is determined according to normal data range.
In the present embodiment, if the testing data in pending data is not within the scope of normal data, by the number to be measured
According to being determined as exceptional value.
S104: exceptional value is modified according to normal data range.
It in the present embodiment, include but is not limited to the average value used within the scope of normal data to the processing method of exceptional value
Exceptional value is modified, exceptional value is modified using the average value of normal data range, median, without Corrections Division
Reason etc..Specific processing mode can determine according to the purposes of data, if use the data as data source, exceptional value will not be to calculation
The convergence result of method has an impact, then before using that data can be without correcting process.If using the data as data
When source, exceptional value can the output result to algorithm produce bigger effect, then consider to be modified exceptional value using average value.
As can be seen from the above description, method for processing abnormal data provided in an embodiment of the present invention first passes through pending data and pre-
If abnormal index establishes normal data range, exceptional value is screened and corrected further according to normal data range, to realize
Quick detection and processing to abnormal data.
Please also refer to Fig. 1 and Fig. 2, Fig. 2 is the process for the method for processing abnormal data that another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, this method further include:
S201: default abnormal index and intensity of anomaly corresponding relationship are established.
In the present embodiment, it presets abnormal index and the corresponding relationship of intensity of anomaly can be as follows:
If default abnormal index is 1.5, intensity of anomaly is determined as mile abnormality.
If default abnormal index is 2.0, intensity of anomaly is determined as moderate abnormality.
If default abnormal index is 3.0, intensity of anomaly is determined as extremely abnormal.
A kind of specific reality please also refer to Fig. 1 and Fig. 2, as method for processing abnormal data provided in an embodiment of the present invention
Apply mode.On the basis of the above embodiments, step S102 is described in detail are as follows:
S202: normal data range is determined according to pending data and default abnormal index.
S203: the corresponding intensity of anomaly of normal data range is determined according to corresponding relationship.
In the present embodiment, every kind of intensity of anomaly all corresponds to a default abnormal index, can calculate separately every kind of abnormal journey
Spend corresponding normal data range.The corresponding criterion numeral of each default abnormal index first can also be calculated according to default abnormal index
According to range, the corresponding abnormal journey of every group of normal data range is determined further according to default abnormal index and the corresponding relationship of intensity of anomaly
Degree.
As can be seen from the above description, the judgment method of intensity of anomaly provided in this embodiment can be quick in progress abnormal data
The accuracy of detection is improved while detection.
Please also refer to Fig. 1 and Fig. 3, Fig. 3 is the process for the method for processing abnormal data that yet another embodiment of the invention provides
Schematic diagram determines normal data range according to pending data and default abnormal index on the basis of the above embodiments, packet
It includes:
S301: the maximum estimated value and least estimated of pending data are determined according to pending data and default abnormal index
Value.
In the present embodiment, it is first determined the first quantile of pending data Q1With the second quantile Q2, wherein first point
Digit, which meets, has the data value of a% to be greater than the first quantile in pending data, the second quantile meets in pending data
There is the data value of a% less than the second quantile.QrFor quantile spacing, meet Qr=Q2-Q1.If default abnormal index K table
Show, maximum estimated value is Q2+KQr, minimum estimate Q1-KQr.Wherein, the value of a is set according to specific needs.
S302: normal data range is determined according to maximum estimated value and minimum estimate.
In the present embodiment, if maximum estimated value is Q2+KQr, minimum estimate Q1-KQr, then normal data range be
[Q1-KQr, Q2+KQr]。
Please also refer to Fig. 1 and Fig. 4, Fig. 4 is the process for the method for processing abnormal data that the another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, step S104 is described in detail are as follows:
S401: if the testing data in pending data is not within the scope of normal data, it is determined that testing data is abnormal
Value.
In the present embodiment, there is no restricted requirement to the data distribution form of testing data, as long as in pending data
Testing data not within the scope of normal data, then judge the detection data for exceptional value.
S402: the intensity of anomaly of exceptional value is determined according to corresponding relationship.
In the present embodiment, it is preset according to used in the available determining normal data range of aforesaid standards data area
Abnormal index can judge the intensity of anomaly of current exceptional value according to the corresponding relationship of default abnormal index and intensity of anomaly.
Please also refer to Fig. 1 to Fig. 5, Fig. 5 is the process for the method for processing abnormal data that the another embodiment of the application provides
Schematic diagram.On the basis of the above embodiments, above-mentioned steps S105 is described in detail are as follows:
S501: it if there are linear relationships for the data in pending data, is linearly repaired using exceptional value as missing values
It mends.
In the present embodiment, if there are linear relationships for the testing data in pending data, when there is exceptional value, direct root
The mapping value of the corresponding parameter value is linearly calculated according to parameter value corresponding with exceptional value, using this mapping value as amendment
Value replacement exceptional value.Wherein, if linearly being calculated, first to there are the data of linear relationship to carry out linearly in pending data
Fitting obtains linear fit curve, and the mapping value of corresponding parameter value is linearly calculated further according to the linear fit curve.
S502: if linear relationship is not present in the data in pending data, according to the median pair of normal data range
Exceptional value is modified.
In the present embodiment, if linear relationship is not present in the testing data in pending data, standard can be used directly
The median of data area or the average value of pending data replace exceptional value as correction value.If pending data is as number
When according to carrying out model training when source, training pattern is insensitive to the exceptional value in pending data, then can be without exceptional value
Amendment.
Corresponding to the method for processing abnormal data of foregoing embodiments, Fig. 6 is the abnormal data that one embodiment of the invention provides
The structural block diagram of processing unit.For ease of description, only parts related to embodiments of the present invention are shown.With reference to Fig. 6, the dress
Set includes: data acquisition module 10, range determination module 20, detection module 30 and correction module 40.
Wherein, data acquisition module 10, for obtaining pending data.
Range determination module 20, for determining normal data range according to pending data and default abnormal index.
Detection module 30, for determining the exceptional value of pending data according to normal data range.
Correction module 40, for being modified according to normal data range to exceptional value.
With reference to Fig. 6, in another embodiment of the present invention, dealing of abnormal data device further include:
Corresponding relation building module 50, for establishing default abnormal index and intensity of anomaly corresponding relationship.
With reference to Fig. 6, in yet another embodiment of the present invention, range determination module 20 includes:
Range determination unit 21, for determining normal data range according to pending data and default abnormal index.
Intensity of anomaly determination unit 22, for determining the corresponding intensity of anomaly of normal data range according to corresponding relationship.
With reference to Fig. 6, in yet another embodiment of the present invention, range determination unit 21 includes:
Estimated value determining device 211, for determining pending data most according to pending data and default abnormal index
Big estimated value and minimum estimate.
Ranges determination device 212, for determining normal data range according to maximum estimated value and minimum estimate.
With reference to Fig. 6, in yet another embodiment of the present invention, detection module 30 includes:
First detection unit 31, if for the testing data in pending data not within the scope of normal data, it is determined that
Testing data is exceptional value.
Second detection unit 32, for determining the intensity of anomaly of exceptional value according to corresponding relationship.
With reference to Fig. 6, in yet another embodiment of the present invention, correction module 40 includes:
Linear repairing unit 41, if there are linear relationships for the data in pending data, using exceptional value as scarce
Mistake value is linearly repaired.
Amending unit 42, if linear relationship is not present for the data in pending data, according to normal data range
Median exceptional value is modified.
Referring to Fig. 7, Fig. 7 is a kind of schematic block diagram for terminal device that one embodiment of the invention provides.Sheet as shown in Figure 7
Terminal 600 in embodiment may include: one or more processors 601, one or more input equipments 602, one or more
A output equipment 603 and one or more memories 604.Above-mentioned processor 601, input equipment 602, then output equipment 603 and
Memory 604 completes mutual communication by communication bus 605.Memory 604 is for storing computer program, computer journey
Sequence includes program instruction.Processor 601 is used to execute the program instruction of the storage of memory 604.Wherein, processor 601 is configured
For operating the function of each module/unit in above-mentioned each Installation practice, such as mould shown in Fig. 6 below caller instruction execution
The function of block 10 to 50.
It should be appreciated that in embodiments of the present invention, alleged processor 601 can be central processing unit (Central
Processing Unit, CPU), which can also be other general processors, digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components etc..General processor can be microprocessor or this at
Reason device is also possible to any conventional processor etc..
Input equipment 602 may include that Trackpad, fingerprint adopt sensor (for acquiring the finger print information and fingerprint of user
Directional information), microphone etc., output equipment 603 may include display (LCD etc.), loudspeaker etc..
The memory 604 may include read-only memory and random access memory, and to processor 601 provide instruction and
Data.The a part of of memory 604 can also include nonvolatile RAM.For example, memory 604 can also be deposited
Store up the information of device type.
In the specific implementation, processor 601 described in the embodiment of the present invention, input equipment 602, output equipment 603 can
Execute realization described in the first embodiment and second embodiment of method for processing abnormal data provided in an embodiment of the present invention
The implementation of terminal described in the embodiment of the present invention also can be performed in mode, and details are not described herein.
A kind of computer readable storage medium is provided in another embodiment of the invention, and computer readable storage medium is deposited
Computer program is contained, computer program includes program instruction, and above-described embodiment side is realized when program instruction is executed by processor
All or part of the process in method can also instruct relevant hardware to complete by computer program, and computer program can
It is stored in a computer readable storage medium, the computer program is when being executed by processor, it can be achieved that above-mentioned each method
The step of embodiment.Wherein, computer program includes computer program code, and computer program code can be source code shape
Formula, object identification code form, executable file or certain intermediate forms etc..Computer-readable medium may include: that can carry meter
Any entity or device of calculation machine program code, recording medium, USB flash disk, mobile hard disk, magnetic disk, CD, computer storage, only
Read memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electricity load
Wave signal, telecommunication signal and software distribution medium etc..It should be noted that the content that computer-readable medium includes can root
Increase and decrease appropriate is carried out according to the requirement made laws in jurisdiction with patent practice, such as in certain jurisdictions, according to vertical
Method and patent practice, computer-readable medium do not include be electric carrier signal and telecommunication signal.
Computer readable storage medium can be the internal storage unit of the terminal of aforementioned any embodiment, such as terminal
Hard disk or memory.Computer readable storage medium is also possible to the External memory equipment of terminal, such as the grafting being equipped in terminal
Formula hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card
(Flash Card) etc..Further, computer readable storage medium can also both include the internal storage unit of terminal or wrap
Include External memory equipment.Computer readable storage medium is for storing other program sum numbers needed for computer program and terminal
According to.Computer readable storage medium can be also used for temporarily storing the data that has exported or will export.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware
With the interchangeability of software, each exemplary composition and step are generally described according to function in the above description.This
A little functions are implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Specially
Industry technical staff can use different methods to achieve the described function each specific application, but this realization is not
It is considered as beyond the scope of this invention.
It is apparent to those skilled in the art that for convenience of description and succinctly, the end of foregoing description
The specific work process at end and unit, can refer to corresponding processes in the foregoing method embodiment, details are not described herein.
In several embodiments provided herein, it should be understood that disclosed terminal and method can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of unit, only
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.In addition, it is shown or discussed it is mutual it
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of device or unit
It connects, is also possible to electricity, mechanical or other form connections.
Unit may or may not be physically separated as illustrated by the separation member, shown as a unit
Component may or may not be physical unit, it can and it is in one place, or may be distributed over multiple networks
On unit.It can select some or all of unit therein according to the actual needs to realize the mesh of the embodiment of the present invention
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, is also possible to two or more units and is integrated in one unit.It is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.
More than, only a specific embodiment of the invention, but scope of protection of the present invention is not limited thereto, and it is any to be familiar with
Those skilled in the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or substitutions,
These modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be wanted with right
Subject to the protection scope asked.
Claims (10)
1. a kind of method for processing abnormal data characterized by comprising
Obtain pending data；
Normal data range is determined according to the pending data and default abnormal index；
The exceptional value of the pending data is determined according to the normal data range；
The exceptional value is modified according to the normal data range.
2. method for processing abnormal data as described in claim 1, which is characterized in that further include:
Establish default abnormal index and intensity of anomaly corresponding relationship.
3. method for processing abnormal data as claimed in claim 2, which is characterized in that described according to the pending data and pre-
If abnormal index determines normal data range, comprising:
Normal data range is determined according to the pending data and default abnormal index；
The corresponding intensity of anomaly of the normal data range is determined according to the corresponding relationship.
4. method for processing abnormal data as claimed in claim 1 or 3, which is characterized in that described according to the pending data
Normal data range is determined with default abnormal index, comprising:
The maximum estimated value and least estimated of the pending data are determined according to the pending data and default abnormal index
Value；
Normal data range is determined according to the maximum estimated value and the minimum estimate.
5. method for processing abnormal data as claimed in claim 3, which is characterized in that described true according to the normal data range
The exceptional value of the fixed pending data, comprising:
If the testing data in the pending data is not within the scope of the normal data, it is determined that the testing data is different
Constant value；
The intensity of anomaly of the exceptional value is determined according to the corresponding relationship.
6. method for processing abnormal data as described in claim 1, which is characterized in that described according to the normal data range pair
The exceptional value is modified, comprising:
If there are linear relationships for the data in the pending data, linearly repaired using the exceptional value as missing values
It mends；
If linear relationship is not present in the data in the pending data, according to the median of the normal data range to institute
Exceptional value is stated to be modified.
7. a kind of dealing of abnormal data device characterized by comprising
Data acquisition module, for obtaining pending data；
Range determination module, for determining normal data range according to the pending data and default abnormal index；
Detection module, for determining the exceptional value of the pending data according to the normal data range；
Correction module, for being modified according to the normal data range to the exceptional value.
8. dealing of abnormal data device as claimed in claim 7, which is characterized in that further include:
Corresponding relation building module, for establishing default abnormal index and intensity of anomaly corresponding relationship.
9. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as claim 1 to 6 when executing the computer program
The step of any one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 6 of realization the method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811487113.3A CN109766331A (en) | 2018-12-06 | 2018-12-06 | Method for processing abnormal data and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811487113.3A CN109766331A (en) | 2018-12-06 | 2018-12-06 | Method for processing abnormal data and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109766331A true CN109766331A (en) | 2019-05-17 |
Family
ID=66450700
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811487113.3A Pending CN109766331A (en) | 2018-12-06 | 2018-12-06 | Method for processing abnormal data and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109766331A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110716928A (en) * | 2019-09-09 | 2020-01-21 | 上海凯京信达科技集团有限公司 | Data processing method, device, equipment and storage medium |
| CN110955650A (en) * | 2019-11-20 | 2020-04-03 | 云南电网有限责任公司电力科学研究院 | Cleaning method for out-of-tolerance data of digital hygrothermograph in standard laboratory |
| CN110990388A (en) * | 2019-11-29 | 2020-04-10 | 东软睿驰汽车技术（沈阳）有限公司 | Data processing method and device |
| CN112652363A (en) * | 2020-12-30 | 2021-04-13 | 杭州博日科技股份有限公司 | Melting curve abnormal value processing method and device and electronic equipment |
| CN113569006A (en) * | 2021-06-17 | 2021-10-29 | 国家电网有限公司 | Large-scale data quality anomaly detection method based on data characteristics |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104281779A (en) * | 2014-09-26 | 2015-01-14 | 宁波绮耘软件有限公司 | Abnormal data judging and processing method and device |
| CN107273530A (en) * | 2017-06-28 | 2017-10-20 | 南京理工大学 | Important ship target dynamic monitoring method based on internet information |
| CN107808221A (en) * | 2017-10-31 | 2018-03-16 | 中国地质大学（武汉） | Blast furnace material distribution Parameter Decision Making method based on case matching |
| CN107908744A (en) * | 2017-11-16 | 2018-04-13 | 河南中医药大学 | A kind of method of abnormality detection and elimination for big data cleaning |
| CN108280119A (en) * | 2017-11-29 | 2018-07-13 | 广州市动景计算机科技有限公司 | Page generation method, device and user terminal |
| CN108809977A (en) * | 2018-06-08 | 2018-11-13 | 电子科技大学 | A kind of distributing optical fiber sensing big data real-time statistics compression method |
| CN108829535A (en) * | 2018-06-08 | 2018-11-16 | 上海擎创信息技术有限公司 | Data processing method, terminal and computer readable storage medium |
| CN108868805A (en) * | 2018-06-08 | 2018-11-23 | 西安电子科技大学 | Shield method for correcting error based on statistical analysis in conjunction with XGboost |
-
2018
- 2018-12-06 CN CN201811487113.3A patent/CN109766331A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104281779A (en) * | 2014-09-26 | 2015-01-14 | 宁波绮耘软件有限公司 | Abnormal data judging and processing method and device |
| CN107273530A (en) * | 2017-06-28 | 2017-10-20 | 南京理工大学 | Important ship target dynamic monitoring method based on internet information |
| CN107808221A (en) * | 2017-10-31 | 2018-03-16 | 中国地质大学（武汉） | Blast furnace material distribution Parameter Decision Making method based on case matching |
| CN107908744A (en) * | 2017-11-16 | 2018-04-13 | 河南中医药大学 | A kind of method of abnormality detection and elimination for big data cleaning |
| CN108280119A (en) * | 2017-11-29 | 2018-07-13 | 广州市动景计算机科技有限公司 | Page generation method, device and user terminal |
| CN108809977A (en) * | 2018-06-08 | 2018-11-13 | 电子科技大学 | A kind of distributing optical fiber sensing big data real-time statistics compression method |
| CN108829535A (en) * | 2018-06-08 | 2018-11-16 | 上海擎创信息技术有限公司 | Data processing method, terminal and computer readable storage medium |
| CN108868805A (en) * | 2018-06-08 | 2018-11-23 | 西安电子科技大学 | Shield method for correcting error based on statistical analysis in conjunction with XGboost |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110716928A (en) * | 2019-09-09 | 2020-01-21 | 上海凯京信达科技集团有限公司 | Data processing method, device, equipment and storage medium |
| CN110955650A (en) * | 2019-11-20 | 2020-04-03 | 云南电网有限责任公司电力科学研究院 | Cleaning method for out-of-tolerance data of digital hygrothermograph in standard laboratory |
| CN110990388A (en) * | 2019-11-29 | 2020-04-10 | 东软睿驰汽车技术（沈阳）有限公司 | Data processing method and device |
| CN112652363A (en) * | 2020-12-30 | 2021-04-13 | 杭州博日科技股份有限公司 | Melting curve abnormal value processing method and device and electronic equipment |
| CN113569006A (en) * | 2021-06-17 | 2021-10-29 | 国家电网有限公司 | Large-scale data quality anomaly detection method based on data characteristics |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109766331A (en) | Method for processing abnormal data and device | |
| CN109726198A (en) | Method for processing abnormal data and device | |
| CN109766393A (en) | Abnormal deviation data examination method and device | |
| CN109753991A (en) | Abnormal deviation data examination method and device | |
| CN109740630A (en) | Method for processing abnormal data and device | |
| CN110069353A (en) | Business asynchronous processing method and device | |
| CN110365703A (en) | Internet-of-things terminal abnormal state detection method, apparatus and terminal device | |
| CN107766040A (en) | A kind of method, apparatus and computer-readable recording medium for generating interface document | |
| CN109962855A (en) | A kind of current-limiting method of WEB server, current-limiting apparatus and terminal device | |
| CN108830632A (en) | A kind of integration managing method, block chain node device and client | |
| CN110322582A (en) | Lightguide cable link method for inspecting, device and terminal device | |
| CN109788461A (en) | Bluetooth dual mode data communication means and device | |
| CN107463348A (en) | Web ends user-defined format print method and system are realized based on B/S frameworks | |
| CN109597745A (en) | Method for processing abnormal data and device | |
| CN109085811B (en) | Equipment point inspection method and device | |
| CN110196404A (en) | A kind of metering chip calibration method, device and the terminal device of charging pile | |
| CN108243407A (en) | A kind of method and terminal device of multiple wireless module device network interface managements | |
| CN110059856A (en) | Parts Inventory optimization method and device | |
| CN107784596A (en) | Insurance kind state information statistics method, terminal device and the storage medium of declaration form | |
| CN109685479A (en) | A kind of methods of exhibiting, computer installation and the computer readable storage medium of construction tunnel progress | |
| CN111966712A (en) | Data processing method, device, server and storage medium | |
| CN108733799A (en) | A kind of method for processing report data, device and terminal | |
| CN109522457A (en) | Data capture method and device | |
| CN109739838A (en) | Method for processing abnormal data and device | |
| CN108255950A (en) | Date storage method and terminal device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |