CN106407735A - Weather and traffic visualization method and device - Google Patents
Weather and traffic visualization method and device Download PDFInfo
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- CN106407735A CN106407735A CN201611190232.3A CN201611190232A CN106407735A CN 106407735 A CN106407735 A CN 106407735A CN 201611190232 A CN201611190232 A CN 201611190232A CN 106407735 A CN106407735 A CN 106407735A
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Abstract
The embodiment of the invention discloses a weather and traffic visualization method and device, and relates to the technical field of air traffic management. The method comprises the steps of obtaining weather data in a selected region within a selected period of time and traffic data matched with the weather data within the selected period of time, obtaining weather and traffic index data of the selected region on the basis of the weather data, the traffic data and preset weather and traffic index calculation rules, obtaining standardized data of the weather and traffic index data on the basis of the weather and traffic index data and a preset standardization data processing method, performing clustering analysis on the standardization data of weather and traffic index data by means of a Ward method, and displaying the mutual relation between the weather data and the traffic data in a visualization image mode according to a result of the clustering analysis. The problem that the mutual relation between weather and an air traffic system cannot be visually explained at present is solved.
Description
Technical field
The present invention relates to air traffic control technical field, in particular to a kind of weather traffic method for visualizing and
Device.
Background technology
Along with the continuous progress of meteorological technology these years, the related practitioner of civil aviaton has also followed up meteorological scientific data side
The automatization of the research in face and blank pipe, informationization, reduce the work mistake that anthropic factor causes, it is to avoid aviation accident or flight thing
Therefore sign.Due to implement time soon, report at this stage can't efficiently catch more complicated air traffic situation,
Also it is unable to estimate the load of controller.And boisterous impact is to include the complicated spatial domain of high power capacity, traffic conditions.
At this stage, China is most in the application of meteorological aspect is aerodrome weather forecast, and daily weather forecast etc. is reported, in addition with by thunder
Reach and obtain and analyze the data obtaining.Do in terms of conformability not enough it is impossible to accomplish the sky of the whole country of the integration of system
Meteorological data in domain, the meteorological and combination of Air Traffic System is done also not enough.
Content of the invention
In view of this, the purpose of the embodiment of the present invention be to provide a kind of weather traffic method for visualizing and device it is intended to
Solve the above problems.
In a first aspect, embodiments providing a kind of weather traffic method for visualizing, methods described includes：Obtain choosing
Determine region in the weather data in seclected time section and the traffic mated in described seclected time section with described weather data
Data；Based on described weather data, described traffic data and default weather traffic index computation rule, obtain described selecting
The weather traffic index data in region；Based on described weather traffic index data and default standardized data processing method,
Obtain the standardized data of described weather traffic index data；Using the standardization to described weather traffic index data for the Ward method
Data carries out cluster analyses；According to the result of cluster analyses, in the form of visual image show described weather data with described
The mutual relation of traffic data.
Second aspect, embodiments provides a kind of weather traffic visualization device, and described device includes：Original number
According to acquiring unit, for obtaining weather data in seclected time section for the selection area and with described weather data in described choosing
The traffic data of coupling in section of fixing time；Weather traffic index data capture unit, for based on described weather data, described friendship
Logical data and default weather traffic index computation rule, obtain the weather traffic index data of described selection area；Standard
Change data capture unit, for based on described weather traffic index data and default standardized data processing method, obtaining
The standardized data of described weather traffic index data；Cluster analysis unit, for being referred to described weather traffic using Ward method
The standardized data of number data carries out cluster analyses；Visualization display unit, for the result according to described cluster analysis unit,
The mutual relation of described weather data and described traffic data is shown in the form of visual image.
Embodiments provide a kind of weather traffic method for visualizing and device, methods described is included by selecting area
Domain is in the weather data in seclected time section and the traffic data that mates in described seclected time section with described weather data；
Based on described weather data, described traffic data and default weather traffic index computation rule, obtain described selection area
Weather traffic index data；Based on described weather traffic index data and default standardized data processing method, obtain
The standardized data of described weather traffic index data；Using the standardized data to described weather traffic index data for the Ward method
Carry out cluster analyses；According to the result of cluster analyses, show described weather data and described traffic in the form of visual image
The mutual relation of data, thus solve currently can not intuitively explain mutual relation between weather and Air Traffic System
Problem.
Other features and advantages of the present invention will illustrate in subsequent description, and, partly becomes from description
It is clear that or being understood by implementing the embodiment of the present invention.The purpose of the present invention and other advantages can be by saying of being write
In bright book, claims and accompanying drawing, specifically noted structure is realizing and to obtain.
Brief description
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, below will be attached to use required in embodiment
Figure is briefly described it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, and it is right to be therefore not construed as
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is a kind of structured flowchart of the electronic equipment that can be applicable in the embodiment of the present application；
The flow chart of the weather traffic method for visualizing that Fig. 2 provides for first embodiment of the invention；
The schematic diagram of the part MATER message that Fig. 3 provides for first embodiment of the invention；
The schematic diagram of the Capital Airport that Fig. 4 provides for the first embodiment of the invention weather phenomenon of 1 day of 12 months；
The schematic diagram of the daily traffic volume of the main airports that Fig. 5 provides for first embodiment of the invention；
The schematic diagram of the weather traffic index data that Fig. 6 provides for first embodiment of the invention；
The schematic diagram of the part WITI value after the translation standard deviation that Fig. 7 provides for first embodiment of the invention；
The schematic diagram of the part WITI value after the translation extreme difference that Fig. 8 provides for first embodiment of the invention；
The result schematic diagram of the distance matrix that Fig. 9 provides for first embodiment of the invention；
The cluster tree diagram that Figure 10 provides for first embodiment of the invention；
The WITI scatterplot that Figure 11 provides for first embodiment of the invention；
The WITI corresponding visualization schematic diagram that Figure 12 provides for first embodiment of the invention；
The visualization schematic diagram of the cluster analysis result that Figure 13 provides for first embodiment of the invention；
The weather traffic visualization device that Figure 14 provides for second embodiment of the invention.
Specific embodiment
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground description is it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Generally exist
The assembly of the embodiment of the present invention described and illustrated in accompanying drawing can be arranged with various different configurations and design herein.Cause
This, be not intended to limit claimed invention to the detailed description of the embodiments of the invention providing in the accompanying drawings below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on embodiments of the invention, those skilled in the art are not doing
The every other embodiment being obtained on the premise of going out creative work, broadly falls into the scope of protection of the invention.
It should be noted that：Similar label and letter represent similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined in individual accompanying drawing, then do not need it to be defined further and explains in subsequent accompanying drawing.Meanwhile, the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that indicating or hint relative importance.
Refer to Fig. 1, Fig. 1 shows a kind of structured flowchart of the electronic equipment 100 that can be applicable in the embodiment of the present application.
This electronic equipment 100 can as user terminal or computer or server, described user terminal can for mobile phone or
Panel computer.As shown in figure 1, electronic equipment 100 can include memorizer 110, storage control 111, processor 112 and weather
Traffic visualization device.
Directly or indirectly electrically connect between memorizer 110, storage control 111, each element of processor 112, to realize
The transmission of data or interaction.For example, electricity can be realized by one or more communication bus or signal bus between these elements
Connect.Described weather traffic method for visualizing is included at least one respectively and can be deposited in the form of software or firmware (firmware)
Be stored in the software function module in memorizer 110, the software function module that for example described weather traffic visualization device includes or
Computer program.
Memorizer 110 can store various software programs and module, and the weather traffic that such as the embodiment of the present application provides can
Depending on changing the corresponding programmed instruction/module of method and device.Processor 112 passes through to run the software journey storing in the memory 110
Sequence and module, thus executing various function application and data processing, that is, the weather traffic realized in the embodiment of the present application can
Depending on change method.Memorizer 110 can include but is not limited to random access memory (Random Access Memory, RAM), only
Read memorizer (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Processor 112 can be a kind of IC chip, have signal handling capacity.Above-mentioned processor can be general
Processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit (Network
Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), special IC (ASIC), ready-made programmable
Gate array (FPGA) or other PLDs, discrete gate or transistor logic, discrete hardware components.It can
With the disclosed each method in realization or execution the embodiment of the present application, step and logic diagram.General processor can be micro-
Processor or this processor can also be any conventional processors etc..
First embodiment
Refer to Fig. 2, present example provides a kind of weather traffic method for visualizing, methods described includes：
Step S200：Obtain weather data in seclected time section for the selection area and with described weather data described
The traffic data of coupling in seclected time section；
It is difficult to meet the demand of the weather data to air route in view of existence conditionses, in embodiments of the present invention, using machine
The weather traffic index of Performance Area is representing the weather traffic index in whole spatial domain.By institute's organic field in the whole nation cannot be taken into account,
In order to simplify calculating, the airport that the present embodiment selects maximum flow from 11 flight information regions of China respectively is calculated,
It is important that showing the calculating process of China's weather typing.
The present embodiment have chosen relatively stable weather in 2015 as object of study, only considers the shadow of wind and visibility
Ring, with the METAR count off of selected airport on every month 1st, 2015 according to calculating the weather traffic index value in this region.
According to mentioned above principle, selected airport is：The Capital Airport of Beijing flight information region, the Pu of Shanghai flight information region
Eastern airport, the peaceful airport of Shenyang flight information region, the White Cloud Airport of Guangzhou flight information region, the double fluid of Chengdu flight information region
Airport, the long water dispenser field of Kunming flight information region, the Tianhe Airport of Wuhan flight information region, the Xi'an of Lanzhou flight information region is salty
Positive airport, the ground shack airport of Urumchi flight information region, the Haikou methylene blue airport of Sanya flight information region, Hong Kong flight feelings
Report Hong Kong airport in area, the peach garden airport of Taiwan flight information region.The Weather information collecting these airports is mainly also to rely on
The METAR report on these airports and TAF report, we can average to daily weather conditions, calculates WITI based on this.
Taking Captical International Airport as a example, download the Capital Airport 2015 first on the website monthly METAR message of 1 day.
Refer to Fig. 3, the schematic diagram of the part MATER message that Fig. 3 provides for first embodiment of the invention, because weather phenomenon is more steady
Fixed, and the issue of METAR message per half an hour is once, so in the present embodiment, having intercepted the message of portion of time section.By
In message above, can summarize, the visibility average out to CAVOK in Captical International Airport on January 1st, 2015, visibility is big
In 9999 meters, wind speed is 3 metre per second (m/s)s.The method judging average weather phenomenon daily according to this, refer to Fig. 4, and Fig. 4 is this
The schematic diagram of the Capital Airport weather phenomenon of 1 day of 12 months that bright first embodiment provides, i.e. 1 day of the Capital Airport 12 months
Visibility and air speed data.
Step S210：Based on described weather data, described traffic data and default weather traffic index computation rule,
Obtain the weather traffic index data of described selection area；
As a kind of embodiment, according to formula one：
WITI (k)=T (k) × W (k)
W (k) is the weights of described selection area, and when adverse weather constitutes impact to air traffic, weight is 1, does not constitute
During impact be then 0, T (k) be described traffic data, WITI (k) is the weather traffic index data of described selection area, obtains described
The weather traffic index data of selection area,
The present embodiment weather data related to select 12 airport collection above, after the completion of collection, according to
The computing formula one being provided, calculates the weather traffic index value in each information area.Firstly the need of it is confirmed that the value of W (k),
Represent the coefficient of weight, significance of which is the influence degree judging weather to air traffic, in the present embodiment, can integrate
The data that may determine that this influence degree be exactly visibility, this two values of wind speed.Due to being in line with meteorological severity
Sexual intercourse, so the substantially distribution that the embodiment of the present invention can determine according to this relation.It is worth in view of this two
More complicated with meteorological linear relationship, temporarily cannot find one and perfectly can express this linear formula.Institute
The relation of this three is simplified to by equation below two with the embodiment of the present invention：
After determining the computational methods of W (k), next step is just to determine the value of T (k) it is contemplated that the weather information above collected
It is all in units of sky, also by collecting various data, can should be obtained in units of sky therefore when seeking the value of T (k)
Obtain the daily traffic volume of main airports, refer to Fig. 5, the daily traffic volume of the main airports that Fig. 5 provides for first embodiment of the invention
Schematic diagram, wherein ZBAA be Beijing flight information region the Capital Airport, ZSPD be Shanghai flight information region pudong airport,
ZYHB is the peaceful airport of Shenyang flight information region, and ZGGG is the White Cloud Airport of Guangzhou flight information region, and ZUUU flies for Chengdu
The Shuangliu Airport in information area, ZPPP is the long water dispenser field of Kunming flight information region, and ZHHH is the Milky Way machine of Wuhan flight information region
, ZLXY is the Xi'an Xianyang Airport of Lanzhou flight information region, and ZWWW is the ground shack airport of Urumchi flight information region,
ZJHK is the Haikou methylene blue airport of Sanya flight information region, and VHHH is Hong Kong airport of Hong Kong flight information region, and RCTP is Taiwan
The peach garden airport of flight information region.
According to above-mentioned formula one and formula two, by the final result drawing after the data processing of collection be every
The WITI value in individual area, refers to Fig. 6, the schematic diagram of the weather traffic index data that Fig. 6 provides for first embodiment of the invention,
Wherein ZBPE is the Capital Airport/AREA CONTROL CRNTRE of Beijing flight information region, and ZYSH is the peaceful machine of Shenyang flight information region
Field/AREA CONTROL CRNTRE, ZSHA is the pudong airport/AREA CONTROL CRNTRE of Shanghai flight information region, and ZGZU is Guangzhou flight feelings
Report the White Cloud Airport/AREA CONTROL CRNTRE in area, ZUUU is the Shuangliu Airport/AREA CONTROL CRNTRE of Chengdu flight information region, ZPKM
For the long water dispenser field/AREA CONTROL CRNTRE of Kunming flight information region, ZHWH is the Tianhe Airport/region pipe of Wuhan flight information region
Center processed, ZLHW is the Xi'an Xianyang Airport/AREA CONTROL CRNTRE of Lanzhou flight information region, and ZWUQ is Urumchi flight information
The ground shack airport/AREA CONTROL CRNTRE in area, ZJSY is the Haikou methylene blue airport/AREA CONTROL CRNTRE of Sanya flight information region,
VHHK is Hong Kong airport/AREA CONTROL CRNTRE of Hong Kong flight information region, and RCAA is the peach garden airport/area of Taiwan flight information region
Domain Control Centre.
Step S220：Based on described weather traffic index data and default standardized data processing method, obtain institute
State the standardized data of weather traffic index data；
Step S230：Using Ward method, cluster analyses are carried out to the standardized data of described weather traffic index data；
Cluster analyses are the methods of the characteristic research individual segregation according to things itself.Class in cluster analyses is in brief
Refer to is exactly the set of similar element.
The foundation of cluster analyses is that an apoplexy due to endogenous wind individuality has larger similarity, and inhomogeneous individual variation is very big.According to point
The difference of class object is divided into quick sample clustering it is simply that clustering to existing measured value, is the various features possessing object of observation, that is,
Each variable of the feature of reaction object being observed is classified.Herein we carry out cluster point using Ward method to WITI
Analysis.
Ward method, i.e. the distance between using squared euclidean distance as two classes, first each sample will constitute a class by itself in set,
When carrying out categories combination, calculate variance between class center of gravity, two classes of the amplitude minimum that sum of deviation square is increased merge first, then
Successively all categories are merged step by step.Specific algorithm is as follows：
N zone sample is divided into k class：G1, G2 ... Gk, usesI-th sample in expression Gt is (hereinIt is p dimension
Vector, has p Hierarchical Clustering index), nt represents the number of samples in Gt, and X (t) is the center of gravity of Gt (is the equal of such sample
Value), then in Gt, the sum of deviation square of sample is formula three：
In the class of k class, sum of deviation square is formula four：
Next the present embodiment carries out data processing according to this principle, carries out data normalization process first：In order to analyze
Convenience, the WITI index calculating is processed herein, eliminates original dimension, compressing original data is arrived [0,1] interval.
Based on this purpose, needing to use translation standard deviation formula is formula five：
Wherein, Xj represents the average of j-th index, and Sj then represents standard deviation.
Data after having processed refers to Fig. 7, the portion after the translation standard deviation that Fig. 7 provides for first embodiment of the invention
The schematic diagram of point WITI value, i.e. 12 airports data after the WITI value translation standard deviation in January to August.
It is then used by translating extreme difference formula, the data after having processed above is carried out with after-treatment, translation extreme difference formula is
Formula six：
Result after change refers to Fig. 8, the part after the translation extreme difference that Fig. 8 provides for first embodiment of the invention
The schematic diagram of WITI value, that is, 12 airports in the WITI value in January to August after translation standard deviation, after translation extreme difference
WITI value.
Next, the present embodiment can set up distance matrix according to the principle of euclidean distance method, process of specifically setting up exists
Realize in SPSS software, after the completion of distance matrix as shown in figure 9, laterally representing the 1-8 month, longitudinally represent corresponding above-mentioned 12 machines
?.
And then, cluster analyses are carried out to standardized data using Ward minimum deflection sum of squares approach, using SPSS statistical
Analysis obtains clustering tree diagram, refers to Figure 10, longitudinally represents the 1-12 month, when weather condition divides and sorts out, by its result
It is divided into 4 classes：By 2 months, September, June be divided into a class；May, July, August, October, December are divided into two classes；March and April, November
It is divided into three classes；January is individually divided into four classes.These classifications represent and extract one group of data from each classification out, generally
May determine that the weather condition in whole classification.
Step S240：According to the result of cluster analyses, in the form of visual image show described weather data with described
The mutual relation of traffic data.
Visualization technique, this concept is derived from visualization in scientific computing, and it is European and American developed countries' twentieth century eighties
Later stage proposes the brand-new research field established.Using the process computing capability of computer, visualization technique will be in scientific research
The data used is needed to be shown with the mode of simple and clear figure in calculating it is therefore an objective to make originally uninteresting data calculate
Process becomes directly perceived, vivid, and this contributes to the dynamic change that scientists hold data.
R is statistical calculations software that is a free and increasing income, and graphing capability is also very powerful.It is also most statistics
One of scholar's analysis software the most favorite.Although there being the approximate payware of some functions, such as S-plus and SAS, but it
Be difficult to be comparable to the completely free and active exploitation community atmosphere of R.
At present, R language provides the version under each big operating system such as Windows, OS X, Linux, can directly from network
Free download, installation, use.R lingware provides substantial amounts of data processing, statistics and graph function in basic installation,
In addition each community also developed thousands of expanding packet (packages) and increased more wonderful functions for R.
There are two kinds of drawing functions in R language, the first is advanced drawing function, that is, create a new figure,>demo
(graphics), another kind is rudimentary drawing function, addition element on existing figure,>demo(persp).
Need to complete corresponding preparation before starting mapping, and the first step is exactly to get out data.For avoid weight
Data is saved as CSV symbol file by the consideration of multiple input herein, and suffix is .csv, and Excel directly provides this guarantor
Deposit option.
First, WITI value table storage Fig. 6 being drawn is .CSV file, opens R lingware.
Read data with read.csv () function in the.data：
>the.data<- read.csv (" WITI.csv ", header=TRUE)
Making scatterplot needs to use the plot function in R language, comprises the following steps that shown：
>x<- the.data $ the date
>y<-the.data$WITI
>Plot (x, y, main=" the scatterplot distribution of WITI value ", pch=4, col=" red ", xlab=" month ",
Ylab=" total WITI value ", type=" p ", font.axis=2, font.lab=2, cex.lab=1.5)
>X=seq (1,12, by=0.1)；Y=[50,100,150,200,250,300,350]
>Lines (x, y, col=" black ", lwd=2)
As shown in figure 11, transverse and longitudinal represents the 1-12 month to last scatterplot, and the longitudinal axis represents corresponding airport WITI value, scatterplot
Can help intuitively check the numerical value of WITI, but weather is not still intuitively experienced to the influence degree of traffic.
Therefore, after having made scatterplot, the present embodiment tries weather traffic index carries out the classification of some quantizations, and with visualizing
Means intuitively to show the influence degree to traffic for the weather.
In the WITI data tried to achieve, more than 80 is that weather is serious to traffic impact, and 75-80 has to air traffic for weather
Certain impact, what less than 75 WITI value was representative is that weather is less on air traffic impact or no affect.
In order that data visualization, we can be in the way of using representing Different Effects degree with different colours.Here
We select thermal map (heatmap) function in R language to realize this target.
The first step：Read data
It is still that data is saved as .csv file, we save the data in the R file under F disk here.In R
Execution such as gives an order
witi<-read.csv("F:/ R/WITI.CSV ", sep=", ")
Thus can successfully read in the tables of data of WITI value, the data of reading can be checked using " witi " instruction.
Second step：Processing data
In view of in the in figure done, the title of row should be the date, need to be instructed with this：
colnames(witi)<- witi $ the date
Name due to row should be named by the name on airport, and execution is to give an order：
row.names(witi)<- witi $ airport
In the form that we obtain, first row is the date, is not required to the data being shown in hotspot graph, therefore uses
Following sentence, to ensure only to take second to arrive last string：
witi<-witi[,2:13]
For the rewriting of data visual effect, need to use：
witi_matrix<-data.matrix(witi)
It is possible to generate hotspot graph with following instruction after completing above-mentioned steps：
witi_heatmap<- heatmap (witi_matrix, Rowv=NA, Colv=NA, col=cm.colors
(256), scale=" column ", margins=c (5,10))
As shown in figure 12, transverse and longitudinal is the 1-12 month to the result obtaining, and the longitudinal axis is 12 airports, with the increase of WITI value, lattice
The color of son assumes the gradual change of light gray → white → dark-grey, and by this figure, we can intuitively check in different months, respectively
The influence degree to traffic for the weather on individual airport.When the grid light gray in airport corresponding month is deeper, illustrate that weather is handed over to aerial
Logical impact is very little it might even be possible to ignore, and when mesh color is white, certain impact has been described, and
When grid is in dark-grey, illustrate that the impact to traffic for the weather is very serious, need certain reply means.
As shown in figure 12, can easily find out, the weather conditions of Beijing flight information region are that comparison is bad, may
It is because the factors such as haze, sand and dust, impact all ratios that in whole year, weather goes to Beijing flight information are larger, and this also can lead to unavoidably
The delay of flight is even cancelled.
And in coastal Shanghai flight information region and Guangzhou flight information region, in may, June, these three summers in July
In month, weather flies up to the influence degree of air traffic, can speculate and be because this Liang Ge information area on China southeast edge
Sea, every summer is just easy to the weather such as thunderstorm, also faces the vile weathers such as possible Landed Typhoon, and therefore weather is handed over
Logical index height is also not at all surprising.And to winter, this situation has just been alleviated.
Additionally, based on the result after cluster analyses, visualization processing equally can be done：
witi<-read.csv("F:/ R/WITI.CSV ", sep=", ")
row.names(witi)<- witi $ airport
witi<-witi[,2:13]
witi_matrix<-data.matrix(witi)
witi_heatmap<- heatmap (witi_matrix, Rowv=NA, Colv=NA, col=cm.colors
(256), scale=" column ", margins=c (5,10))
As shown in figure 13, transverse axis represents airport to the result obtaining, and the longitudinal axis represents the result of corresponding Figure 10 cluster analyses.Permissible
Know, the impact of 12 airports corresponding air traffic of weather in first kind month is smaller；It is weather in third and fourth class
The impact of corresponding air traffic is than larger.
Embodiments provide a kind of weather traffic method for visualizing, methods described is included by selection area in choosing
Fix time the weather data in section and the traffic data mating in described seclected time section with described weather data；Based on institute
State weather data, described traffic data and default weather traffic index computation rule, obtain the weather of described selection area
Traffic index data；Based on described weather traffic index data and default standardized data processing method, obtain described sky
The standardized data of gas traffic index data；Using Ward method, the standardized data of described weather traffic index data is gathered
Alanysis；According to the result of cluster analyses, show described weather data and described traffic data in the form of visual image
Mutual relation, and solve the problems, such as the mutual relation that currently can not intuitively explain between weather and Air Traffic System, make
Obtaining uninteresting data hard to understand originally becomes visual pattern, contributes to us and preferably analyzes weather traffic index.
Second embodiment
Refer to Figure 14, embodiments provide a kind of weather traffic visualization device 300, described device 300 is wrapped
Include：
Initial data acquiring unit 310, for obtain weather data in seclected time section for the selection area and with institute
State the traffic data that weather data mates in described seclected time section；
Weather traffic index data capture unit 320, for based on described weather data, described traffic data and default
Weather traffic index computation rule, obtain described selection area weather traffic index data；
For example it is used for obtaining the weather traffic index data of described selection area, W based on WITI (k)=T (k) × W (k)
K () is the weights of described selection area, when adverse weather constitutes impact to air traffic, weight is 1, does not constitute during impact then
It is described traffic data for 0, T (k), WITI (k) is the weather traffic index data of described selection area.
Described weather data includes visibility data and air speed data, and weight W (k)=1/ of described selection area (can be seen
Degree/1000+ wind speed/10), wherein, visibility is described visibility data, and wind speed is described air speed data.Described weather data
And the traffic data mating in described seclected time section with described weather data includes METAR and TAF message.
Standardized data acquiring unit 330, for based on described weather traffic index data and default normalized number
According to processing method, obtain the standardized data of described weather traffic index data；
As a kind of embodiment, described standardized data acquiring unit 330 includes：
Data normalization unit 331, for based on described weather traffic index data and translation standard deviation formula, obtaining
Normalization weather traffic index data；
Data normalization unit 332, after processing for data normalization unit 331, according to translation extreme difference formula, obtains mark
Standardization weather traffic index data；
Distance matrix acquiring unit 333, after processing for data normalization unit 332, according to euclidean distance method, obtains institute
State the distance matrix of standardization weather traffic index data.
Cluster analysis unit 340, for being carried out to the standardized data of described weather traffic index data using Ward method
Cluster analyses；
Visualization display unit 350, for the result according to described cluster analysis unit, aobvious in the form of visual image
Show the mutual relation of described weather data and described traffic data.
It should be noted that each unit in the present embodiment can be by software code realization, now, above-mentioned each unit
Can be stored in memorizer 110.Above each unit equally can be realized by hardware such as IC chip.
It should be understood that disclosed apparatus and method are it is also possible to pass through in several embodiments provided herein
Other modes are realized.Device embodiment described above is only schematically, for example, the flow chart in accompanying drawing and block diagram
Show the device of multiple embodiments according to the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.At this point, each square frame in flow chart or block diagram can represent the one of a module, program segment or code
Part, a part for described module, program segment or code comprises holding of one or more logic function for realizing regulation
Row instruction.It should also be noted that at some as in the implementation replaced, the function of being marked in square frame can also be to be different from
The order being marked in accompanying drawing occurs.For example, two continuous square frames can essentially execute substantially in parallel, and they are sometimes
Can execute in the opposite order, this is depending on involved function.It is also noted that it is every in block diagram and/or flow chart
The combination of the square frame in individual square frame and block diagram and/or flow chart, can be with the special base of the function of execution regulation or action
System in hardware to be realized, or can be realized with combining of computer instruction with specialized hardware.
In addition, each functional module in each embodiment of the present invention can integrate one independent portion of formation
Divide or modules individualism is it is also possible to two or more modules are integrated to form an independent part.
If described function realized using in the form of software function module and as independent production marketing or use when, permissible
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
Partly being embodied in the form of software product of part that prior art is contributed or this technical scheme, this meter
Calculation machine software product is stored in a storage medium, including some instructions with so that a computer equipment (can be individual
People's computer, server, or network equipment etc.) execution each embodiment methods described of the present invention all or part of step.
And aforesaid storage medium includes：USB flash disk, portable hard drive, read only memory (ROM, Read-Only Memory), random access memory are deposited
Reservoir (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.Need
Illustrate, herein, such as first and second or the like relational terms be used merely to by an entity or operation with
Another entity or operation make a distinction, and not necessarily require or imply there is any this reality between these entities or operation
The relation on border or order.And, term " inclusion ", "comprising" or its any other variant are intended to the bag of nonexcludability
Containing, so that including a series of process of key elements, method, article or equipment not only include those key elements, but also including
Other key elements being not expressly set out, or also include for this process, method, article or the intrinsic key element of equipment.
In the absence of more restrictions, the key element being limited by sentence "including a ..." is it is not excluded that including described key element
Process, method, also there is other identical element in article or equipment.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.All within the spirit and principles in the present invention, made any repair
Change, equivalent, improvement etc., should be included within the scope of the present invention.It should be noted that：Similar label and letter exist
Representing similar terms in figure below, therefore, once being defined in a certain Xiang Yi accompanying drawing, being then not required in subsequent accompanying drawing
It is defined further and to be explained.
The above, the only specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, and any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, all should contain
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should described be defined by scope of the claims.
It should be noted that herein, such as first and second or the like relational terms are used merely to a reality
Body or operation are made a distinction with another entity or operation, and not necessarily require or imply these entities or deposit between operating
In any this actual relation or order.And, term " inclusion ", "comprising" or its any other variant are intended to
Comprising of nonexcludability, wants so that including a series of process of key elements, method, article or equipment and not only including those
Element, but also include other key elements being not expressly set out, or also include for this process, method, article or equipment
Intrinsic key element.In the absence of more restrictions, the key element that limited by sentence "including a ..." it is not excluded that
Also there is other identical element including in the process of described key element, method, article or equipment.
Claims (10)
1. a kind of weather traffic method for visualizing is it is characterised in that methods described includes：
Obtain selection area the weather data in seclected time section and with described weather data in described seclected time section
The traffic data of coupling；
Based on described weather data, described traffic data and default weather traffic index computation rule, obtain described selecting
The weather traffic index data in region；
Based on described weather traffic index data and default standardized data processing method, obtain described weather traffic index
The standardized data of data；
Using Ward method, cluster analyses are carried out to the standardized data of described weather traffic index data；
According to the result of cluster analyses, show the mutual of described weather data and described traffic data in the form of visual image
Relation.
2. method according to claim 1 it is characterised in that described based on described weather data, described traffic data with
And default weather traffic index computation rule, obtain the weather traffic index data of described selection area, including：
Based on WITI (k)=T (k) × W (k), obtain the weather traffic index data of described selection area, W (k) is described selecting
The weights in region, when adverse weather constitutes impact to air traffic, weight is 1, do not constitute during impact be then 0, T (k) be described
Traffic data, WITI (k) is the weather traffic index data of described selection area.
3. method according to claim 2 is it is characterised in that described weather data includes visibility data and wind speed number
According to weights W (k) of described selection area are：Wherein, visibility is described visibility
Data, wind speed is described air speed data.
4. method according to claim 1 is it is characterised in that described based on described weather traffic index data and default
Standardized data processing method, obtain described weather traffic index data standardized data, including：
Based on described weather traffic index data and translation standard deviation formula, obtain normalization weather traffic index data；So
It is based on translation extreme difference formula afterwards, obtain standardization weather traffic index data；According to euclidean distance method, obtain described standardization sky
The distance matrix of gas traffic index data.
5. method according to claim 1 it is characterised in that described weather data and with described weather data described
In seclected time section, the traffic data of coupling includes METAR and TAF message.
6. a kind of weather traffic visualization device is it is characterised in that described device includes：
Initial data acquiring unit, for obtain weather data in seclected time section for the selection area and with described sky destiny
Traffic data according to coupling in described seclected time section；
Weather traffic index data capture unit, for based on described weather data, described traffic data and default weather
Traffic index computation rule, obtains the weather traffic index data of described selection area；
Standardized data acquiring unit, for based on described weather traffic index data and default standardized data process side
Method, obtains the standardized data of described weather traffic index data；
Cluster analysis unit, for carrying out cluster point using Ward method to the standardized data of described weather traffic index data
Analysis；
Visualization display unit, for the result according to described cluster analysis unit, is shown described in the form of visual image
Weather data and the mutual relation of described traffic data.
7. device according to claim 6 is it is characterised in that described weather traffic index data capture unit, for base
In WITI (k)=T (k) × W (k), obtain the weather traffic index data of described selection area, W (k) is described selection area
Weights, when adverse weather constitutes impact to air traffic, weight is 1, do not constitute during impact be then 0, T (k) be described traffic number
According to WITI (k) is the weather traffic index data of described selection area.
8. device according to claim 7 is it is characterised in that described weather data includes visibility data and wind speed number
According to the weights of described selection areaWherein, visibility is described visibility data, wind
Speed is described air speed data.
9. device according to claim 6 is it is characterised in that described standardized data acquiring unit includes：
Data normalization unit, for based on described weather traffic index data and translation standard deviation formula, obtaining normalization
Weather traffic index data；
Data normalization unit, after described data normalization cell processing, is then based on translating extreme difference formula, obtains standard
Change weather traffic index data；
Distance matrix acquiring unit, after described data normalization cell processing, according to euclidean distance method, obtains described standard
Change the distance matrix of weather traffic index data.
10. device according to claim 6 it is characterised in that described weather data and with described weather data in institute
The traffic data stating coupling in seclected time section includes METAR and TAF message.
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| CN201611190232.3A CN106407735A (en) | 2016-12-20 | 2016-12-20 | Weather and traffic visualization method and device |
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