CN106446941B - Unconventional emergency event dynamic priority method based on Model Matching - Google Patents
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Abstract
The present invention discloses a kind of unconventional emergency event dynamic priority method based on Model Matching, it include: the set using the various key messages rule of key message model identification key message, real-time processing data stream is matched, filters out the key message for meeting rule by matching；Different types of key message, significance level in systems is different, and different key messages are assigned with different numerical value, and the size by assigning numerical value indicates the significance level of key message in systems；Calculate key message frequency, the number occurred in the key message unit time；That is key message rule is in key message time window, every class key message frequency of occurrences；Key message priority, the arithmetic average of key message frequency and weight product, key message frequency and weight are calculated, determines the significance level of key message in systems.
Description
Technical field
The unconventional emergency event dynamic priority method based on Model Matching that the present invention relates to a kind of, belongs to data processing skill
Art field.
Background technique
The Natural Science Fund In The Light committee, China implements " unconventional sudden incidents report research " weight in starting in 2008
Since big project, numerous scholars and scientific worker study unconventional emergency event.
Unconventional emergency event identification and the important link for being the discovery that unconventional emergency event research, scholar and technical work
Person obtains many progress in terms of unconventional emergency event identification and discovery by constantly studying.
It is achieved many in terms of unconventional emergency event research by the effort of numerous scholars and scientific worker
Achievement.In existing research achievement, the research in terms of unconventional emergency event recognition methods and model has a common trait,
The focus point for being exactly these research achievements is algorithm and model itself, how existing research achievement is efficiently applied to believe online
Breath processing, corresponding research are also lacked.
Summary of the invention
Goal of the invention: aiming at the problems existing in the prior art, the data of unconventional emergency event are called pass by the present invention
Key data, critical data correspond to key message, the knowledge of data flow of the emphasis in the processing of unconventional emergency event online information
Not, data weighting, data occur frequency and priority carry out analysis, research, propose it is a kind of based on Model Matching very
Emergency event dynamic priority method is advised, using method proposed by the present invention, is applied at online information for unconventional emergency event
Reason provides a kind of alternative thinking and scheme.
Technical solution: a kind of unconventional emergency event dynamic priority method based on Model Matching, including critical data are known
Not, key message weight calculation, the process that key message frequency calculates and key message priority calculates.
Critical data identification process
Key message model KMODEL: identifying the set of the various key messages rule of key message, to real-time processing number
It is matched according to stream, filters out the key message for meeting rule by matching.
KMODEL=M (KRULE)=x | x ∈ KRULE } (4)
Real-time stream is matched by key message model, is calculated and is identified by key message logic rules, mistake
Filter out the data acquisition system for meeting key message rule.
Key message model is a dynamic model, and in not homologous ray, the recognition rule of key message is different, is passed through
Model configuration file record, description key message rule, construct key message model.
Before identifying critical data, key message model configuration file is loaded and parsed first, is closed
Key information model data MS, key message model data are a key message regular collection, a key message rule parsing
As a result a key message mark is corresponded to.
Key message weight
Key message weight: different types of key message, significance level in systems is different, to different crucial letters
Breath assigns different numerical value, and the size by assigning numerical value indicates the significance level of key message in systems.
Initial data is matched by key message model, identifies that key message, key message are mapped to have
The section of different weights.
Key message weight dynamic change, in not homologous ray, different business, the weighted value of key message is different, leads to
Cross the relationship of key message weight configuration file record, description key message data weighting and key message.
Before identifying critical data, weight configuration file is loaded, weight configuration file is parsed, calculates weight mark
Will obtains weight mark set WS, and WS is put into memory.The specific implementation steps are as follows:
1) weight configuration file is loaded；
2) to weight configuration file into parsing；
3) weight mark is calculated；
4) weight mark is put into memory list.
A kind of corresponding weight mark of weight type, indicates different weight marks by different numerical value (weighted value), leads to
Crossing different weighted values indicates the weight type of different key messages, and the relationship of the two corresponds.
Weight mark configuration file is associated with key message configuration file by key message rule flag.
In conjunction with MS and WS, to original data stream, treated, and data flow is identified, recognition result passes through 1,0 two-value table
Show, 1 indicates that identification data belong to key message, and 0 indicates that identification data are non-critical informations, if data meet key message rule
Then, then identified data are key messages, are not otherwise, algorithm such as (5):
Wherein:
KSnIt is that key message rule starts in recognition cycle into current time, every class key message that system identification goes out
Number set, DATA is identified data, and MS is model data.
Key message frequency
Key message frequency: the number occurred in the key message unit time.That is key message rule is in key message
Between in window, every class key message frequency of occurrences.Frequency formula such as (6):
Pre=FFrequency (KSn, t) and=KSn/t (6)
Wherein:
KSnThe set for the number that every class key message identifies, t be key message rule recognition cycle start to
The time span of current time.
Key message priority
Key message priority: the arithmetic average of key message frequency and weight product, key message frequency and weight, certainly
The significance level of key message in systems is determined.
In a time slice, with the variation of time, the continual analysis of mass data, the priority of key message is not
It is disconnected to change, dynamic adjustment is carried out by the key message priority to visualization display, real-time, preferential display priority is high
Data, be averaged by the product of frequency and weight to key message, mean value is big, and priority is high, and priority data calculates
It is a lasting process, priority dynamic adjusts formula such as (7):
Wherein:
Pre is the frequency of key message, is weight initial value, and WS is weight mark.
In real-time analyzer, mass data in real time, continually enter system, Pri value is big, then key message is excellent
First grade is higher, and data are more crucial.
Detailed description of the invention
Fig. 1 is key message rule and key message relationship model figure；
Fig. 2 is model, key message rule and key message rule flag；
Fig. 3 is that key message is mapped to weight；
Fig. 4 is that key message identifies memory logic chart；
Fig. 5 is clock memory relational graph；
Fig. 6 is key message priority forming process relationship memory figure；
Fig. 7 is threshold method result figure；
Fig. 8 is key message frequency；
Fig. 9 is key message priority.
Specific embodiment
Combined with specific embodiments below, the present invention is furture elucidated, it should be understood that these embodiments are merely to illustrate the present invention
Rather than limit the scope of the invention, after the present invention has been read, those skilled in the art are to various equivalences of the invention
The modification of form falls within the application range as defined in the appended claims.
A kind of unconventional emergency event dynamic priority method based on Model Matching, abbreviation Model Matching dynamic priority algorithm
(PMADP), including critical data identification, key message weight calculation, key message frequency calculate and key message priority meter
The process of calculation.Wherein critical data identifies link, and existing algorithm and model can be used as data recognition rule applied to this hair
Bright method.
Critical data identification process
Key message time window: key message starts to calculate the time interval for being treated as end point to key message, this
It is the lifetime of key message, key message is once processed, and (it is each to obtain that data are identified using key message recognition rule
Class key message calculates the frequency of every class key message by key message frequency calculation formula, designs every class key message
Weight is calculated the priority of every class key message by critical data weight, the frequency of calculating acquisition.) after, the mark of key message
Note will reset to original state.
Key message rule KRULE: identifying the logical relation of key message, and logical relation contains number in real-time stream
According to calculated relationship, incidence relation, judgment criterion, algorithm and computation model with independent function.Logical relation can be divided into:
Simple logic relationship: the only logical relation of single logical operation relationship.
DATA=data | data ∈ R } (1)
In formula (1), R is a kind of simple relation, and DATA is all data acquisition systems for meeting certain relationship R, and formula (1) indicates full
All data acquisition systems of sufficient relationship R.
The production logic of formula (1) may be expressed as:
R—>DATA IF R THEN DATA (2)
Wherein: R is unity logic relationship, and DATA is the data for meeting R relationship.
Compound logic relationship: being passed through by multiple simple logic operation relations or simultaneously, the compositive relation that constitutes such as exclusive or.
In formula (3), R1, R2, R3, R4 are a kind of simple relations, and DATAC is all data acquisition systems for meeting these relationships,
Formula (3) indicates all data acquisition systems for meeting the various combinations of relationship R1, R2, R3, R4.
Key message model KMODEL: identifying the set of the various key messages rule of key message, to real-time processing number
It is matched according to stream, filters out the key message for meeting rule by matching.
KMODEL=x | x ∈ KRULE } (4)
Key message rule and key message model are a point total relationship, the relationship of key message rule and key message model
Such as Fig. 1.Real-time stream is matched by key message model, is calculated and is identified by key message logic rules, filtering
Meet the data acquisition system of key message rule out.
Key message model is a dynamic model, and in not homologous ray, the recognition rule of key message is different, is passed through
Model configuration file record, description key message rule, construct key message model.
Before identifying critical data, key message model configuration file is loaded and parsed first, is closed
Key information model data MS, key message model data are a key message regular collection, a key message rule parsing
As a result a key message mark, resolution logic such as Fig. 2 are corresponded to.
Key message model property:
Key message model is key message regular collection, that is, key message model by numerous key message rules with
The rule composition of these key message rule association relationships is described；
The corresponding key message rule flag of one key message rule, after the load of model configuration file, rule and mark
The one-to-one correspondence of knowledge is indicated in calculator memory.
Key message weight
Key message weight: different types of key message, significance level in systems is different, to different crucial letters
Breath assigns different numerical value, and the size by assigning numerical value indicates the significance level of key message in systems.
Initial data is matched by key message model, identifies that key message, key message are mapped to have
The section of different weights, such as Fig. 3.
Key message weight dynamic change, in not homologous ray, different business, the weighted value of key message is different, leads to
Cross the relationship of key message weight configuration file record, description key message data weighting and key message.
Before identifying critical data, weight configuration file is loaded, weight configuration file is parsed, calculates weight mark
Will obtains weight mark set WS, and WS is put into memory.The specific implementation steps are as follows:
1) weight configuration file is loaded；
2) to weight configuration file into parsing；
3) weight mark is calculated；
4) weight mark is put into memory list.
A kind of corresponding weight mark of weight type, indicates different weight marks by different numerical value (weighted value), leads to
Crossing different weighted values indicates the weight type of different key messages, and the relationship of the two corresponds.Key message and weight type, power
Weight values relationship such as Fig. 4.
Weight mark configuration file is associated with key message configuration file by key message rule flag.
In conjunction with MS and WS, to original data stream, treated, and data flow is identified, recognition result passes through 1,0 two-value table
Show, 1 indicates that identification data belong to key message, and 0 indicates that identification data are non-critical informations, if data meet key message rule
Then, then identified data are key messages, are not otherwise, algorithm such as (5):
Wherein:
KSnIt is that key message rule starts in recognition cycle into current time, every class key message that system identification goes out
Number set, DATA is identified data, and MS is model data.Key message identification memory logic is shown in Fig. 4.
Key message frequency
Key message frequency: the number occurred in the key message unit time.That is key message rule is in key message
Between in window, every class key message frequency of occurrences.Frequency formula such as (6):
Pre=KSn/t (6)
Wherein:
KSnThe set for the number that every class key message identifies, t be key message rule recognition cycle start to
The time span of current time, clock memory relationship are shown in Fig. 5.
Key message priority
Key message priority: the arithmetic average of key message frequency and weight product, key message frequency and weight, certainly
The significance level of key message in systems is determined.
In a time slice, with the variation of time, the continual analysis of mass data, the priority of key message is not
It is disconnected to change, dynamic adjustment is carried out by the key message priority to visualization display, real-time, preferential display priority is high
Data, be averaged by the product of frequency and weight to key message, mean value is big, and priority is high, and priority data calculates
It is a lasting process, priority dynamic adjusts formula such as (7):
Wherein:
Pre is the frequency of key message, is weight initial value, and WS is weight mark, PreiIndicate i-th of key message
Frequency.
In real-time analyzer, mass data in real time, continually enter system, Pri value is big, then key message is excellent
First grade is higher, and data are more crucial, and key message priority forming process relationship memory is shown in Fig. 6.
Experimental analysis
According to the achievement in Nsfc Major project " unconventional sudden incidents report research "
It counts, in 2001 to the 2010 years especially great natural calamities in China, forest fire tops the list.Threshold method is ground in warning system
Study carefully, using one of more method, experiment is compared analysis with threshold method to this algorithm using forest fire as references object.
The processing logic such as formula (8) of threshold method
IF R >=X THEN Doing (8)
If R is more than or equal to X, then doing logical process.In formula 8, X is the threshold value of setting, and R is initial data or various calculations
The end value that method calculates.
Air humidity, temperature, the hydrocarbonaceous amount in air, wind-force, thunder and lightning are to determine an important factor for forest fire occurs.It is gloomy
Cigarette, flame in woods are the direct embodiments of forest fires.
Data configuration situation explanation:
When air humidity: less than 61.6%, it may occur however that fire；
Area and temperature coefficient: R=0.367, P > 0.01, it may occur however that fire；
When hydrocarbonaceous amount in air: greater than 0.2%, Yi Fasheng fire；
When wind-force: less than 2 grade, it may occur however that fire；
When thunder and lightning: greater than 50 kilo-ampere, Yi Yinfa fire；
Cigarette: being fiery point；
Flame: being fiery point.
Area of woods is big, and temperature, humidity, wind-force, gas concentration, cigarette, fiery data change at any time, this just needs sensor
Quantity is more, and acquisition time interval is short, therefore contains much information, and effectively to be monitored to forest fire, and application system needs are accomplished:
Alarm interference is few；
The high integration stress of priority, preferential display.
Data type, weight and threshold value relationship are shown in Table 1.
Air humidity, area and temperature coefficient, hydrocarbonaceous amount, wind-force, thunder and lightning, cigarette, fiery data are constructed by analog form.Phase
Hope experimental data that can reflect as far as possible the actual data change situation an of long period in 200 minutes time dimensions, because
This experimental data has biggish fluctuation.
Fig. 7 is the result of air humidity, area and temperature coefficient, hydrocarbonaceous amount, wind-force, thunder and lightning, cigarette, fiery threshold method.
According to formula 8, using the identical data of Fig. 7, air humidity, area and temperature coefficient, hydrocarbonaceous amount, wind-force, thunder and lightning,
Cigarette, fiery frequency are shown in Fig. 8.
According to formula 9, using the identical data of Fig. 7, air humidity, area and temperature coefficient, hydrocarbonaceous amount, wind-force, thunder and lightning,
Cigarette, fiery priority are shown in Fig. 9.
As seen in Figure 7, using threshold method, alarm interference is more, and key message emphasis does not protrude.
By Fig. 8,9 as can be seen that using new algorithm, invalid warning information is reduced, the information priorities highest of most critical,
It is displayed by priority and pays close attention to.
3.1 data type of table, weight and threshold value relationship
Claims (3)
1. a kind of unconventional emergency event dynamic priority method based on Model Matching, it is characterised in that: know including critical data
Not, key message weight calculation, the process that key message frequency calculates and key message priority calculates；
Critical data identification process
Key message model KMODEL: the set of the various key messages rule of key message is identified, to real-time processing data stream
It is matched, filters out the key message for meeting rule by matching；
Key message weight
Different types of key message, significance level in systems is different, and different key messages are assigned with different numerical value,
Size by assigning numerical value indicates the significance level of key message in systems；
Key message frequency
Key message frequency, the number occurred in the key message unit time；I.e. key message rule is in key message time window
It is interior, every class key message frequency of occurrences；
Key message priority
Key message priority, the arithmetic average of key message frequency and weight product, key message frequency and weight, determine
The significance level of key message in systems；
Before identifying critical data, key message model configuration file is loaded and parsed first, obtains crucial letter
Model data MS is ceased, key message model data is a key message regular collection, a key message rule parsing result
A corresponding key message mark；
Initial data is matched by key message model, identifies that key message, key message are mapped to have difference
The section of weight；Key message weight dynamic change, in not homologous ray, different business, the weighted value of key message is different,
Pass through the relationship of key message weight configuration file record, description key message data weighting and key message；
Before identifying critical data, weight configuration file is loaded, weight configuration file is parsed, calculated weight mark, obtain
Weight mark set WS is obtained, and WS is put into memory；The specific implementation steps are as follows:
1) weight configuration file is loaded；
2) to weight configuration file into parsing；
3) weight mark is calculated；
4) weight mark is put into memory list；
A kind of corresponding weight mark of weight type, indicates different weight marks by different numerical value, passes through different weighted values
Indicate the weight type of different key messages, the relationship of the two corresponds；
Weight mark configuration file is associated with key message configuration file by key message rule flag；
In conjunction with MS and WS, to original data stream, treated, and data flow is identified, recognition result is indicated by 1,0 two-value, 1
Indicate that identification data belong to key message, 0 indicates that identification data are non-critical informations, if data meet key message rule,
Then identified data are key messages, are not otherwise, algorithm such as (5):
Wherein:
KSnIt is that key message rule starts in recognition cycle into current time, the number for every class key message that system identification goes out
Set, DATA is identified data, and MS is model data.
2. the unconventional emergency event dynamic priority method based on Model Matching as described in claim 1, it is characterised in that: frequency
Rate formula such as (6):
Pre=FFrequency (KSn, t) and=KSn/t (6)
Wherein:
KSnIt is the set for the number that every class key message identifies, t is that key message rule starts in recognition cycle to current
The time span of time.
3. the unconventional emergency event dynamic priority method based on Model Matching as claimed in claim 2, it is characterised in that:
In a time slice, as the priority of the variation of time, the continual analysis of mass data, key message is constantly sent out
Changing carries out dynamic adjustment, the high number of real-time, preferential display priority by the key message priority to visualization display
According to being averaged by the product of frequency and weight to key message, mean value is big, and priority is high, and priority data calculating is one
A lasting process, priority dynamic adjustment formula such as (7):
Wherein:
Pre is the frequency of key message, is weight initial value, and WS is weight mark；
In real-time analyzer, mass data in real time, continually enter system, Pri value is big, then key message priority
Higher, data are more crucial.
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