CN103714185B - Subject event updating method base and urban multi-source time-space information parallel updating method - Google Patents
Subject event updating method base and urban multi-source time-space information parallel updating method Download PDFInfo
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- CN103714185B CN103714185B CN201410021559.2A CN201410021559A CN103714185B CN 103714185 B CN103714185 B CN 103714185B CN 201410021559 A CN201410021559 A CN 201410021559A CN 103714185 B CN103714185 B CN 103714185B
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Abstract
The invention discloses a subject event updating method base and an urban multi-source time-space information parallel updating method. Suggested time-space information updating is related to multiple factors such as information sources, data models and dimension, updating methods, updating technological process, quality control and subject events, and a time-space database is updated on the basis of multi-source data integration and abnormal change discovery. On the basis of time-space database updating, a sudden event updating mechanism, an updating method based on subject event linkage and a GPU (Graphic Processing Unit) parallel acceleration updating algorithm are established, so that the dynamic information updating of urban time-space substances and time-space events is realized specific to the requirements of updating content and frequency of time-space information. The subject event updating method base and the urban multi-source time-space information parallel updating method has the advantages that corresponding data and sensors are updated by the GPU parallel updating algorithm according to the judgment and triggering of corresponding subject events, so that major sudden events concerned by users can be discovered while the time-space information of users is kept newest, and technical support can be provided for emergency safety, traffic dispersion and the like in smart cities.
Description
Technical field
The invention belongs to smart city space time information more frontier, it is related to a kind of subject eventses update method storehouse and city is many
Source space time information paralleling update method, particularly to a kind of smart city subject eventses update method storehouse based on subject eventses and
Urban multi-source space time information paralleling update method.
Background technology
The data that various Aeronautics and Astronautics, Photogrammetry and novel sensor obtain, and Internet of Things, mobile Internet, position
Putting the multi-source space time information such as service network is the applications such as current city operational management, construction plan, emergency command and public service
Base support, is to build " smart city " indispensable important component part.With sky vacant lot sensor network build by
Step is perfect, and the city space-time data of collection in worksite and historical accumulation gets more and more, and occurs in that " data magnanimity, information explosion, knowledge
Poor " contradiction situation.The applied research of domestic and international Spatio-Temporal Data Model for Spatial and space-time database is concentrated mainly on land deeds and goes through at present
History changes organization and administration, intelligent transportation and navigation information system, urban climate analysis of environment change, urban development and the soil of data
Ground is using aspects such as simulations, but the Exemplary digital city in building is still a kind of static information city, only on a small quantity
Thematic data to be organized with the global space snapshot of discrete time point or discrete space website long-term sequence, be still difficult to into
Row space-time data efficiently accesses and adapts to various urban issues analysis decision needs.When magnanimity city space-time data is that development is efficient
Empty data management and update method provide opportunity, therefore study the Data renewal mechanism based on ANOMALOUS VARIATIONS finds and are to ensure that number
According to accuracy and Up-to-date state, improve the quality of data, support smart city run important foundation.Simultaneously with gpu hardware
Development, the parallel high-speed based on gpu calculates and also quickly grows, and carries for solving mass data and raising real-time update efficiency in updating
Supply strong support.
Anomaly based on multi-source heterogeneous data in the sensor network of city and data parallel replacement problem are a kind of bases
Ask in the large scale of geography information and expertise, magnanimity, sequential, multi-source, the classification of high uncertainty isomeric data and identification
Topic.For the random multi-source heterogeneous data of magnanimity how automatically analyzing city sensor network acquisition, and combine expertise
Quickly update with database realizing abnormality detection and data parallel, be that the geographical space time information data base of countries in the world all suffers from
" database update " problem.
At present, multi-sensor data free air anomaly detection method substantially can be divided into: the method based on figure is (using visual
The method changed, such as variable cloud and scatterplot, and find abnormal entity from figure), (belonged to using non-space based on the method deviateing
Property value and entity non-spatial attributes meansigma methodss in spatial neighbor domain difference to measure the intensity of anomaly of entity), different based on local
The method (method by local density defines local irrelevance) of normal manner amount, (obtained after space clustering based on the method for cluster
The isolated point obtaining or tuftlet are considered as free air anomaly) etc..For example: " data updates the patent of invention of Patent No. cn102081619a
Method, distribution node and mass storage cluster system ", a kind of patent of invention " efficient magnanimity of Patent No. cn101339570
Remotely-sensed data distributed organization and management method ", the patent of invention of Patent No. cn102332004a is " for Mass Data Management
Data processing method and system ".
Existing update method is directed to the efficient Temporal-spatial data management renewal aspect of subject-oriented, the storage of massive spatio-temporal data
Poor to dynamic object ability to express, management data mode is single, motility is not enough, extensibility has much room for improvement with managing, and
The half structure that big quantity sensor obtains, unstructuredness information are difficult to build efficient index structure and carry out unified management with real time
Scheduling, and current data management focuses primarily upon city entity renewal with renewal, lacks the ANOMALOUS VARIATIONS of subject-oriented event
Discovery and update mechanism, due to there are change identification or the numerous ambiguities defining criterion, are difficult to accomplish that theory is complete and independent,
Logical level, the space-time pyramid body Model under time geography conceptual framework and various time-space relationship model etc. have more flexibly
Reason space-time structure ability to express, but theoretical research work is more than physics realization, and basic structural feature ability to express still has not
Foot.
Different from traditional abnormality detection and free air anomaly detection method, space-time abnormality detection need to take into account spatial entities with
The change of time, it is increasingly complex that although achieving some scattered achievements, but the depth of holistic approach and range are also very not enough,
The not nearly enough maturation of theoretical method of development.In addition to the detection and discovery of event, the fast parallel update algorithm based on gpu is yet
It is not applied to spatiotemporal data update on a large scale.After therefore these Fundamental Geographic Information Databases build up, towards
It is necessary to it is carried out with Dynamic Maintenance and efficient renewal in the application process of theme, to ensure accuracy and the Up-to-date state of data, carry
The quality of high data, more effectively serves the public, and this is the vital task of smart city sustainable operation, is also this patent
Main purpose.
Content of the invention
In order to solve above-mentioned technical problem, the present invention is directed to the multi-source of space time information it is proposed that one kind is based on
The smart city subject eventses update method storehouse of subject eventses and urban multi-source space time information paralleling update method.
The technical solution adopted in the present invention is:
A kind of subject eventses update method storehouse it is characterised in that: include event judgment rule, basis more new regulation and linkage
More new regulation；
Described event judgment rule includes: the conditional judgment rule of subject eventses, subject eventses domain knowledge base, data
Source coupling and the rule associating；
The conditional judgment rule of described subject eventses is: first passes through associated specialist knowledge, including Urban Emergency
Content, the concrete classification of accident and classification foundation, Urban Emergency behavioral standard and relevant professional knowledge, by difference
The accident of type is classified and is modeled, and sets up the cybernetics control number of each different accident, and sets up burst thing
Part mates contingency table with sensor, and different classes of multisensor space-time data and Urban Emergency categorizing system are carried out
Corresponding, quickly to find corresponding Urban Emergency in different space-time datas and to receive the accident of new category
Enter existing Urban Emergency knowledge base, eventually form a dynamic Urban Emergency rule base, such as congestion is provided
Vehicle flowrate threshold values, the basis for estimation of smokescope threshold values class event, determine accident；
Described data source coupling with the rule of association is: provides the corresponding traffic congestion of such as vehicle flowrate, smokescope pair
Answer the corresponding Association repository of fire class event, the linkage for the later stage updates offer linkage rule；
Described basis more new regulation includes: subject eventses update and judge that parameter library, subject eventses update process rule, master
Topic event update detection and evaluation rule；
Described subject eventses update process rule: update subject eventses update method storehouse and process such as traffic congestion pair
Highlighted congested link, information should be had to issue, congested link monitor video extracts the relevant updates operation that class accident produces, bag
Include the display of fresh information, the transmission of fresh information, the statistics of fresh information；.
Described subject eventses update detection and evaluation rule is: by setting up appraisement system, be concordance, completeness inspection
Survey and Termination Analysis provide detection data time tag and precision class function and parameter, mainly correlation is carried out to fresh information
Detection, ensure the verity of fresh information and completeness；
Described linkage more new regulation includes: subject eventses interpolation linkage more new regulation, the linkage of subject eventses parameter update
Rule.
Described subject eventses interpolation linkage more new regulation is: for some point or several point in the sensor of networking
Data variation, by Kriging regression or Natural neighbors interpolation class method enter row information linkage update；
Described subject eventses Parameters variation linkage more new regulation is: the linkage that the special parameter related to sensor is carried out
Update, the relevant information with the change sensor itself of parameter occurs change, therefore when corresponding information change occurs,
Need linkage to update corresponding sensor parameters, adjust sensor states.
A kind of constructive method in subject eventses update method storehouse it is characterised in that: according to urban history accident obtain
Initial magnanimity Urban Emergency set, the expertise in combination with city field and correlative factor are believed to Urban Emergency
Breath carries out systematic generalization and classification, and the key character of all kinds of accidents and the form of expression are described, the completeest
Rule base is included in the city anomalous event set of constituent class, thus obtaining subject eventses update method storehouse.
A kind of urban multi-source space time information paralleling update method in utilization subject eventses update method storehouse it is characterised in that
Comprise the following steps:
Step 1. space-time data cleans: receives the space-time data that sensor passes come, the standard to described space-time data
Really property and real-time are judged, reject error message；
Step 2. subject eventses find: by the conditional judgment rule of subject eventses using city subject eventses classification system
System and semantic analysis technology carry out to the subject eventses in described space-time data finding to judge；
Step 3. subject eventses identify: by subject eventses domain knowledge base with reference to semantic analysis technology to having been found that
Subject eventses carry out type judgement；
The linkage of step 4. space time information updates: after determining subject eventses, according to different sensors data characteristicses, to institute
The space-time data stated carries out part renewal, version updating or update all；
Step 5. Termination Analysis: update detection by subject eventses and evaluation rule enters to the space-time data having updated
Row completeness and concordance judge, judge whether renewal terminates.
Preferably, the subject eventses described in step 2 find, it implements including following sub-step:
Step 2.1. space-time data is classified: by subject eventses categorizing system, according to the good data type ginseng of predefined
According to table, space-time data is classified, described space-time data is carried out classification be to space-time data information according to space time information,
Spatial information, temporal information are classified；Described subject eventses categorizing system is mainly user-defined space-time data information
Type judgment rule, is defined according to the type of space-time, space, time for existing sensor information and data form,
Compare during judgement classification；
Step 2.2. cross-checks: to classified space-time data, the conditional judgment rule using subject eventses is empty to it
Between information detection carried out by its spatial relationship and semantic information to event information discover whether to meet subject eventses occurrence condition,
Its temporal information then carries out detection by time serieses relation pair event information and discovers whether to meet subject eventses occurrence condition, its
Space time information then carry out respectively above detect and carry out space-time crosscheck, judge whether it meets subject eventses occurrence condition；
Step 2.3. subject eventses find: carry out accuracy detection to the space-time data information after detection and remove abnormal data
And mistake, if not finding subject eventses, jump out detection, if finding subject eventses, entering next stage carries out subject eventses
Identification.
Preferably, the subject eventses identification described in step 3, it implements including following sub-step:
Step 3.1. subject eventses are classified: the subject eventses having been found that are carried out point by subject eventses domain knowledge base
Class, classification is classified according to the type of trigger message and attribute；
Step 3.2. subject eventses specificity analysises: subject eventses attribute is divided into spatial event, time-event or space-time thing
Part, the difference according to subject eventses attribute is analyzed to it according to space, semantic relation or time serieses respectively, obtains it empty
Between characteristic or time response, spatio-temporal event is then also needed to carry out space-time alternate analyses to obtain its space-time characterisation；
Step 3.3. subject eventses identify: according to its space-time characterisation of subject eventses, with reference to subject eventses knowledge base, to master
Topic event is identified, and null authentication debug characteristic and mistake when the characteristic of subject eventses is carried out；Described master
Topic event classification knowledge base is that user is described to subject eventses according to space-time characterisation according to expertise and categorizing system
Event dictionary, is mainly used in the identification of subject eventses.
Preferably, the space time information linkage described in step 4 updates, it implements including following sub-step:
Step 4.1. data prepare: subject eventses identification after, by data source coupling with correlation rule will with lead
The related data of topic event is collected, and pushes and is ready for processing into particular memory location, the relative number of subject eventses
According to contrast relationship by User Defined, be stored in renewal rule base, wherein said data source coupling and correlation rule, main
Comprise the corresponding relation of various main particular events and related sensor information；
Step 4.2. updates and judges: judges that the space-time data that parameter library updates to need judges according to updating, root first
Update process rule according to the feature comparison subject eventses of subject eventses and the space-time data that need to update it to be updated judge, choosing
Select parameter linkage to update or interpolation linkage renewal；For the renewal of the single subject eventses of only parameter attribute, enter line sensor
Parameter linkage update；For have view data and have interrelated impact subject eventses renewal enter row interpolation link more
Newly；Described parameter linkage updates the parameter being to link according to parameter and update the sensor to information source for the rule base and carries out correlation
Renewal, mainly by parameter link rule base mate respective sensor, then enter line parameter update；Described interpolation linkage
Renewal is to be linked according to interpolation to update the rule base space-time data related to subject eventses and enter row interpolation, then by after interpolation when
Empty data is updated processing, and wherein interpolation linkage updates the interpolation that rule base comprises space-time data corresponding to corresponding subject eventses
Update method, different themes event data type interpolation method has difference, has user to be defined according to practical situation；
Step 4.3. updates and selects: and then parameter library is judged according to subject eventses renewal, according to updating, space-time data amount is big
Little and data type selects to carry out whole updating or part updates；When space-time data volume is more than threshold values, carry out part renewal, when
When space-time data amount is less than threshold values, then carry out whole updating；Described whole updating is that space-time data is replaced more completely
Newly, described part updates the renewal only carrying out Partial Transformation data；
Step 4.4. accelerates to judge: if described space-time data picture or image class big data quantity picture information, then touches
Send out gpu to accelerate parallel to update, otherwise carry out Termination Analysis；
Step 4.5. Termination Analysis: using subject eventses renewal detection and evaluation rule, space-time data is carried out complete
Property and consistency check, inspection updates the correctness that whether completes and complete.
Preferably, the gpu described in step 4.4 accelerates to update parallel, it implements including following sub-step:
Step 4.4.1: space-time data loading system internal memory will be updated；
Step 4.4.2: space-time data is carried out by block segmentation according to space-time data size；
Step 4.4.3: by incoming for block space-time data gpu internal memory；
Step 4.4.4: the multi-core using gpu carries out parallel computation, mainly to space-time data procession conversion and
Matrix calculus；
Step 4.4.5: judge to update whether conversion completes, if do not complete calculating, described step 4.4.3 of revolution execution,
Otherwise enter next step；
Step 4.4.6: judging whether gpu parallel computation terminates, if not terminating, turning round described step 4.4.2 of execution,
If terminating, carry out next step；
Step 4.4.7: space-time data completes to calculate return system internal memory.
Space time information proposed by the invention update with information source, data model and yardstick, update method, more new technological process,
Quality control is relevant with many factors such as subject eventses, be multisource data fusion (include image class data fusion, image with non-
Image data fusion) and ANOMALOUS VARIATIONS find on the basis of renewal that space-time database is carried out.And build on here basis
The update mechanism of vertical accident, the update mechanism that linked based on subject eventses and gpu accelerate update algorithm, parallel thus being directed to
Space time information update content, the needs of frequency, realize city space-time entity and the multidate information of spatio-temporal event updates.
The space time information of subject-oriented proposed by the invention updates and is updated mainly for the data after merging, for many
Source, multiple dimensioned, multi-time Scales, different semantic environment the collaborative renewal of event linkage: the spy based on the change of multi-source geospatial entity
Point, the operation operator towards collaborative renewal, can achieve (partly) automatically database update；Gridding pipe for urban information
Reason, the method such as research Kriging regression carries out grid local updating and the collaborative update method based on grid；Using gpu simultaneously
Row accelerating algorithm realizes city space time information local updating and whole updating method；Realized using version and active database technology
Collaborative renewal between local multi-source Spatial Data, meets Long routine and (accurate) real-time requirement in renewal process, sets up continuable
Collaborative update mechanism based on event linkage.
The present invention constructs the renewal based on subject eventses of a space-time data being applied to multi-source big data quantity, according to
The judgement of corresponding subject eventses and triggering, by gpu parallel update algorithm, corresponding data and sensor are updated so that
The space time information of user keeps to find, while last state, the vital emergent event that user is concerned about, can be in smart city
Emergent safety and traffic dispersion etc. technical support is provided.
Brief description
Fig. 1: for the subject eventses update method library structure figure of the embodiment of the present invention.
Fig. 2: for the subject eventses method base construction method flow chart of the embodiment of the present invention.
Fig. 3: for the urban multi-source space time information paralleling update method flow chart of the embodiment of the present invention.
Fig. 4: the spatio-temporal event for the embodiment of the present invention finds flow chart.
Fig. 5: for the theme spatio-temporal event identification process figure of the embodiment of the present invention.
Fig. 6: update flow chart for the linkage based on event for the embodiment of the present invention.
Fig. 7: for the gpu parallel algorithms flow chart of the embodiment of the present invention.
Fig. 8: for the theme spatio-temporal event concordance of the embodiment of the present invention, completeness overhaul flow chart.
Specific embodiment
Below with reference to the drawings and specific embodiments, the present invention is further elaborated.
Ask for an interview Fig. 1, a kind of subject eventses update method storehouse of the present invention, including event judgment rule, basis more new regulation
With linkage more new regulation；
Event judgment rule includes: the conditional judgment rule of subject eventses, subject eventses domain knowledge base, data source coupling
With the rule associating；
The conditional judgment rule of subject eventses is: first pass through associated specialist knowledge, including the content of Urban Emergency,
The concrete classification of accident and classification foundation, Urban Emergency behavioral standard and relevant professional knowledge, will be different types of
Accident is classified and is modeled, and sets up the cybernetics control number of each different accident, and sets up accident and biography
The coupling contingency table of sensor, different classes of multisensor space-time data and Urban Emergency categorizing system is carried out corresponding,
Quickly to find corresponding Urban Emergency in different space-time datas and to include the accident of new category
Some Urban Emergency knowledge bases, eventually form a dynamic Urban Emergency rule base, provide such as congestion wagon flow
Amount threshold values, the basis for estimation of smokescope threshold values class event, determine accident；
Data source coupling with the rule of association is: provides the corresponding traffic congestion of such as vehicle flowrate, the corresponding fire of smokescope
The corresponding Association repository of class event, the linkage for the later stage updates offer linkage rule；
Basis more new regulation includes: subject eventses update and judge that parameter library, subject eventses update process rule, subject eventses
Update detection and evaluation rule；
Subject eventses update and process rule and be: subject eventses update method storehouse processes such as traffic congestion to should have highlighted gathering around
Stifled section, information are issued, congested link monitor video extracts the relevant updates operation that class accident produces, including fresh information
Display, the transmission of fresh information, the statistics of fresh information；
Subject eventses update detection and evaluation rule is: by setting up appraisement system, be concordance, completeness detection and end
Only property analysis provides detection data time tag and precision class function and parameter, and mainly fresh information is carried out with the inspection of correlation
Survey, ensure verity and the completeness of fresh information；
Linkage more new regulation includes: subject eventses interpolation linkage more new regulation, subject eventses parameter linkage more new regulation.
Subject eventses interpolation linkage more new regulation is: for the data of some point or several point in the sensor of networking
Change, is updated by the linkage that Kriging regression or Natural neighbors interpolation class method enter row information；The area obtaining as Sensor Network
Domain observation data interpolation typically on the basis of controlling point data obtains, once sample point data changes, corresponding area
Domain observation data also will be updated.
Subject eventses Parameters variation linkage more new regulation is: the linkage that the special parameter related to sensor is carried out updates,
Relevant information with the change sensor itself of parameter occurs change, therefore when corresponding information change, needs
Linkage updates corresponding sensor parameters, adjusts sensor states.
Ask for an interview Fig. 2, the constructive method of subject of the present invention event update method base, obtained according to urban history accident
Initial magnanimity Urban Emergency set, the expertise in combination with city field and correlative factor are believed to Urban Emergency
Breath carries out systematic generalization and classification, and the key character of all kinds of accidents and the form of expression are described, the completeest
Rule base is included in the city anomalous event set of constituent class, thus obtaining subject eventses update method storehouse.
Ask for an interview Fig. 3, the urban multi-source space time information paralleling update method in the utilization subject eventses update method storehouse of the present invention,
Comprise the following steps:
Step 1. space-time data cleans: receive the space-time data that comes of sensor passes, the accuracy to space-time data and
Real-time is judged, rejects error message.
Step 2. subject eventses find: by the conditional judgment rule of subject eventses using city subject eventses classification system
System and semantic analysis technology carry out to the subject eventses in space-time data finding to judge；Ask for an interview Fig. 4, subject eventses find, its tool
Body is realized including following sub-step:
Step 2.1. space-time data is classified: by subject eventses categorizing system, according to the good data type ginseng of predefined
According to table, space-time data is classified, space-time data is carried out with classification is that space-time data information is believed according to space time information, space
Breath, temporal information are classified；Subject eventses categorizing system is mainly user-defined space-time data information type judgment rule,
Existing sensor information and data form are defined according to the type of space-time, space, time, compare during judgement
Classification；
Step 2.2. cross-checks: to classified space-time data, the conditional judgment rule using subject eventses is empty to it
Between information detection carried out by its spatial relationship and semantic information to event information discover whether to meet subject eventses occurrence condition,
Its temporal information then carries out detection by time serieses relation pair event information and discovers whether to meet subject eventses occurrence condition, its
Space time information then carry out respectively above detect and carry out space-time crosscheck, judge whether it meets subject eventses occurrence condition；
Step 2.3. subject eventses find: carry out accuracy detection to the space-time data information after detection and remove abnormal data
And mistake, if not finding subject eventses, jump out detection, if finding subject eventses, entering next stage carries out subject eventses
Identification.
Step 3. subject eventses identify: by subject eventses domain knowledge base with reference to semantic analysis technology to having been found that
Subject eventses carry out type judgement；Ask for an interview Fig. 5, subject eventses identify, it implements including following sub-step:
Step 3.1. subject eventses are classified: the subject eventses having been found that are carried out point by subject eventses domain knowledge base
Class, classification is classified according to the type of trigger message and attribute；
Step 3.2. subject eventses specificity analysises: subject eventses attribute is divided into spatial event, time-event or space-time thing
Part, the difference according to subject eventses attribute is analyzed to it according to space, semantic relation or time serieses respectively, obtains it empty
Between characteristic or time response, spatio-temporal event is then also needed to carry out space-time alternate analyses to obtain its space-time characterisation；
Step 3.3. subject eventses identify: according to its space-time characterisation of subject eventses, with reference to subject eventses knowledge base, to master
Topic event is identified, and null authentication debug characteristic and mistake when the characteristic of subject eventses is carried out；Subject eventses
Domain knowledge base is the event word that user is described to subject eventses according to space-time characterisation according to expertise and categorizing system
Allusion quotation, is mainly used in the identification of subject eventses.
Step 4. space time information linkage update: after determining subject eventses, according to different sensors data characteristicses, pair when
Empty data carries out part renewal, version updating or update all；Ask for an interview Fig. 6, space time information linkage updates, its implement including
Following sub-step:
Step 4.1. data prepare: subject eventses identification after, by data source coupling with correlation rule will with lead
The related data of topic event is collected, and pushes and is ready for processing into particular memory location, the relative number of subject eventses
According to contrast relationship by User Defined, be stored in renewal rule base in, wherein data source coupling and correlation rule, mainly comprise
The corresponding relation of various main particular events and related sensor information；
Step 4.2. updates and judges: judges that the space-time data that parameter library updates to need judges according to updating, root first
Update process rule according to the feature comparison subject eventses of subject eventses and the space-time data that need to update it to be updated judge, choosing
Select parameter linkage to update or interpolation linkage renewal；For the renewal of the single subject eventses of only parameter attribute, such as photographic head
Angle, the parameter linkage entering line sensor updates；For have view data and have interrelated impact subject eventses renewal,
Such as change of temperature, pm2.5 etc., enters row interpolation linkage and updates；Parameter linkage renewal is to be linked according to parameter to update rule base
The renewal of correlation is carried out to the parameter of the sensor of information source, mainly rule base coupling is linked to inductive sensing by parameter
Device, then enters line parameter and updates；It is to be linked according to interpolation to update the rule base space-time related to subject eventses that interpolation linkage updates
Data enters row interpolation, such as Kriging regression, then is updated processing by the space-time data after interpolation, wherein interpolation links more
New regulation storehouse comprises the interpolation update method of space-time data corresponding to corresponding subject eventses, different themes event data type interpolation
Method has difference, has user to be defined according to practical situation；
Step 4.3. updates and selects: and then parameter library is judged according to subject eventses renewal, according to updating, space-time data amount is big
Little and data type selects to carry out whole updating or part updates；When space-time data volume is more than threshold values, carry out part renewal, when
When space-time data amount is less than threshold values, then carry out whole updating；Whole updating is to be replaced renewal, part completely to space-time data
Update the renewal only carrying out Partial Transformation data；
Step 4.4. accelerates to judge: if space-time data picture or image class big data quantity picture information, then triggers gpu
Parallel acceleration updates, and otherwise carries out Termination Analysis；Ask for an interview Fig. 7, gpu accelerates to update parallel, and it implements including following son
Step:
Step 4.4.1: space-time data loading system internal memory will be updated；
Step 4.4.2: space-time data is carried out by block segmentation according to space-time data size；
Step 4.4.3: by incoming for block space-time data gpu internal memory；
Step 4.4.4: the multi-core using gpu carries out parallel computation, mainly to space-time data procession conversion and
Matrix calculus；
Step 4.4.5: judge to update whether conversion completes, if do not complete calculating, turning round execution step 4.4.3, otherwise entering
Enter next step；
Step 4.4.6: judging whether gpu parallel computation terminates, if not terminating, turning round execution step 4.4.2, if terminating
Then carry out next step；
Step 4.4.7: space-time data completes to calculate return system internal memory.
Step 4.5. Termination Analysis: using subject eventses renewal detection and evaluation rule, space-time data is carried out complete
Property and consistency check, inspection updates the correctness that whether completes and complete.Ask for an interview Fig. 8, by the completeness of detection data and
Concordance is evaluated, and determines to update whether terminate.Judge whether data is updated over finishing, and after updating whether with number before
According to type and attribute identical, it is to avoid update mistake.
Step 5. Termination Analysis: update detection using subject eventses and evaluation rule carries out completeness to space-time data
And consistency check, judge whether renewal terminates.
These are only presently preferred embodiments of the present invention, be not intended to limit protection scope of the present invention, therefore, all
Any modification, equivalent substitution and improvement made within the spirit and principles in the present invention etc., should be included in the protection model of the present invention
Within enclosing.
Claims (6)
1. a kind of constructive method in subject eventses update method storehouse it is characterised in that: described subject eventses update method storehouse includes
Event judgment rule, basis more new regulation and linkage more new regulation；
Described event judgment rule includes: the conditional judgment rule of subject eventses, subject eventses domain knowledge base, data source
The rule joined and associate；
The conditional judgment rule of described subject eventses is: first pass through associated specialist knowledge, interior including Urban Emergency
Appearance, the concrete classification of accident and classification foundation, Urban Emergency behavioral standard and relevant professional knowledge, will be dissimilar
Accident classified and modeled, set up the cybernetics control number of each different accident, and set up accident with
The coupling contingency table of sensor, it is right that different classes of multisensor space-time data and Urban Emergency categorizing system are carried out
Should, quickly to find corresponding Urban Emergency in different space-time datas and to include the accident of new category
Existing Urban Emergency knowledge base, eventually forms a dynamic Urban Emergency rule base, provides accident
Basis for estimation, determines accident；The basis for estimation of described accident includes congestion vehicle flowrate threshold values, smokescope threshold values；
Described data source coupling with the rule of association is: provides corresponding Association repository, the linkage for the later stage updates offer connection
Dynamic rule；Described corresponding Association repository content includes vehicle flowrate and corresponds to traffic congestion event, smokescope correspondence event of fire；
Described basis more new regulation includes: subject eventses update and judge that parameter library, subject eventses update process rule, theme thing
Part updates detection and evaluation rule；
Described subject eventses update process rule: subject eventses update method storehouse processes the relevant updates that accident produces
Operation, including the display of fresh information, the transmission of fresh information, fresh information statistics；
Described subject eventses update detection and evaluation rule is: by setting up appraisement system, be concordance, completeness detection and
Termination Analysis provide detection data time tag and precision class function and parameter, and fresh information is carried out with detection, the guarantor of correlation
The verity of card fresh information and completeness；
Described linkage more new regulation includes: subject eventses interpolation linkage more new regulation, subject eventses parameter linkage more new regulation；
Described subject eventses interpolation linkage more new regulation is: for the number of some point or several point in the sensor of networking
According to change, updated by the linkage that Kriging regression or Natural neighbors interpolation class method enter row information；
Described subject eventses parameter linkage more new regulation is: the linkage that the special parameter related to sensor is carried out updates, with
The relevant information the change sensor itself of parameter occurs change, therefore when corresponding information change, needs to join
The corresponding sensor parameters of dynamic renewal, adjust sensor states；
The constructive method in described subject eventses update method storehouse is to obtain initial magnanimity city according to urban history accident to dash forward
Send out event sets, the expertise in combination with city field carries out systematic generalization and classification to Urban Emergency information, and
The key character of all kinds of accidents and the form of expression are described, complete the city anomalous event set classified the most at last
Include rule base, thus obtaining subject eventses update method storehouse.
2. the urban multi-source space time information side of renewal parallel in the subject eventses update method storehouse described in a kind of utilization claim 1
Method is it is characterised in that comprise the following steps:
Step 1. space-time data cleans: receives the space-time data that sensor passes come, the accuracy to described space-time data
And real-time is judged, reject error message；
Step 2. subject eventses find: by the conditional judgment of subject eventses rule using city subject eventses categorizing system and
Semantic analysis technology carries out to the subject eventses in described space-time data finding to judge；
Step 3. subject eventses identify: by subject eventses domain knowledge base with reference to semantic analysis technology to the theme having been found that
Event carries out type judgement；
The linkage of step 4. space time information updates: after determining subject eventses, according to different sensors data characteristicses, to described
Space-time data carries out part renewal, version updating or update all；
Step 5. Termination Analysis: update detection using subject eventses and evaluation rule carries out completeness and one to space-time data
The inspection of cause property, judges whether renewal terminates.
3. method according to claim 2 it is characterised in that: subject eventses described in step 2 find, it implements
Including following sub-step:
Step 2.1. space-time data is classified: by subject eventses categorizing system, according to the good data type reference of predefined
Table, classifies to space-time data, and described classification that space-time data is carried out is according to space time information, sky to space-time data information
Between information, temporal information classified；Described subject eventses categorizing system is that user-defined space-time data information type is sentenced
Disconnected rule, is defined according to the type of space-time, space, time for existing sensor information and data form, during judgement
Compare classification；
Step 2.2. cross-checks: to classified space-time data, the conditional judgment rule using subject eventses is believed to its space
Breath carries out detection by its spatial relationship and semantic information and discovers whether to meet subject eventses occurrence condition, at that time to event information
Between information then detection is carried out by time serieses relation pair event information and discovers whether to meet subject eventses occurrence condition, its space-time
Information then carry out respectively above detect and carry out space-time crosscheck, judge whether it meets subject eventses occurrence condition；
Step 2.3. subject eventses find: carry out accuracy detection to the space-time data information after detection and remove abnormal data and mistake
By mistake, if not finding subject eventses, jumping out detection, if finding subject eventses, entering the identification that next stage carries out subject eventses.
4. method according to claim 2 it is characterised in that: the identification of subject eventses described in step 3, it implements
Including following sub-step:
Step 3.1. subject eventses are classified: by subject eventses domain knowledge base, the subject eventses having been found that classified, point
Class is classified according to the type of trigger message and attribute；
Step 3.2. subject eventses specificity analysises: subject eventses attribute is divided into spatial event, time-event or spatio-temporal event, root
Difference according to subject eventses attribute is analyzed to it according to space, semantic relation or time serieses respectively, obtains its space special
Property or time response, then also need to carry out space-time alternate analyses to obtain its space-time characterisation for spatio-temporal event；
Step 3.3. subject eventses identify: according to its space-time characterisation of subject eventses, with reference to subject eventses knowledge base, to theme thing
Part is identified, and null authentication debug characteristic and mistake when the characteristic of subject eventses is carried out；Described theme thing
Part domain knowledge base is the event that user is described to subject eventses according to space-time characterisation according to expertise and categorizing system
Dictionary, is mainly used in the identification of subject eventses.
5. method according to claim 2 it is characterised in that: the linkage of space time information described in step 4 updates, and it is concrete
Realize including following sub-step:
Step 4.1. data prepare: subject eventses identification after, by data source coupling with correlation rule will with there is theme thing
The related data of part is collected, and pushes and is ready for processing into particular memory location, the relative data of subject eventses
Contrast relationship, by User Defined, is stored in renewal rule base, wherein said data source is mated and correlation rule, main bag
Corresponding relation containing various main particular events and related sensor information；
Step 4.2. updates and judges: judges that the space-time data that parameter library updates to need judges according to updating, first according to master
The feature comparison subject eventses of topic event and the space-time data that need to update update process rule and it are updated judge, select ginseng
Number linkage updates or interpolation linkage updates；For the renewal of the single subject eventses of only parameter attribute, enter the ginseng of line sensor
Number linkage updates；For have view data and have interrelated impact subject eventses renewal enter row interpolation linkage update；Institute
The parameter linkage stated updates the parameter being to link according to parameter and update the sensor to information source for the rule base and carries out correlation more
Newly, it is that respective sensor is mated by parameter linkage rule base, then enter line parameter and update；Described interpolation linkage renewal is root
Update the rule base space-time data related to subject eventses according to interpolation linkage and enter row interpolation, then the space-time data after interpolation is entered
Row renewal is processed, and wherein interpolation linkage updates the interpolation renewal side that rule base comprises space-time data corresponding to corresponding subject eventses
Method, different themes event data type interpolation method has difference, has user to be defined according to practical situation；
Step 4.3. update select: and then according to subject eventses update judge parameter library, according to renewal space-time data amount size and
Data type selects to carry out whole updating or part updates；When space-time data volume is more than threshold values, carries out part renewal, work as space-time
When data volume is less than threshold values, then carry out whole updating；Described whole updating is that space-time data is replaced completely with renewal, institute
The part stated updates the renewal only carrying out Partial Transformation data；
Step 4.4. accelerates to judge: if described space-time data picture or image class big data quantity picture information, then triggers
Gpu accelerates to update parallel, otherwise carries out Termination Analysis；
Step 4.5. Termination Analysis: using subject eventses update detection and evaluation rule space-time data is carried out completeness and
Consistency check, inspection updates the correctness whether completing and completing.
6. method according to claim 5 it is characterised in that: the gpu described in step 4.4 parallel accelerate update, its tool
Body is realized including following sub-step:
Step 4.4.1: space-time data loading system internal memory will be updated；
Step 4.4.2: space-time data is carried out by block segmentation according to space-time data size；
Step 4.4.3: by incoming for block space-time data gpu internal memory；
Step 4.4.4: the multi-core using gpu carries out parallel computation, to the conversion of space-time data procession and matrix calculus；
Step 4.4.5: judge to update whether conversion completes, if do not complete calculating, described step 4.4.3 of revolution execution, otherwise
Enter next step；
Step 4.4.6: judging whether gpu parallel computation terminates, if not terminating, turning round described step 4.4.2 of execution, if knot
Shu Ze carries out next step；
Step 4.4.7: space-time data completes to calculate return system internal memory.
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| CN108256679B (en) * | 2018-01-11 | 2022-04-19 | 福建榕基软件股份有限公司 | Custom event occurrence prediction method and storage medium |
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