CN106709666A - Method and system for determining threshold value of index - Google Patents
Method and system for determining threshold value of index Download PDFInfo
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- CN106709666A CN106709666A CN201710009800.3A CN201710009800A CN106709666A CN 106709666 A CN106709666 A CN 106709666A CN 201710009800 A CN201710009800 A CN 201710009800A CN 106709666 A CN106709666 A CN 106709666A
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Abstract
The application discloses a method for determining a threshold value of an index. The method comprises the following steps: acquiring historical sample sets of the index; determining probability distribution subjected by the historical sample sets to obtain a corresponding distribution function; determining the threshold value of the index by utilizing the distribution function and analyzing the practical significance reflected by the newly-acquired index value by utilizing the threshold value. According to the method disclosed by the application, after the historical sample sets of the index are acquired, the probability distribution subjected by the historical sample set can be determined, then the corresponding distribution function can be obtained, the threshold value of the index can be determined by the distribution function, and since the distribution function reflects the probability distribution rule of the index-value sample sets, the threshold value of the index determined by utilizing the distribution function can be more reasonable and reliable. In addition, the application also correspondingly discloses a system for determining the index threshold value.
Description
Technical field
The present invention relates to index analysis technical field, more particularly to a kind of metrics-thresholds determine method and system.
Background technology
Currently, enterprise is after the development strategy for making itself, it will usually the state of development of itself is carried out in real time with
Track is supervised, to avoid being absorbed in serious development crisis.
In order to realize the tracking supervision to enterprise's self-growth situation, enterprise's common practice is based on prison set in advance
Pipe index, the development process to enterprise is supervised, and so as to obtain current desired value in real time, and then needs to combine finger accordingly
Mark threshold value, the current real-time indicators value to getting is analyzed and evaluated, to determine the state of development level of current enterprise.And
How to determine that rationally reliable metrics-thresholds are that also have problem to be solved at present.
The content of the invention
In view of this, determine method and system it is an object of the invention to provide a kind of metrics-thresholds, be capable of determining that conjunction
Manage reliable metrics-thresholds.Its concrete scheme is as follows：
A kind of metrics-thresholds determine method, including：
Obtain the historical sample collection of index；
Determine the probability distribution that the historical sample collection is obeyed, obtain corresponding distribution function；
Using the distribution function, the threshold value of the index is determined, to analyze the new finger for getting using the threshold value
The practical significance that scale value is reflected.
Optionally, the process of the historical sample collection for obtaining index, including：
The history desired value of the index is gathered and stored, original training set is obtained；
The history desired value produced under identical index generation environment is filtered out from the original training set, institute is obtained
State historical sample collection.
Optionally, the index is the index for reflecting the business finance general level of the health.
Optionally, the process for determining the probability distribution that the historical sample collection is obeyed, including：
Using distributed Fitness Test method, the probability distribution that the historical sample collection is obeyed is determined, obtain the distribution
Function.
Optionally, it is described to utilize the distribution function, determine the process of the threshold value of the index, including：
Using the distribution function, the alarm threshold of the index is determined.
Optionally, it is described to utilize the distribution function, determine the process of the alarm threshold of the index, including：
Determine the pointer type of the index；Wherein, the pointer type of the index is the first kind or Second Type, institute
It is the pointer type of correlation between the numerical values recited warning degree corresponding with desired value of desired value to state the first kind,
The Second Type is the index class of negatively correlated relation between the numerical values recited warning degree corresponding with desired value of desired value
Type；
Using the distribution function, and with reference to the pointer type of the index, determine the alarm threshold of the index.
Determine system the invention also discloses a kind of metrics-thresholds, including：
Sample set acquisition module, the historical sample collection for obtaining index；
Distribution determining module, for determining the probability distribution that the historical sample collection is obeyed, is distributed letter accordingly
Number；
Threshold determination module, for utilize the distribution function, determine the threshold value of the index, with using the threshold value come
The practical significance that the new desired value for getting of analysis is reflected.
Optionally, the sample set acquisition module, including：
Desired value collecting unit, for gathering and stores the history desired value of the index, obtains original training set；
Desired value screening unit, produces for being filtered out from the original training set under identical index generation environment
History desired value, obtain the historical sample collection.
Optionally, the distribution determining module, specifically for using distributed Fitness Test method, determining the historical sample
The obeyed probability distribution of collection, obtains the distribution function.
Optionally, the threshold determination module, including：
Pointer type determining unit, the pointer type for determining the index；Wherein, the pointer type of the index is
The first kind or Second Type, the first kind for desired value numerical values recited warning degree corresponding with desired value between be in
The pointer type of positive correlation, the Second Type is between the numerical values recited warning degree corresponding with desired value of desired value
The pointer type of negatively correlated relation；
Alarm threshold determining unit, for the utilization distribution function, and with reference to the pointer type of the index, determines
The alarm threshold of the index.
In the present invention, metrics-thresholds determine method, including：Obtain the historical sample collection of index；Determine historical sample collection institute
The probability distribution of obedience, obtains corresponding distribution function；Using distribution function, the threshold value of agriculture products, to be divided using threshold value
The practical significance that the new desired value for getting of analysis is reflected.
It can be seen that, the present invention is after the historical sample collection for getting index, it will determine that historical sample collection is obeyed general
Rate is distributed, and obtains corresponding distribution function, and then above-mentioned distribution function determines the threshold value of index, due to reflecting on distribution function
The probability distribution rule of desired value sample, so that more rationally can may be used using the metrics-thresholds that distribution function is determined
Lean on.That is, the present invention is capable of determining that comparing rationally reliable metrics-thresholds.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Inventive embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Fig. 1 determines method flow diagram for a kind of metrics-thresholds disclosed in the embodiment of the present invention；
Fig. 2 determines system structure diagram for a kind of metrics-thresholds disclosed in the embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Determine method the embodiment of the invention discloses a kind of metrics-thresholds, shown in Figure 1, the method includes：
Step S11：Obtain the historical sample collection of index.
It should be noted that the index in the present embodiment is the index for referring to reflect enterprise's self-growth situation, tool
Body, can be the index for reflecting the business finance general level of the health.
Step S12：Determine the probability distribution that historical sample collection is obeyed, obtain corresponding distribution function.
Step S13：Using distribution function, the threshold value of agriculture products, to analyze the new desired value for getting using threshold value
The practical significance for being reflected.
It can be seen that, the embodiment of the present invention is after the historical sample collection for getting index, it will determine that historical sample collection is taken
From probability distribution, obtain corresponding distribution function, then above-mentioned distribution function determines the threshold value of index, due to distribution function
On reflect the probability distribution rule of desired value sample so that can be more using the metrics-thresholds that distribution function is determined
It is rationally reliable.That is, the embodiment of the present invention is capable of determining that comparing rationally reliable metrics-thresholds.
Determine method the embodiment of the invention discloses a kind of specific metrics-thresholds, comprise the following steps：
Step S21：The history desired value of index is gathered and stored, original training set is obtained.
Step S22：The history desired value produced under identical index generation environment is filtered out from original training set, is obtained
To historical sample collection.
Step S23：Using distributed Fitness Test method, the probability distribution that historical sample collection is obeyed is determined, be distributed
Function.
Wherein, above-mentioned distributed Fitness Test method that is to say so-called χ in the prior art2Method of inspection.
In the present embodiment, above-mentioned distribution function can be specifically normal distyribution function, or heavytailed distribution function etc..
Step S24：Using distribution function, the alarm threshold of agriculture products is newly got with being analyzed using alarm threshold
The practical significance that is reflected of desired value.
Specifically, above-mentioned utilization distribution function, the process of the alarm threshold of agriculture products, can include below step S241
And S242：
Step S241：The pointer type of agriculture products；Wherein, the pointer type of index be the first kind or Second Type,
The first kind is the pointer type of correlation between the numerical values recited warning degree corresponding with desired value of desired value, the
Two types are the pointer type of negatively correlated relation between the numerical values recited warning degree corresponding with desired value of desired value.
In the present embodiment, the above-mentioned first kind is the pointer type that desired value is bigger, corresponding situation situation is more serious.And
Above-mentioned Second Type is the pointer type that desired value is smaller, corresponding situation situation is more serious.Certainly, except above two type
Outside, the pointer type of index can also include the 3rd type, specially when desired value is located within a certain interval range, phase
The situation situation answered becomes quite serious pointer type.
Step S242：Using distribution function, and with reference to the pointer type of index, determine the alarm threshold of index.
For example, it is assumed that the pointer type of index be the above-mentioned first kind, then can by above-mentioned distribution function 90% it is general
Desired value corresponding to rate is defined as above-mentioned alarm threshold.
It is understood that in the present embodiment, can be according to the difference of index generation environment, certain the specific finger that will be got
Target original training set is divided into multigroup historical sample collection, then using distributed Fitness Test method, every group of history is determined respectively
The each corresponding distribution function of sample set, it is true followed by each distribution function so as to be correspondingly made available multiple distribution functions
The corresponding alarm threshold under different index generation environments of above-mentioned specific indexes is made, so as to be correspondingly made available multiple warnings
Threshold value.So, after new desired value corresponding with above-mentioned specific indexes is got, will be produced according to the corresponding index of the desired value
Raw environment, finds out corresponding metrics-thresholds, and the above-mentioned new desired value for getting is analyzed using the metrics-thresholds then.
Season, index is produced to produce period and index to produce region etc. in addition, These parameters generation environment includes but is not limited to index.
Further, system is determined the embodiment of the invention also discloses a kind of metrics-thresholds, shown in Figure 2, the system
Including：
Sample set acquisition module 11, the historical sample collection for obtaining index；
Distribution determining module 12, for determining the probability distribution that historical sample collection is obeyed, obtains corresponding distribution function；
Threshold determination module 13, for utilizing distribution function, the threshold value of agriculture products, to analyze new acquisition using threshold value
To the practical significance that is reflected of desired value.
It can be seen that, the embodiment of the present invention is after the historical sample collection for getting index, it will determine that historical sample collection is taken
From probability distribution, obtain corresponding distribution function, then above-mentioned distribution function determines the threshold value of index, due to distribution function
On reflect the probability distribution rule of desired value sample so that can be more using the metrics-thresholds that distribution function is determined
It is rationally reliable.That is, the embodiment of the present invention is capable of determining that comparing rationally reliable metrics-thresholds.
Specifically, above-mentioned sample set acquisition module, including desired value collecting unit and desired value screening unit；Wherein,
Desired value collecting unit, for gathering and stores the history desired value of index, obtains original training set；
Desired value screening unit, for filtered out from original training set under identical index generation environment produce go through
History desired value, obtains historical sample collection.
Further, above-mentioned distribution determining module, specifically for using distributed Fitness Test method, determining historical sample collection
The probability distribution obeyed, obtains distribution function.
In the present embodiment, above-mentioned threshold determination module can specifically include that pointer type determining unit and alarm threshold are true
Order unit；Wherein,
Pointer type determining unit, for the pointer type of agriculture products；Wherein, the pointer type of index is the first kind
Or Second Type, the first kind is correlation between the numerical values recited warning degree corresponding with desired value of desired value
Pointer type, Second Type is the finger of negatively correlated relation between the numerical values recited warning degree corresponding with desired value of desired value
Mark type；
Alarm threshold determining unit, for utilizing distribution function, and with reference to the pointer type of index, determines the police of index
Guard against threshold value.
Finally, in addition it is also necessary to explanation, herein, such as first and second or the like relational terms be used merely to by
One entity or operation make a distinction with another entity or operation, and not necessarily require or imply these entities or operation
Between there is any this actual relation or order.And, term " including ", "comprising" or its any other variant meaning
Covering including for nonexcludability, so that process, method, article or equipment including a series of key elements not only include that
A little key elements, but also other key elements including being not expressly set out, or also include for this process, method, article or
The intrinsic key element of equipment.In the absence of more restrictions, the key element limited by sentence "including a ...", does not arrange
Except also there is other identical element in the process including the key element, method, article or equipment.
Method and system are described in detail to be determined to a kind of metrics-thresholds provided by the present invention above, herein should
Principle of the invention and implementation method are set forth with specific case, the explanation of above example is only intended to help and manages
The solution method of the present invention and its core concept；Simultaneously for those of ordinary skill in the art, according to thought of the invention,
Be will change in specific embodiment and range of application, in sum, this specification content should not be construed as to this hair
Bright limitation.
Claims (10)
1. a kind of metrics-thresholds determine method, it is characterised in that including：
Obtain the historical sample collection of index；
Determine the probability distribution that the historical sample collection is obeyed, obtain corresponding distribution function；
Using the distribution function, the threshold value of the index is determined, to analyze the new desired value for getting using the threshold value
The practical significance for being reflected.
2. the metrics-thresholds based on distributed Fitness Test according to claim 1 determine method, it is characterised in that described
The process of the historical sample collection of index is obtained, including：
The history desired value of the index is gathered and stored, original training set is obtained；
The history desired value produced under identical index generation environment is filtered out from the original training set, described going through is obtained
History sample set.
3. the metrics-thresholds based on distributed Fitness Test according to claim 1 determine method, it is characterised in that described
Index is the index for reflecting the business finance general level of the health.
4. the metrics-thresholds based on distributed Fitness Test according to claim 1 determine method, it is characterised in that described
The process of the probability distribution that the historical sample collection is obeyed is determined, including：
Using distributed Fitness Test method, the probability distribution that the historical sample collection is obeyed is determined, obtain the distribution function.
5. the metrics-thresholds based on distributed Fitness Test according to any one of Claims 1-4 determine method, its feature
It is, it is described to utilize the distribution function, determine the process of the threshold value of the index, including：
Using the distribution function, the alarm threshold of the index is determined.
6. the metrics-thresholds based on distributed Fitness Test according to claim 5 determine method, it is characterised in that described
Using the distribution function, the process of the alarm threshold of the index is determined, including：
Determine the pointer type of the index；Wherein, the pointer type of the index is the first kind or Second Type, described the
One type is the pointer type of correlation between the numerical values recited warning degree corresponding with desired value of desired value, described
Second Type is the pointer type of negatively correlated relation between the numerical values recited warning degree corresponding with desired value of desired value；
Using the distribution function, and with reference to the pointer type of the index, determine the alarm threshold of the index.
7. a kind of metrics-thresholds determine system, it is characterised in that including：
Sample set acquisition module, the historical sample collection for obtaining index；
Distribution determining module, for determining the probability distribution that the historical sample collection is obeyed, obtains corresponding distribution function；
Threshold determination module, for utilizing the distribution function, determines the threshold value of the index, to be analyzed using the threshold value
The practical significance that the new desired value for getting is reflected.
8. metrics-thresholds according to claim 1 determine system, it is characterised in that the sample set acquisition module, including：
Desired value collecting unit, for gathering and stores the history desired value of the index, obtains original training set；
Desired value screening unit, for filtered out from the original training set under identical index generation environment produce go through
History desired value, obtains the historical sample collection.
9. metrics-thresholds according to claim 1 determine system, it is characterised in that
The distribution determining module, specifically for using distributed Fitness Test method, determining what the historical sample collection was obeyed
Probability distribution, obtains the distribution function.
10. the metrics-thresholds according to any one of claim 7 to 9 determine system, it is characterised in that the threshold value determines mould
Block, including：
Pointer type determining unit, the pointer type for determining the index；Wherein, the pointer type of the index is first
Type or Second Type, the first kind for desired value numerical values recited warning degree corresponding with desired value between be in positive
The pointer type of pass relation, the Second Type between the numerical values recited warning degree corresponding with desired value of desired value in negative
The pointer type of dependency relation；
Alarm threshold determining unit, for the utilization distribution function, and with reference to the pointer type of the index, determines described
The alarm threshold of index.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110262947A (en) * | 2018-03-12 | 2019-09-20 | 腾讯科技（深圳）有限公司 | Threshold alarm method, apparatus, computer equipment and storage medium |
| CN110471015A (en) * | 2019-09-05 | 2019-11-19 | 国网北京市电力公司 | Determination method and device, storage medium and the processor of sensor detection threshold |
| CN110969356A (en) * | 2019-12-03 | 2020-04-07 | 浪潮软件股份有限公司 | Method and system for setting index threshold based on normal distribution |
| CN113806420A (en) * | 2021-08-31 | 2021-12-17 | 国网山东省电力公司金乡县供电公司 | Power grid data monitoring method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030079160A1 (en) * | 2001-07-20 | 2003-04-24 | Altaworks Corporation | System and methods for adaptive threshold determination for performance metrics |
| US20030191732A1 (en) * | 2002-04-08 | 2003-10-09 | Lee Shih-Jong J. | Online learning method in a decision system |
| US20070005297A1 (en) * | 2005-06-30 | 2007-01-04 | Oracle International Corporation | Automatic determination of high significance alert thresholds for system performance metrics using an exponentially tailed model |
| CN105069296A (en) * | 2015-08-10 | 2015-11-18 | 国网浙江省电力公司电力科学研究院 | Determination method and system of equipment threshold value |
-
2017
- 2017-01-06 CN CN201710009800.3A patent/CN106709666A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030079160A1 (en) * | 2001-07-20 | 2003-04-24 | Altaworks Corporation | System and methods for adaptive threshold determination for performance metrics |
| US20030191732A1 (en) * | 2002-04-08 | 2003-10-09 | Lee Shih-Jong J. | Online learning method in a decision system |
| US20070005297A1 (en) * | 2005-06-30 | 2007-01-04 | Oracle International Corporation | Automatic determination of high significance alert thresholds for system performance metrics using an exponentially tailed model |
| CN105069296A (en) * | 2015-08-10 | 2015-11-18 | 国网浙江省电力公司电力科学研究院 | Determination method and system of equipment threshold value |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110262947A (en) * | 2018-03-12 | 2019-09-20 | 腾讯科技（深圳）有限公司 | Threshold alarm method, apparatus, computer equipment and storage medium |
| CN110262947B (en) * | 2018-03-12 | 2022-05-17 | 腾讯科技（深圳）有限公司 | Threshold warning method and device, computer equipment and storage medium |
| CN110471015A (en) * | 2019-09-05 | 2019-11-19 | 国网北京市电力公司 | Determination method and device, storage medium and the processor of sensor detection threshold |
| CN110969356A (en) * | 2019-12-03 | 2020-04-07 | 浪潮软件股份有限公司 | Method and system for setting index threshold based on normal distribution |
| CN113806420A (en) * | 2021-08-31 | 2021-12-17 | 国网山东省电力公司金乡县供电公司 | Power grid data monitoring method and device |
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Application publication date: 20170524 |