A kind of station passenger flow pressure prediction and statistical analysis technique and its systemTechnical field
The invention belongs to railway transport of passengers intellectualized technology field, specially a kind of station passenger flow pressure prediction and statistical analysisMethod and its system.
Background technology
With the high speed development of the railway transportations such as motor-car, high ferro, railway is with advantage safely, quickly, comfortable, inexpensive, oneIt is directly the main means of transport of people's trip, according to the official's data announced, the china railway spring transportation volume of the flow of passengers reaches 2.4 within 2013Hundred million, increase by 12.1% on a year-on-year basis, the china railway spring transportation volume of the flow of passengers reaches 2.66 hundred million within 2014, and the volume of the flow of passengers increases year by year, 2015 yearsThe china railway spring transportation volume of the flow of passengers reaches 2.95 hundred million person-times, and the odd-numbered day all reaches more than 800 ten thousand passenger flow transport, just usually, railway stationBe also overstaffed, this is that railway work brings huge pressure, in order to the interior passenger that maintains to stand order, ensure the peace of passengerEntirely, it usually needs increase human and material resources to be dredged, monitoring device can be all typically installed in station, monitoring device can be figureAs real-time Transmission is to Central Control Room, but staff has found the region for dredging personnel in need from Central Control Room, notifies in station itWhen its staff goes treatment, often due to passenger is excessive, it is impossible to timely arrive in and process, especially there are illegal incidents,Can not timely be resolved；Further, the ticket sales volume of each train also has large effect to passenger flow situation, sellThe many certainty volumes of the flow of passengers of amount are also more, and do not connect volume of the flow of passengers distribution situation and ticketing quantity carries out research spy in the prior artBeg for, be so unfavorable for solving the problems, such as that station passenger flow pressure is most basic, govern the development of railway transportation.
The content of the invention
In order to solve the above problems, the invention provides a kind of station passenger flow pressure prediction and statistical analysis technique and its it isSystem, the purpose of realization is that the station that can predict future time carries passenger flow pressure, it is also possible to which the real-time station of statistical analysis carriesPassenger flow pressure, for giving plan capacity, the reference of the valid data such as intelligent scheduling, station is worked and realize intelligent automation,Traditional experience accumulation is no longer relied solely on, laminating actual conditions are maximized, is that the specific arrangement of station work gives essence the mostReally, effectively instruct.
To achieve these goals, the present invention provides following technical scheme：A kind of station passenger flow pressure that the present invention is providedPrediction and statistical analysis technique, comprise the following steps：
S1, configuration different time sections, train number correspondence are waited and multiply the topology data in region, the topology data include from date,Close Date, entry-into-force time, train number and time multiply the data of region corresponding relation；
S2, current volume of the flow of passengers data are counted, and/or non-flow of guests data are made prediction, volume of the flow of passengers dataIncluding day part enter the station total number of persons data and calculated according to S1 topology datas, each time for obtaining of statistics multiplies region number data,And generate visualization display.
Each railway station multiplies the corresponding related data in region for train number and time, and it refers to big waiting room, ticket checking that time multiplies regionRoom etc., as motor-car, the various trains of high ferro open fortune, time multiplies region is also no longer only waiting room, many ticketing spot passagesAll become time and multiply region, the train number with wait that to multiply the corresponding topology data in region can be newly-built, or script trainStand what is just had, can be introduced directly into or be directly to carry out part modification original, using the inventive method, can be withVisualization display is automatically made to the passenger flow pressure that current station carries, made staff's simplicity, clearly understood the volume of the flow of passengersDistribution situation, so as to carry out arrangement and planning in advance, intelligentized operation is realized using computer, instead of artificial work, is subtractedThe workload of light work personnel, the raising degree of accuracy, raising operating efficiency.
Further, in the S1 topology datas from date, Close Date refer to use the start-stop of the topology dataDate, when the entry-into-force time refers to the specific execution within the cycle using placement scheme data.Such as newly-built topology dataFrom date is on January 1st, 2017, and the Close Date is on 2 2nd, 2017, and the entry-into-force time is daily 15 points to 24 points, then existIn on January 1st, 2017 to 2 months 2 this periods in 2017,15 points to 24 points daily this section of moment, are according to newly-built clothOffice data, train number and time multiply region to be carried out corresponding, makes the execution of placement scheme data more flexible, convenient adjustment, for shouldFor there is bigger practicality in practice.
Further, configuration station capacity data are also included in the S1, station capacity data include freight volume data and fortuneThe corresponding each train number of amount data sells ticket data, and the freight volume data always sell ticket data daily for the station.
Further, the method non-flow of guests data made prediction in the S2：According to history freight volume data with it is pre-Survey the same day configuration freight volume data similarity, calculate, statistics predicted on the day of volume of the flow of passengers data.
Further, the method non-flow of guests data made prediction in the S2：According to history freight volume data with it is pre-The freight volume data of same day configuration are surveyed, each train number of history sells ticket data and sells the similar of ticket data to each train number of configurationDegree, calculates the volume of the flow of passengers data on the day of each train number is predicted, statistics predict on the day of enter the station, respectively time multiply region volume of the flow of passengers numberAccording to.Station freight volume data are actually the total transport number in daily station, are carried with passenger flow on the freight volume data theory of station and pressedPower has direct relation, and the station always sells that ticket quantity is more daily, and the station number to be carried is also more, imply that visitorFlowing pressure also can be bigger, so when to future time passenger flow forecast pressure, freight volume data are different, specific volume of the flow of passengers dataDifference, using the station freight volume data on the day of prediction to the volume of the flow of passengers Data correction predicted, maximizes laminating actual conditions, makes pre-Survey data and effectively data basis are provided.
Preferably, the station freight volume data are obtained and real-time update data from Railway Passenger Ticket System.Railway passenger tickets systemSystem refers to the billing printing system of China's Railway Passenger Transportation, including Railways Ticketing and reservation, and station fortune is obtained from Railway Passenger Ticket SystemAmount data are mode the most accurate.
Further, when configuring topology data in the S1, obtain train number from trip's dress system and multiply region corresponding relation with timeData, and real-time update data trip dress system refers to Passenger information service integrated control system, and the system is believed with railways train operationBased on breath, integrated use modern communication technology, control technology and network technology provide the user collection digital video monitoring, numberWord broadcast, synthesis display, spot announcement train announcement, traveler guiding, information inquiry, manually seek help, clock system, intrusion alarm andThe novel intelligent integrated system that the equipment such as illumination, power supply are automatically controlled, from trip, dress system direct access train number correspondence time multiplies regionPlacement scheme data, it is more intelligent, without staff craft typing, also cause placement scheme data it is more accurate.
Further, the S2 includes receiving train arrival and leaving information from trip dress system, according to photos and sending messages amendment passenger flowAmount data, and generate visualization display.When statistics can currently measure data, in order to ensure real-time, adapt to train work state,Accurately the data-intensive situation of the volume of the flow of passengers is embodied, train arrival and leaving information is received from trip's dress system, when Train delay, thisThe passenger that should be checked is detained due to not checking, so keeping the number not checked when carving statistics volume of the flow of passengers data, is learningWhen train has arrived at a station, then the patronage that ticket gets on the bus will have been examined cut.
Further, the method for configuring different time sections topology data：From date is verified, if there is identicalFrom date, then return to miscue, if it is different, then by program data storage.The inventive method can help staffIn newly-built, importing, modification placement scheme data, whether the topology data of the new configuration of checking configures repetition, when staff's mistakeDuring operation, then prompting can be produced.
Further, when being verified to from date, if from date is different, the Close Date is further verified, ifHave lap with the history topology data time period, history topology data and newest topology data are split, fractionation it is specificMethod is：Retain the topology data of underlapped part, lap is performed according to newest topology data, finally new formation is moreIndividual topology data is arranged according to from date increasing.In view of the complexity of actual conditions, topology data might have overlapWhen, the inventive method automatic Verification and can form new placement scheme and be used for staff.
Further, when the topology data of different time is configured in the S1, in copying history topology data to copy,Generation user prompting and/or the entry-into-force time according to configuration, the automatic topology data for performing the latest configuration time, setup time isThe time that configuration operation is completed.Maximum laminating actual conditions, can be such that staff is arbitrarily selected according to actual conditions, maximizeEnsure that flexibility.
Further, the method that current volume of the flow of passengers data are counted is included in the S2：
S21, passenger flow information data are obtained, the passenger flow information data include that current passenger of entering the station rides secondary, Cheng KejinStand the time, the time of departure, earliest allow the time of entering the station, start the ticket checking time, terminate the ticket checking time；
S22, entered the station demographics to day part, each train number respectively, then all train number day parts are entered the station number superposition, is obtainedEntered the station total number of persons data to day part；
S23, the topology data according to S1, will belong to one and wait and multiply the corresponding number of entering the station of all train numbers in region and tire outMeter, obtains each number data waited and multiply region.
Further, the method in the S2 to non-flow of guests data prediction includes：
S24, obtain the station history passenger flow information data, the passenger flow information data include train number, passenger enter the station the time,Enter the station number, the time of departure, earliest allow the time of entering the station, start the ticket checking time, terminate the ticket checking time；
S25, set up each train number passenger and enter the station the functional relation of number of entering the station in time and the time period that allows to enter the station earliest；
S26, the functional relation using S25, by each train number, the number superposition of entering the station of day part, obtain day part and enter the station alwaysNumber data, according to the topology data of S1, count each number data waited and multiply region, the volume of the flow of passengers data predicted.
Further, the history passenger flow information data for being obtained in S24 also include station capacity data, using S25's in S26Functional relation, each train number predicted, the number A that enters the station of day part, configuration prediction same day station capacity data, according to historyEach train number sells ticket data N, each train number to prediction same day configuration and sells ticket data M, is calculated each on the day of predictionThe number R that enters the station of train number, day part, the formula of calculating is R=Ax (M/N), then each train number is entered the station number R superpositions, obtains pre-Same day day part is surveyed to enter the station total number of persons data；According to the topology data of S1, will belong to one wait multiply each train number in region, it is each whenThe number R that enters the station of section adds up, each on the day of obtaining prediction to wait the number data for multiplying region.
Further, default volume of the flow of passengers early warning value, the volume of the flow of passengers data that will be obtained and early warning value ratio are also included in the S2It is right, generate visual early warning information.The time of staff oneself comparison is saved, automatic comparison is realized using computer,And the situation of early warning is displayed, more get information about passenger flow dense degree.
Further, the method also include S3, according to volume of the flow of passengers data, the densely distributed time of the volume of the flow of passengers is multiplied into institute in regionCorresponding train number, the train number is adjusted to volume of the flow of passengers distribution pine by the time of departure, ticket checking time according to the train number, the train number numberScattered time multiplies region, and the topology data generated after adjustment is kept in, generation user's prompting.When estimating time and multiply region and may go outWhen existing intensive, will cause to wait to multiply the intensive train number of region number and be adjusted to the scattered time of volume of the flow of passengers distribution and multiply region, generation is preferredTopology data, for staff refer to, so ensure when on the day of reality, each time multiply the region volume of the flow of passengers rationally, train number peaceRow is reasonable.
Further, also include multiplying region volume of the flow of passengers data according to each time in the S3, multiply without loose time of volume of the flow of passengers distributionDuring region, freight volume data are adjusted, according to freight volume data order from big to small, each time is calculated again and multiplies region volume of the flow of passengers numberAccording to, the topology data after the freight volume data of each adjustment, adjustment freight volume data is kept in, generation user points out.Theoretically comeSay, freight volume is more, time multiplies region, and the intensive probability of passenger flow occur bigger, so, when the result of prediction multiplies region without loosely waitingWhen, computer can Automatic sieve select the station freight volume data being best suitable for, provide and effectively count for staff plans same day capacityAccording to reference.
The invention also discloses the system for realizing the above method, including topology data configuration module, volume of the flow of passengers data displayModule, topology data configuration module is used to configure the topology data that the corresponding time of different time, train number multiplies region, the topology data bagInclude the data that from date, Close Date, entry-into-force time, train number and time multiply region corresponding relation；
The volume of the flow of passengers data disaply moudle is used to be counted to current volume of the flow of passengers data, and/or to following passenger flowAmount data are made prediction, and generate visualization display, and volume of the flow of passengers data multiply region including enter the station total number of persons data, each time of day partNumber data.
Further, the system also includes station capacity data configuration module, for showing and screening station capacity data,Station capacity data sell ticket data including freight volume data each train number corresponding with freight volume data, and the freight volume data are shouldTicket data are always sold daily in station.
Further, the volume of the flow of passengers data disaply moudle including day part enter the station total number of persons data disaply moudle, each waitMultiply region number data disaply moudle.
Further, topology data configuration module and trip's dress system data transfer.
Further, station capacity data configuration module and railway customer service system data transfer.
Further, the system also includes warning module, and warning module can be used to preset early warning value, by early warning value and calculatingThe volume of the flow of passengers data for obtaining compare, and generate visual early warning situation.
Further, system also includes adjust automatically topology data module, and adjust automatically topology data module is used for basisVolume of the flow of passengers data, corresponding train number in region is multiplied by the densely distributed time of the volume of the flow of passengers, the time of departure, ticket checking according to the train numberTime, the train number number, are adjusted to the train number the loose time of volume of the flow of passengers distribution and multiply region, and will generate the topology data after adjustmentIt is temporary, generation user's prompting.
The further system also includes adjustment station capacity data module, according to volume of the flow of passengers data, detects without looseWait region when, according to freight volume data order from big to small, each time is calculated again and multiplies region volume of the flow of passengers data, will be eachThe record for adjusting station capacity data is kept in, generation user's prompting.
The present invention uses above-mentioned technical proposal, including following beneficial effect：Height is intelligent, automation is realized to current visitorThe statistics of flow pressure, following passenger flow pressure prediction, and various statistical analyses can be made to Trip distribution situation as needed, subtractThe workload of light work personnel, make station staff in time, clearly understand volume of the flow of passengers situation, with this come adjust people in timePower, material resources, effectively evacuate passenger flow, keep the stabilization, in order at station.
Brief description of the drawings
Fig. 1 is flow chart of the present invention；
Fig. 2 is that the day part counted in embodiment one enters the station total number of persons curve map；
Fig. 3 multiplies region number data column diagram respectively to be waited in embodiment one；
Fig. 4 is the total number of persons curve map that entered the station to the day part of current statistic in embodiment one, and area under the curve 1 multiplies region for timeOne volume of the flow of passengers data area-graph, area under the curve 2 multiply volume of the flow of passengers data area-graph, the area under the curve 3 in region two to wait for time multipliesThe volume of the flow of passengers data area-graph in region three, area under the curve 4 multiply the volume of the flow of passengers data area-graph in region four to wait；
Fig. 5 is to predict that following passenger flow data enters the station time and the functional relationship model of the number of entering the station in embodiment one；
Fig. 6 is station passenger flow pressure prediction and the system of statistical analysis in embodiment one；
Fig. 7 multiplies the volume of the flow of passengers data in region for the 4th time predicted in embodiment two, and peak area 5 is the people of entering the station of G5 train numbersNumber data, peak area 6 is the number data that enter the station of G6 train numbers, and peak area 7 is the number data that enter the station of G7 train numbers.
Specific embodiment
The present invention is described in further detail below by specific embodiment and with reference to accompanying drawing.
Embodiment one：Shown in reference picture 1, a kind of station passenger flow pressure prediction and statistical analysis technique that the present invention is provided,Comprise the following steps：
S1, configuration different time sections, train number correspondence are waited and multiply the topology data in region, the topology data include from date,Close Date, entry-into-force time, train number and time multiply the data of region corresponding relation：From date, Close Date refer to using the clothThe commencement date and deadline of office data, the entry-into-force time refers to specific when performing within the cycle using placement scheme data, such as table oneShown a topology data；
S2, current volume of the flow of passengers data are counted, and/or non-flow of guests data are made prediction, volume of the flow of passengers dataIncluding day part enter the station total number of persons data and calculated according to S1 topology datas, each time for obtaining of statistics multiplies region number data,And generate visualization display.
Table one
| From date | 2017.1.1 |
| Close Date | 2017.2.2 |
| Entry-into-force time | Daily 15:00-24:00 |
| Time multiplies region one | G1 train numbers, G2 train numbers, G3 train numbers |
| Time multiplies region two | T256 train numbers, Z156 train numbers, T161 train numbers |
| Time multiplies region three | G242 train numbers, G212 train numbers, G138 train numbers |
Upper table shows to use the topology data within 2017.1.1-2017.2.2 this periods, and the entry-into-force time is daily15:00-24:00, G1 train numbers, G2 train numbers, G3 train numbers multiply the waiting of region one and ride in time in this part of topology data.
Wherein, the Close Date, the entry-into-force time can default setting, for choosing fill out item, system can be given tacit consent to automatically, such as closing dayPhase does not fill out, then be defaulted as use time to 9999-99-99, and the entry-into-force time is since 2017.1.1 zero points, to closing dayThis period of phase, this topology data comes into force always.
Preferably, during above-mentioned configuration topology data, the data that train number multiplies region corresponding relation with time are obtained from trip's dress system.
Specifically, the method for being counted to current volume of the flow of passengers data in the S2, can use the most simply to entering the stationPatronage adds up, and obtains the visual presentation of curve map, column diagram, such as shown in Fig. 2 and Fig. 3, the bag of preferred methodInclude：
S21, passenger flow information data are obtained, the passenger flow information data include that current passenger of entering the station rides secondary, Cheng KejinStand the time, the time of departure, earliest allow the time of entering the station, start the ticket checking time, terminate the ticket checking time, such as shown in table two；
S22, entered the station to day part, each train number patronage statistics respectively, then all train number day part numbers of entering the station are foldedPlus, obtain day part and enter the station total number of persons data；
S23, the topology data according to S1, will belong to one and wait and multiply the corresponding number of entering the station of all train numbers in region and tire outMeter, obtains each number data waited and multiply region.As shown in figure 4, transverse axis represents the time for recording the patronage that enters the station, the longitudinal axis is representedEnter the station patronage, and area under the curve 1 multiplies the volume of the flow of passengers data area-graph in region one, area under the curve 2 to wait for time multiplies region twoVolume of the flow of passengers data area-graph, area under the curve 3 multiply volume of the flow of passengers data area-graph, the area under the curve 4 in region three to wait for time multiplies regionFour volume of the flow of passengers data area-graph, first obtains each train number passenger flow inbound case, then is overlapped, and generates heating power area-graph, both may be usedTo see the total number of persons situation that enters the station, also allow for statistics and wait the Trip distribution situation for multiplying region, save and calculate, count volume of the flow of passengers dataTime, quickly generate visualization display, the collection of illustrative plates for obtaining various visualization displays are directly using disclosed in prior artProgram code；
Table two
Upper table show and has counted the number of entering the station every 5min, and this time period can arbitrarily select.
Further, the volume of the flow of passengers data of future time can also be predicted using the inventive method, in the S2Method to non-flow of guests data prediction includes：
S24, obtain the station history passenger flow information data, the passenger flow information data include train number, passenger enter the station the time,Enter the station number, the time of departure, earliest allow the time of entering the station, start the ticket checking time, terminate the ticket checking time, it is as shown in Table 2, selectedThe historical data for taking, is prediction the previous day on the same day, or the same period last year or is identical working day or festivals or holidays, in a word withThe maximum laminating prediction same day is defined；
S25, set up each train number passenger and enter the station the functional relation of number of entering the station in time and the time period that allows to enter the station earliest, adoptThe functional relation of each train number is set up with SPSS, such as shown in Fig. 5, observed value is the historical data transferred, and transverse axis enters for passengerThe time stand with to allow the minute entered the station earliest poor, the longitudinal axis is entered the station number for the period, it can be seen that sample data is closed with the functionSystem fits the most, and the functional relation for obtaining is y=0.0000046t3+0.001t2- 0.148t+6.3, wherein t for passenger enter the station whenBetween with to allow the minute of the time of entering the station earliest poor, y is corresponding number, and the curve according to Fig. 5 then can be to the prediction same dayThe volume of the flow of passengers number of all periods is calculated；
S26, the functional relation using S25, by each train number, the number superposition of entering the station of day part, obtain day part and enter the station alwaysNumber data, according to the topology data of S1, count each number data waited and multiply region, the volume of the flow of passengers data predicted.
The system for realizing the above method, as shown in fig. 6, including topology data configuration module, volume of the flow of passengers data disaply moudle,Topology data configuration module is used to configure the topology data that the corresponding time of different time, train number multiplies region, and the topology data includesDate, Close Date, entry-into-force time, train number and the time of beginning multiply the data of region corresponding relation；
The volume of the flow of passengers data disaply moudle is used to be counted to current volume of the flow of passengers data, and/or to following passenger flowAmount data are made prediction, and generate visualization display, and volume of the flow of passengers data multiply region including enter the station total number of persons data, each time of day partNumber data.
The volume of the flow of passengers data disaply moudle multiplies region number including enter the station total number of persons data disaply moudle, each time of day partData disaply moudle.Day part enters the station the calculating logic program of the embedded S21-S23 methods of total number of persons data disaply moudle, and each time multipliesRegion number data disaply moudle embeds the calculating logic program of above-mentioned S24-S26 methods, is used to realize the above method.
Topology data configuration module and trip's dress system data transfer, are used to receive the cloth inning that train number correspondence time multiplies regionAccording to.
Embodiment two：A kind of station passenger flow pressure prediction and statistical analysis side that a kind of present invention disclosed by the invention is providedMethod, comprises the following steps：
S1, configuration different time sections, train number correspondence are waited and multiply the topology data in region, the topology data include from date,Close Date, entry-into-force time, train number and time multiply the data of region corresponding relation：From date, Close Date refer to using the clothThe commencement date and deadline of office data, the entry-into-force time refers to specific when performing within the cycle using placement scheme data, such as table oneShown a topology data；
S2, current volume of the flow of passengers data are counted, and/or non-flow of guests data are made prediction, volume of the flow of passengers dataEntered the station total number of persons data including day part, calculated according to S1 topology datas, each time that statistics is obtained multiplies region number data, and it is rawShown into visualization.
Further, configuration station capacity data are also included in the S1, station capacity data include freight volume data and fortuneThe corresponding each train number of amount data sells ticket data, and the freight volume data always sell ticket data daily for the station；The carCapacity of standing data are obtained from Railway Passenger Ticket System.
When configuring topology data in the S1, the data that train number multiplies region corresponding relation with time can be obtained from trip's dress system.
When current volume of the flow of passengers data are counted, the current traffic data, each obtained from Railway Passenger Ticket System can be shownTrain number sells ticket data.
When to following passenger flow forecast, non-flow of guests data are made prediction method in the S2：According to historyFreight volume data with prediction the same day configuration freight volume data similarity, such as ratio, calculate, statistics predicted on the day of passenger flowAmount data.Volume of the flow of passengers data for example from 180,000 couples of 2017.2.6 of 2017.2.2 freight volumes data are predicted, and 2017.2.6 is totalTicketing quantitative forecast is that 220,000, i.e. freight volume data are 220,000, therefore 2.6 day part enters the station, total number of persons, each time multiply the number in regionNecessarily with having a tremendous difference on the day of predicting, therefore predicted with prediction same day freight volume ratio data with history freight volume dataData can improve accuracy.
It is more highly preferred to, non-flow of guests data are made prediction method in the S2：According to history freight volume data withThe freight volume data of prediction same day configuration, each train number of history sells ticket data and sells the similar of ticket data to each train number of configurationDegree, such as ratio calculates the volume of the flow of passengers data on the day of each train number is predicted, statistics predicted on the day of enter the station, Ge Houcheng areasDomain volume of the flow of passengers data.
Specific method includes：S24, obtain the station history passenger flow information data, the passenger flow information data include train number,Passenger enter the station the time, the number that enters the station, the time of departure, earliest allow the time of entering the station, start the ticket checking time, terminate the ticket checking time；
S25, set up each train number passenger and enter the station the functional relation of number of entering the station in time and the time period that allows to enter the station earliest；
S26, the functional relation using S25, by each train number, the number superposition of entering the station of day part, obtain day part and enter the station alwaysNumber data, according to the topology data of S1, count each number data waited and multiply region, the volume of the flow of passengers data predicted.
The history passenger flow information data obtained in S24 also include station capacity data, using the functional relation of S25 in S26,Each train number, the number A that enters the station of day part for being predicted, configuration prediction same day station capacity data, according to each train number hair of historySell ticket data N, to prediction the same day configuration each train number sell ticket data M, be calculated prediction on the day of each train number, it is each whenThe number R that enters the station of section, the formula of calculating is R=Ax (M/N), then each train number is entered the station number R superpositions, obtain the prediction same day it is each whenDuan Jinzhan total number of persons data；According to the topology data of S1, one will be belonged to and wait each train number, the people of entering the station of day part for multiplying regionNumber R adds up, each on the day of obtaining prediction to wait the number data for multiplying region, as shown in fig. 7, for a certain time chosen multiplies region, for exampleTime multiplies volume of the flow of passengers data in region 4, and peak area is the number data that enter the station of a certain train number, and such as peak area 5 enters for G5 train numbersNumber of standing data, peak area 6 is the number data that enter the station of G6 train numbers, and peak area 7 is the number data that enter the station of G7 train numbers, generationVisualization display can be diversified forms, such as simple curve map, scatter diagram, column diagram etc., and what the present embodiment was enumerated isArea-graph, when area-graph is made, can calculate each train, the day part number of entering the station and account for this train and sell ticket number and obtainPercentage, and then data basis are obtained to do area-graph, preferred this visual means wait the volume of the flow of passengers for multiplying region in statisticsDuring data, it can also be appreciated that the number situation that enters the station of each train number.
From Railway Passenger Ticket System obtain away from prediction the same day 30 days in part station capacity data, as shown in table 3：
Each train sells ticket data under the different freight volume data of table three
| Train number | 130000 | 150000 | 160000 | 180000 |
| 1134 | 0 | 0 | 0 | 0 |
| 1136 | 0 | 0 | 0 | 0 |
| 1303 | 934 | 1067 | 1134 | 1334 |
| 1487 | 934 | 1067 | 1134 | 1334 |
| 3009 | 1145 | 1309 | 1391 | 1636 |
| 3021 | 1019 | 1165 | 1238 | 1456 |
| 3093 | 1226 | 560 | 1489 | 1752 |
| D20001 | 490 | 938 | 594 | 1310 |
| D2003 | 820 | 938 | 996 | 1577 |
| G1559 | 820 | 938 | 996 | 630 |
| G1563 | 820 | 938 | 996 | 1055 |
The capacity data (part) of prediction same day configuration are for example shown in table 4：
Table four：Each train sells ticket data under prediction same day freight volume data
As shown in table three, table four, such as choose 180,000 freight volume data to be predicted, and predict the freight volume data of same day configurationIt is 260,000, then each train data will be modified with two ratios of freight volume, is more accurately obtained the prediction same dayVolume of the flow of passengers data.
The present embodiment also discloses the system for realizing the above method, including topology data configuration module, volume of the flow of passengers data showShow module, topology data configuration module is used to configure the topology data that the corresponding time of different time, train number multiplies region, the topology dataMultiply the data of region corresponding relation including from date, Close Date, entry-into-force time, train number and time；
The volume of the flow of passengers data disaply moudle is used to be counted to current volume of the flow of passengers data, and/or to following passenger flowAmount data are made prediction, and generate visualization display, and volume of the flow of passengers data multiply region including enter the station total number of persons data, each time of day partNumber data.
The system also includes station capacity data configuration module, for showing and screening station capacity data, station capacityData sell ticket data including freight volume data each train number corresponding with freight volume data, and the freight volume data are that the station is dailyAlways sell ticket data.
The volume of the flow of passengers data disaply moudle multiplies region number including enter the station total number of persons data disaply moudle, each time of day partData disaply moudle.
Topology data configuration module and trip's dress system data transfer, station capacity data configuration module and railway customer service systemData transfer.
Embodiment three：Except technical scheme disclosed in above-described embodiment one, two, in order to further optimize this hairBright method, the method that different time topology data is configured in the S1：From date is verified, if there is identical startingDate, then miscue is returned to, if it is different, then by program data storage.
When being verified to from date, if from date is different, the Close Date is further verified, if being laid out with historyData time section has lap, and history topology data and newest placement scheme data are split, and the specific method of fractionation is：Retain the placement scheme data of underlapped part, lap is performed according to newest cloth data, the last new multiple cloth for being formedOffice's protocol is arranged according to from date increasing.
For example, the history protocol time period is 2017.1.2-2017.3.25, when in newly-installed placement scheme dataBetween section be 2016.12.1-2017.2.1, then the date of lap be 2017.1.2-2017.2.1, then the inventive method retain2016.12.1-2017.1.1, the placement scheme data of 2017.2.2-2017.3.25, lap 2017.1.2-2017.2.1According to newly-installed execution, the three placement scheme data arrangements order that will finally obtain is：
(1)2016.12.1-2017.1.1；
(2)2017.1.2-2017.2.1；
(3)2017.2.2-2017.3.25。
When the topology data of different time is configured in the S1, in copying history topology data to copy, user is generatedPrompting and/or the entry-into-force time according to configuration, the automatic topology data for performing the latest configuration time, setup time operate for configurationThe time of completion.Placement scheme data as escribed above, user can select to be continuing with the cloth of 2017.1.2-2017.3.25Office's protocol, it is also possible to which selection uses amended three placement scheme data, or automatic according to the latest configuration timeAutomatically perform.
Also include default volume of the flow of passengers early warning value in the S2, volume of the flow of passengers data and the early warning value that will be obtained are compared, and generation canDepending on the early warning information changed, such as shown in following table：
Staffing refers to station same day maximum seating capacity, and early warning number refers to the current total number of persons that enters the station, typically in trainStanding an early warning value of can all preset, real-time scale refers to the percentage of early warning number and staffing.For another example wait and multiply regional early warning information,It is as shown in the table：
Generating form, or curve map, thermodynamic chart, scatter diagram that visual display can be above table is allCan with.
It should be noted that the inventive method may each be any language of the those skilled in the art using computerTo realize.
The system for completing the above method, except system disclosed in embodiment one, two, also including warning module, warning moduleCan be used to preset early warning value, early warning value is compared with the volume of the flow of passengers data being calculated, generate visual early warning situation.
Example IV：Except technical solution of the present invention disclosed in embodiment one to three, in order to further optimize present invention sideMethod, the method also includes S3, according to volume of the flow of passengers data, and the densely distributed time of the volume of the flow of passengers is multiplied into corresponding train number in region, rootAccording to the time of departure of the train number, ticket checking time, the train number number, the train number is adjusted to the loose time of volume of the flow of passengers distribution and multiplies region,And keep in the topology data generated after adjustment, generation user's prompting.
Further, also include multiplying region volume of the flow of passengers data according to each time in the S3, multiply without loose time of volume of the flow of passengers distributionDuring region, freight volume data are adjusted, according to freight volume data order from big to small, each time is calculated again and multiplies region volume of the flow of passengers numberAccording to, the topology data after the freight volume data of each adjustment, adjustment freight volume data is kept in, generation user points out.
The inventive method can also multiply the loose situation in region and make detection to the time of prediction, and repetitive cycling is calculated each timeMultiply region volume of the flow of passengers data, until pointing out user by having loose time when multiplying region, adjust automatically train number is also the sameSituation, after adjustment train number, i.e. adjustment placement scheme data, starts repetitive cycling and calculates each volume of the flow of passengers data waited and multiply region, directlyTo there is optimal scheme, for user's selection.
To counting during current volume of the flow of passengers data, it is contemplated that actual capabilities can occur various situations, such as Train delay etc., enterOne-step optimization includes receiving train arrival and leaving information from trip dress system for the S2, according to photos and sending messages amendment volume of the flow of passengers data,And generate visualization display.For example in S2 will belong to one wait multiply region all train numbers enter the station demographics when, at 10 pointsAt this moment, it is not in passenger flow early warning situation that the train of a certain train number should be checked and the time is multiplied region, but at thisCarve, the train number is late, causes to check, therefore at this time point, may just occur that passenger flow is intensive and alarm condition occur,With trip's dress system information transfer, it is ensured that the passenger flow bearing capacity of statistics is the most accurate.
The system for realizing the present embodiment method, except disclosed in embodiment one to three, the system also includes adjust automatically clothOffice data module, adjust automatically topology data module is used for according to volume of the flow of passengers data, and the densely distributed time of the volume of the flow of passengers is multiplied into regionIn corresponding train number, the train number is adjusted to the volume of the flow of passengers point by the time of departure, ticket checking time according to the train number, the train number numberThe loose time of cloth multiplies region, and generates the topology data after adjustment and keep in, generation user's prompting.
The system also includes adjustment station capacity data module, according to volume of the flow of passengers data, detects without loose region of waitingWhen, according to freight volume data order from big to small, each time is calculated again and multiplies region volume of the flow of passengers data, will every time adjust stationThe record of capacity data is kept in, generation user's prompting.
It should be noted that above method step is computerization language of the those skilled in the art using any one formRealize.
The preferred embodiments of the present invention are the foregoing is only, is not intended to limit the invention, for the skill of this areaFor art personnel, the present invention can have various modifications and variations.It is all within the spirit and principles in the present invention, made any repairChange, equivalent, improvement etc., should be included within the scope of the present invention.