CN107292517A - The civil aviaton's security information service system analyzed based on big data - Google Patents
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- CN107292517A CN107292517A CN201710477539.XA CN201710477539A CN107292517A CN 107292517 A CN107292517 A CN 107292517A CN 201710477539 A CN201710477539 A CN 201710477539A CN 107292517 A CN107292517 A CN 107292517A
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- 238000007794 visualization technique Methods 0.000 claims abstract description 4
- 238000012800 visualization Methods 0.000 claims description 8
- 238000009825 accumulation Methods 0.000 claims description 6
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Abstract
The invention discloses the civil aviaton's security information service system analyzed based on big data, including big data memory cell, data acquisition unit, analysis engine, Tupu unit, machine learning engine and query unit；The data acquisition unit is used to gather original service data, and by the original service data Cun Chudao big data memory cell；The analysis engine is analyzed based on original service data, obtains the warning information relevant with paying close attention to personnel；The Tupu unit leads the visualization technique of figure using chart database and power, restores the character relation network for the personnel of paying close attention to；The machine learning engine is used to provide the analysis engine, Tupu unit required algorithm model in the course of the work；The query unit is used to provide fuzzy query and characteristic key based on the concern key element related to public security, civil aviaton.
Description
Technical field
The present invention relates to big data processing technology field, the civil aviaton's security information service more particularly to analyzed based on big data
System.
Background technology
The important trip mode that commercial air flights are people is taken at present, how to realize and commercial air flights are taken to criminal
Effective monitoring, threat of the personnel at risk to flight safety how is found in time, the weight as public security department and the concern of civil aviaton unit
Point.
At present, the data of each concern key element of public security and civil aviaton are in disorder scattered, and data class is more, storage is big, new data
Produce fast, it is difficult to realize the timely and effective analysis to lawless people stroke, public security department and civil aviaton using the data of each department
Unit is difficult to make fast and accurate response for criminal.
The content of the invention
To solve the above problems, the invention provides a kind of civil aviaton's security information service system analyzed based on big data,
It can carry out collection of illustrative plates reduction focusing on people, the comprehensive behavior for restoring people and pass according to public security and the data of civil aviaton
It is train of thought, safety check, the real-time concern early warning for data of booking tickets can be realized, responds in time, accurately for lawless people, from
And the effective monitoring that commercial air flights are taken to criminal is realized, threat of the criminal to flight safety is excluded in time.
The present invention uses following technical scheme：
Based on big data analyze civil aviaton's security information service system, including big data memory cell, data acquisition unit,
Analysis engine, Tupu unit, machine learning engine and query unit, wherein：
The data acquisition unit is used to gather original service data, and by the original service data Cun Chudao big datas
Memory cell, the original service data include civil aviaton's ticket booking data, airport security data, public security data and pay close attention to people
Member's list data；
The analysis engine is analyzed based on original service data, obtains the early warning letter relevant with paying close attention to personnel
Breath；
The Tupu unit leads the visualization technique of figure using chart database and power, restores the personage for the personnel of paying close attention to
Relational network；
The machine learning engine is used to provide the analysis engine, Tupu unit required algorithm mould in the course of the work
Type, the machine learning engine realizes that it includes Data Mining module, data prediction based on spark distributed computing frameworks
Module, model training module, model evaluation module, model visualization module and model prediction module, the Data Mining module
For carrying out distribution statisticses, correlation analysis, hypothesis testing and Density Estimator to data, the data preprocessing module is used for
Data are cleaned, changed, are loaded, feature extraction and feature selecting, the model evaluation module is used for having trained
Model is estimated, and the visualization that the model visualization module is used for implementation model shows that the model prediction module is used for
By mold curing to production environment, real time propelling movement information of forecasting and generation analysis and suggestion report；
The query unit is used to provide fuzzy query and feature inspection based on the concern key element related to public security, civil aviaton
Rope.
Preferably, in addition to map retrieval unit, the map retrieval unit be used for the retrieval that map level is provided and with
Track is analyzed, and is tracked with the movement track for realizing the personnel that pay close attention to.
Preferably, the Tupu unit includes HDFS file system, chart database engine and application layer, the HDFS files
The HBASE database that is stored with system and Solrcloud indexes, the chart database engine include data and index accumulation layer,
Database layer and ClientAPI layers, the data and index accumulation layer and the HBASE database and Solrcloud index phases
Even, described ClientAPI layers is connected with the application layer, and the application layer is used to provide massive relation computing, magnanimity retrieval, closed
It is association, manual drawing, GIS integration, real-time relationship computing, relational extensions, characteristic query, attribute collection and map analysis.
Preferably, the analysis engine includes staff list management module and early warning value computing module, the staff list
Management module is used for piping off, the personal information of paying close attention to of Red List is managed, the early warning value computing module
The warning information relevant with paying close attention to personnel is calculated based on ralation method.
Preferably, in addition to artificial drawing unit, the artificial drawing unit be used to supplementing by hand character relation data with
And management service character relation data.
After adopting the above technical scheme, the present invention has the following advantages that compared with background technology：
The present invention carries out collection of illustrative plates reduction focusing on people according to public security and the data of civil aviaton, comprehensive to restore people's
Behavior and relation train of thought, can realize safety check, the real-time concern early warning for data of booking tickets, and do in time, accurately for lawless people
Go out response, it is achieved thereby that taking the effective monitoring of commercial air flights to criminal, criminal is excluded in time to flight safety
Threat.
Brief description of the drawings
Fig. 1 is structural representation of the invention；
Fig. 2 is the structural representation of Tupu unit of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Embodiment
With reference to shown in Fig. 1, the invention discloses the civil aviaton's security information service system analyzed based on big data, including big number
According to memory cell 1, data acquisition unit 2, analysis engine 3, Tupu unit 4, machine learning engine 5 and query unit 6, wherein：
Data acquisition unit 2 is used to gather original service data, and original service data Cun Chudao big datas are stored into single
Member 1, original service data include civil aviaton's ticket booking data, airport security data, public security data and pay close attention to staff list number
According to.
Analysis engine 3 is analyzed based on original service data, obtains the warning information relevant with paying close attention to personnel.Point
Analyse engine 3 include staff list management module and early warning value computing module, staff list management module be used for piping off,
The personal information of paying close attention to of Red List is managed, and early warning value computing module is based on ralation method and calculates and pay close attention to personnel
Relevant warning information.
Tupu unit 4 leads the visualization technique of figure using chart database and s power, and the personage for restoring the personnel of paying close attention to is closed
It is network.Tupu unit 4 includes being stored with HDFS file system, chart database engine and application layer, HDFS file system
HBASE database and Solrcloud indexes, chart database engine include data and index accumulation layer, database layer and
ClientAPI layers, data and index accumulation layer are connected with HBASE database and Solrcloud indexes, and ClientAPI layers with answering
It is connected with layer, application layer is used to provide massive relation computing, magnanimity retrieval, relationship, manual drawing, in real time GIS integration, pass
It is computing, relational extensions, characteristic query, attribute collection and map analysis.
Machine learning engine 5 is used to provide analysis engine 3, Tupu unit 4 required algorithm model in the course of the work, machine
Device learns engine 5 and realizes that it includes Data Mining module, data preprocessing module, model based on spark distributed computing frameworks
Training module, model evaluation module, model visualization module and model prediction module, Data Mining module are used to carry out data
Distribution statisticses, correlation analysis, hypothesis testing and Density Estimator, data preprocessing module are used to clean data, turned
Change, load, feature extraction and feature selecting, model evaluation module is used to be estimated the model trained, and model is visual
The visualization for changing module for implementation model shows that model prediction module is used for mold curing to production environment, real time propelling movement
Information of forecasting and generation analysis and suggestion report；
Query unit 6 is used to provide fuzzy query and characteristic key based on the concern key element related to public security, civil aviaton.
Civil aviaton's security information service system of the present invention also includes map retrieval unit 7 and artificial drawing unit 8, wherein：
Map retrieval unit 7 is used for retrieval and the trace analysis for providing map level, to realize the row for the personnel that pay close attention to
Dynamic track following.
Artificial drawing unit 8 is used to supplement character relation data and management service character relation data by hand.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
It should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims
It is defined.
Claims (5)
1. the civil aviaton's security information service system analyzed based on big data, it is characterised in that including big data memory cell, data
Collecting unit, analysis engine, Tupu unit, machine learning engine and query unit, wherein：
The data acquisition unit is used to gather original service data, and the original service data Cun Chudao big datas are stored
Unit, the original service data include civil aviaton's ticket booking data, airport security data, public security data and pay close attention to personnel's name
Forms data；
The analysis engine is analyzed based on original service data, obtains the warning information relevant with paying close attention to personnel；
The Tupu unit leads the visualization technique of figure using chart database and power, restores the character relation for the personnel of paying close attention to
Network；
The machine learning engine is used to provide the analysis engine, Tupu unit required algorithm model in the course of the work,
The machine learning engine realizes that it includes Data Mining module, data prediction mould based on spark distributed computing frameworks
Block, model training module, model evaluation module, model visualization module and model prediction module, the Data Mining module are used
In data are carried out with distribution statisticses, correlation analysis, hypothesis testing and Density Estimator, the data preprocessing module is used for pair
Data are cleaned, changed, being loaded, feature extraction and feature selecting, and the model evaluation module is used for the mould to having trained
Type is estimated, and the visualization that the model visualization module is used for implementation model is shown, the model prediction module is used for will
Mold curing is reported to production environment, real time propelling movement information of forecasting and generation analysis and suggestion；
The query unit is used to provide fuzzy query and characteristic key based on the concern key element related to public security, civil aviaton.
2. the civil aviaton's security information service system as claimed in claim 1 analyzed based on big data, it is characterised in that：Also include
Map retrieval unit, the map retrieval unit is used for retrieval and the trace analysis for providing map level, is paid close attention to realizing
The movement track tracking of personnel.
3. the civil aviaton's security information service system as claimed in claim 1 or 2 analyzed based on big data, it is characterised in that：Institute
Stating Tupu unit includes the HBASE that is stored with HDFS file system, chart database engine and application layer, the HDFS file system
Database and Solrcloud indexes, the chart database engine include data and index accumulation layer, database layer and
ClientAPI layers, the data and index accumulation layer are connected with the HBASE database and Solrcloud indexes, described
ClientAPI layers are connected with the application layer, the application layer be used for provide massive relation computing, magnanimity retrieval, relationship,
Manual drawing, GIS integration, real-time relationship computing, relational extensions, characteristic query, attribute collection and map analysis.
4. the civil aviaton's security information service system as claimed in claim 3 analyzed based on big data, it is characterised in that：Described point
Analysing engine includes staff list management module and early warning value computing module, and the staff list management module is used for being included in black name
The single, personal information of paying close attention to of Red List is managed, and the early warning value computing module is based on ralation method and calculated and emphasis
The relevant warning information of concern personnel.
5. the civil aviaton's security information service system as claimed in claim 3 analyzed based on big data, it is characterised in that：Also include
Artificial drawing unit, the artificial drawing unit is used to supplement character relation data and management service character relation number by hand
According to.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108304454A (en) * | 2017-11-27 | 2018-07-20 | 大象慧云信息技术有限公司 | Invoice data real time aggregation device based on big data |
| CN108804673A (en) * | 2018-06-11 | 2018-11-13 | 中国民用航空飞行学院 | A kind of International Civil Aviation security information management platform |
| CN109559049A (en) * | 2018-12-03 | 2019-04-02 | 中国民航空中警察总队十二支队 | Commercial air flights security Warning System |
| CN109635009A (en) * | 2018-12-27 | 2019-04-16 | 北京航天智造科技发展有限公司 | Fuzzy matching inquiry system and method |
| CN109785083A (en) * | 2019-03-05 | 2019-05-21 | 深圳市活力天汇科技股份有限公司 | A kind of world air ticket extension recommended method |
| CN110782061A (en) * | 2018-08-01 | 2020-02-11 | 北京嘀嘀无限科技发展有限公司 | Method and system for predicting malignant event |
| CN110837753A (en) * | 2018-08-16 | 2020-02-25 | 成都华迈通信技术有限公司 | Collective and separate model for human-vehicle object identification and control and use method thereof |
| CN110955703A (en) * | 2019-11-26 | 2020-04-03 | 武汉虹旭信息技术有限责任公司 | Special personnel information management system and management method |
| CN111210667A (en) * | 2019-12-27 | 2020-05-29 | 中国民用航空飞行学院 | Civil aviation flight security risk early warning system |
| CN114627968A (en) * | 2022-03-18 | 2022-06-14 | 四川大学华西医院 | Multi-modal omics data management system |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108304454B (en) * | 2017-11-27 | 2022-05-17 | 大象慧云信息技术有限公司 | Invoice data real-time aggregation device based on big data |
| CN108304454A (en) * | 2017-11-27 | 2018-07-20 | 大象慧云信息技术有限公司 | Invoice data real time aggregation device based on big data |
| CN108804673A (en) * | 2018-06-11 | 2018-11-13 | 中国民用航空飞行学院 | A kind of International Civil Aviation security information management platform |
| CN110782061A (en) * | 2018-08-01 | 2020-02-11 | 北京嘀嘀无限科技发展有限公司 | Method and system for predicting malignant event |
| CN110837753A (en) * | 2018-08-16 | 2020-02-25 | 成都华迈通信技术有限公司 | Collective and separate model for human-vehicle object identification and control and use method thereof |
| CN109559049A (en) * | 2018-12-03 | 2019-04-02 | 中国民航空中警察总队十二支队 | Commercial air flights security Warning System |
| CN109635009A (en) * | 2018-12-27 | 2019-04-16 | 北京航天智造科技发展有限公司 | Fuzzy matching inquiry system and method |
| CN109635009B (en) * | 2018-12-27 | 2023-09-15 | 北京航天智造科技发展有限公司 | Fuzzy matching inquiry system |
| CN109785083A (en) * | 2019-03-05 | 2019-05-21 | 深圳市活力天汇科技股份有限公司 | A kind of world air ticket extension recommended method |
| CN110955703A (en) * | 2019-11-26 | 2020-04-03 | 武汉虹旭信息技术有限责任公司 | Special personnel information management system and management method |
| CN111210667A (en) * | 2019-12-27 | 2020-05-29 | 中国民用航空飞行学院 | Civil aviation flight security risk early warning system |
| CN114627968A (en) * | 2022-03-18 | 2022-06-14 | 四川大学华西医院 | Multi-modal omics data management system |
| CN114627968B (en) * | 2022-03-18 | 2023-10-20 | 四川大学华西医院 | Multi-mode histology data management system |
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Application publication date: 20171024 |