CN102867223A - Prediction method for airport flow indexes - Google Patents
Prediction method for airport flow indexes Download PDFInfo
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- CN102867223A CN102867223A CN2012103064538A CN201210306453A CN102867223A CN 102867223 A CN102867223 A CN 102867223A CN 2012103064538 A CN2012103064538 A CN 2012103064538A CN 201210306453 A CN201210306453 A CN 201210306453A CN 102867223 A CN102867223 A CN 102867223A
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Abstract
The invention discloses a prediction method for airport flow indexes. The prediction method comprises the following steps of: firstly, calculating delay indexes by means of the airport flow; and secondarily, acquiring the possibility of airport flight delay according to the delay indexes. According to the prediction method, the possibility of the airport flight delay is digitally expressed, so that passengers objectively and comprehensively know about the possibility of the airport flight delay with great convenience and can reasonably arrange the self schedules.
Description
Technical field
The present invention relates to the civil aviaton field, be specially a kind of airport traffic index predictor method.
Background technology
At present, generally be provided with at home civil aviaton's data query system in the airport, the information data of each flight is provided to the public by civil aviaton's data query system.But in each Flight Information data that existing civil aviaton data query system provides, do not have to reflect the data of air station flight delay possibility, the passenger can't comprehensively grasp the flight trend in advance comprehensively, causes the trip mode that the passenger can not reasonable arrangement oneself.
Summary of the invention
The object of the invention provides a kind of airport traffic index predictor method, is applied in civil aviaton's data query system, to solve the problem that does not reflect airliner delay possibility data in the prior art civil aviaton data query system.
In order to achieve the above object, the technical solution adopted in the present invention is:
Airport traffic index predictor method, it is characterized in that: comprise logic processing module, incur loss through delay the index module, be provided with the computing formula of calculating the airliner delay index in the described delay index module, logic processing module is analyzed the delay index that delay index module calculates, and judges whether airport traffic can cause airliner delay;
The computing formula of delay index is divided into two kinds of situations according to the flow of air station flight:
When airport plan in a hour in the past arrival ﹠ departure flights amount (H)〉2 the time,
Incur loss through delay index=(airport one hour in the past the actual flight amount of taking off+airport in the past one hour actual landing flight amount)/(the flight amount of on time not taking off that one hour in the past Proposed Departure flight amount+airport, airport, one hour in the past plan landing flight amount+airport overstock the same day+airport the same day overstock the flight amount that on time do not arrive)
When arrival ﹠ departure flights amount (H)＜=2 was planned in one hour in the past in the airport:
Incur loss through delay index=(airport by current actual total flight amount+airport of taking off by the total flight amount of current actual landing)/(airport by the current general plan amount of taking off+airport by current general plan landing amount),
Logic processing module is analyzed the delay index that delay index module calculates:
When incuring loss through delay index〉0.9 the time, airport traffic is normal, and the airliner delay possibility is rudimentary,
When 0.3＜and when incuring loss through delay index＜0.9, the airport small size is incured loss through delay, and the airliner delay possibility be intermediate,
When incuring loss through delay index＜0.3, the airport large tracts of land is incured loss through delay, and the airliner delay possibility is senior.
Described airport traffic index predictor method, it is characterized in that: described airport same day overstocks do not take off on time flight amount=airport by current general plan take off flight Liang – airport by the current actual flight Liang – airport of taking off by the current in the past one hour Proposed Departure flight amount of flight Liang – airport of taking off of having cancelled
The overstocked flight amount=airport that on time do not arrive on the same day, airport in the past one hour is planned landing flight amount by current actual landing flight Liang – airport by the current landing flight Liang – airport of having cancelled by current general plan landing flight Liang – airport.
Among the present invention, utilize the airport data on flows on the same day, calculate the delay index under the different flow condition, utilize the delay index that the air station flight delay possibility is judged.The air station flight delay possibility can be showed by datumization by the present invention, it is objective and understand all sidedly the delay possibility of air station flight to greatly facilitate the passenger, makes the stroke that the passenger can arranged rational oneself.
Description of drawings
Fig. 1 is schematic diagram of the present invention.
Embodiment
As shown in Figure 1.Among Fig. 1, AD is in the past one hour actual flight amount of taking off of airport, AA is in the past one hour actual landing flight amount of airport, PD is in the past one hour Proposed Departure flight amount of airport, PA is airport one hour in the past plan landing flight amount, D is the airport overstocked flight amount of on time not taking off on the same day, A is the airport overstocked flight amount that on time do not arrive on the same day, TD is that the airport is by current actual total flight amount of taking off, TA is that the airport is by the total flight amount of current actual landing, TPD be the airport by the current general plan amount of taking off, TPA be the airport by current general plan landing amount, H is airport plan in a hour in the past arrival ﹠ departure flights.
Airport traffic index predictor method, comprise logic processing module, incur loss through delay the index module, incur loss through delay and be provided with the computing formula of calculating the airliner delay index in the index module, logic processing module is analyzed the delay index that delay index module calculates, and judges whether airport traffic can cause airliner delay;
The computing formula of delay index is divided into two kinds of situations according to the flow of air station flight:
When airport plan in a hour in the past arrival ﹠ departure flights amount (H)〉2 the time,
Incur loss through delay index=(airport one hour in the past the actual flight amount of taking off+airport in the past one hour actual landing flight amount)/(the flight amount of on time not taking off that one hour in the past Proposed Departure flight amount+airport, airport, one hour in the past plan landing flight amount+airport overstock the same day+airport the same day overstock the flight amount that on time do not arrive)
When arrival ﹠ departure flights amount (H)＜=2 was planned in one hour in the past in the airport:
Incur loss through delay index=(airport by current actual total flight amount+airport of taking off by the total flight amount of current actual landing)/(airport by the current general plan amount of taking off+airport by current general plan landing amount),
Logic processing module is analyzed the delay index that delay index module calculates:
When incuring loss through delay index〉0.9 the time, airport traffic is normal, and the airliner delay possibility is rudimentary,
When 0.3＜and when incuring loss through delay index＜0.9, the airport small size is incured loss through delay, and the airliner delay possibility be intermediate,
When incuring loss through delay index＜0.3, the airport large tracts of land is incured loss through delay, and the airliner delay possibility is senior.
Airport same day overstocks do not take off on time flight amount=airport by current general plan take off flight Liang – airport by the current actual flight Liang – airport of taking off by the current in the past one hour Proposed Departure flight amount of flight Liang – airport of taking off of having cancelled.
The overstocked flight amount=airport that on time do not arrive on the same day, airport in the past one hour is planned landing flight amount by current actual landing flight Liang – airport by the current landing flight Liang – airport of having cancelled by current general plan landing flight Liang – airport.
Claims (2)
1. airport traffic index predictor method, it is characterized in that: comprise logic processing module, incur loss through delay the index module, be provided with the computing formula of calculating the airliner delay index in the described delay index module, logic processing module is analyzed the delay index that delay index module calculates, and judges whether airport traffic can cause airliner delay;
The computing formula of delay index is divided into two kinds of situations according to the flow of air station flight:
When airport plan in a hour in the past arrival ﹠ departure flights amount (H)〉2 the time,
Incur loss through delay index=(airport one hour in the past the actual flight amount of taking off+airport in the past one hour actual landing flight amount)/(the flight amount of on time not taking off that one hour in the past Proposed Departure flight amount+airport, airport, one hour in the past plan landing flight amount+airport overstock the same day+airport the same day overstock the flight amount that on time do not arrive)
When arrival ﹠ departure flights amount (H)＜=2 was planned in one hour in the past in the airport:
Incur loss through delay index=(airport by current actual total flight amount+airport of taking off by the total flight amount of current actual landing)/(airport by the current general plan amount of taking off+airport by current general plan landing amount),
Logic processing module is analyzed the delay index that delay index module calculates:
When incuring loss through delay index〉0.9 the time, airport traffic is normal, and the airliner delay possibility is rudimentary,
When 0.3＜and when incuring loss through delay index＜0.9, the airport small size is incured loss through delay, and the airliner delay possibility be intermediate,
When incuring loss through delay index＜0.3, the airport large tracts of land is incured loss through delay, and the airliner delay possibility is senior.
2. airport traffic index predictor method according to claim 1, it is characterized in that: described airport same day overstocks do not take off on time flight amount=airport by current general plan take off flight Liang – airport by the current actual flight Liang – airport of taking off by the current in the past one hour Proposed Departure flight amount of flight Liang – airport of taking off of having cancelled
The overstocked flight amount=airport that on time do not arrive on the same day, airport in the past one hour is planned landing flight amount by current actual landing flight Liang – airport by the current landing flight Liang – airport of having cancelled by current general plan landing flight Liang – airport.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400053A (en) * | 2013-08-26 | 2013-11-20 | 合肥飞友网络科技有限公司 | Punctual flight takeoff forecasting method |
| CN106448273A (en) * | 2016-11-02 | 2017-02-22 | 合肥飞友网络科技有限公司 | A method for automatically monitoring flight executing in real time |
| CN107480247A (en) * | 2017-08-10 | 2017-12-15 | 中国民航信息网络股份有限公司 | The monitoring method and device of airport passenger distribution |
| CN109887344A (en) * | 2019-04-19 | 2019-06-14 | 鄂尔多斯应用技术学院 | A kind of method of determining air station flight delay degree |
| CN113657671A (en) * | 2021-08-18 | 2021-11-16 | 北京航空航天大学 | Flight delay prediction method based on ensemble learning |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101339700A (en) * | 2008-08-14 | 2009-01-07 | 中国民航大学 | Airport flight delay early-warning system based on immune algorithm |
| CN101546484A (en) * | 2009-04-30 | 2009-09-30 | 南京航空航天大学 | Flight delay conformance analysis and forecast system based on SOA and operation method thereof |
| WO2012110047A1 (en) * | 2011-02-14 | 2012-08-23 | Flughafen Wien Ag | Device and method for monitoring and controlling airport processes |
-
2012
- 2012-08-27 CN CN2012103064538A patent/CN102867223A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101339700A (en) * | 2008-08-14 | 2009-01-07 | 中国民航大学 | Airport flight delay early-warning system based on immune algorithm |
| CN101546484A (en) * | 2009-04-30 | 2009-09-30 | 南京航空航天大学 | Flight delay conformance analysis and forecast system based on SOA and operation method thereof |
| WO2012110047A1 (en) * | 2011-02-14 | 2012-08-23 | Flughafen Wien Ag | Device and method for monitoring and controlling airport processes |
Non-Patent Citations (1)
| Title |
|---|
| 徐涛等: "基于SOA的民航航班延误波及分析与预警系统", 《计算机科学》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400053A (en) * | 2013-08-26 | 2013-11-20 | 合肥飞友网络科技有限公司 | Punctual flight takeoff forecasting method |
| CN106448273A (en) * | 2016-11-02 | 2017-02-22 | 合肥飞友网络科技有限公司 | A method for automatically monitoring flight executing in real time |
| CN107480247A (en) * | 2017-08-10 | 2017-12-15 | 中国民航信息网络股份有限公司 | The monitoring method and device of airport passenger distribution |
| CN109887344A (en) * | 2019-04-19 | 2019-06-14 | 鄂尔多斯应用技术学院 | A kind of method of determining air station flight delay degree |
| CN113657671A (en) * | 2021-08-18 | 2021-11-16 | 北京航空航天大学 | Flight delay prediction method based on ensemble learning |
| CN113657671B (en) * | 2021-08-18 | 2024-02-09 | 北京航空航天大学 | Flight delay prediction method based on ensemble learning |
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Application publication date: 20130109 |