Air ticket revising recommendation system based on data analysis

Abstract

The invention discloses an air ticket revising recommendation system based on data analysis, relates to the technical field of air ticket revising recommendation, and solves the technical problems that in the prior art, risk early warning cannot be performed when external factor analysis and internal factor analysis are normal, and the operation efficiency of air ticket revising is reduced. The method specifically comprises the following steps: carrying out risk early warning on an analysis unit which has no influence on external factors and internal factors, and carrying out prediction according to real-time risk early warning so as to reasonably carry out flight period change; according to the method, real-time data acquisition and analysis are carried out on an analysis unit needing flight period change, flight period change alternatives or selections are provided for the analysis unit through data acquisition and analysis, a proper route can be matched in time when the flight needs period change, the period change efficiency of the analysis unit is guaranteed, and the influence caused by period change is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of air ticket rescheduling recommendation, and in particular to an air ticket rescheduling recommendation system based on data analysis. Background Art

[0002] The ticket rescheduling recommendation system is an intelligent service system designed to help passengers handle ticket rescheduling needs more conveniently and efficiently; in short, the ticket rescheduling recommendation system provides passengers with more convenient, efficient and personalized ticket rescheduling services by integrating information, optimizing algorithms and improving user experience.

[0003] The patent with publication number CN113379084A discloses a ticket rescheduling method and a ticket rescheduling device. The method determines the passengers and flight segments to be rescheduled that need to be rescheduled in the ticket order to be rescheduled; judges whether the passengers and flight segments to be rescheduled meet the rescheduling strategy rules matching the ticket order to be rescheduled; if so, determines the target rescheduling time to which the flight segment to be rescheduled needs to be rescheduled, and generates rescheduling segment data that meets the conditions based on the flight segment to be rescheduled and the target rescheduling time; determines the target rescheduling flight to be rescheduled in the rescheduling segment data, and issues a ticket for the target rescheduling flight; because the temporary ticket order in the ticket order to be rescheduled is an order with the same data format as the system ticket order obtained after data aggregation of the ticket orders sold through the distribution channels, it can realize self-service rescheduling for passengers who purchase tickets through all channels, and solves the problem that the existing method can only support rescheduling through the original booking channel but cannot support rescheduling through all channels.

[0004] With reference to the above patent documents and in combination with the actual application scenarios of the system, the following questions can be raised:

[0005] 1. When the rescheduling system is running, in addition to matching the real-time order rescheduling, it is unable to infer the risk of the current ticket rescheduling through flight passenger data collection and analysis, resulting in the problem of untimely warning;

[0006] 2. After completing data collection and analysis, it is not possible to make intelligent recommendations for rescheduling. When the rescheduling system is running, the accuracy of rescheduling order recommendations is low, and the feasibility of rescheduling cannot be guaranteed.

[0007] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0008] The purpose of the present invention is to solve the above-mentioned problems and to propose a flight ticket rescheduling recommendation system based on data analysis.

[0009] The purpose of the present invention can be achieved through the following technical solutions:

[0010] A flight ticket rescheduling recommendation system based on data analysis includes a flight ticket planning platform, wherein the flight ticket planning platform is connected to:

[0011] The external factor analysis unit performs external factor analysis on the analysis unit, obtains the external factor information of each analysis unit, substitutes it into the formula to obtain the external factor analysis coefficient corresponding to the analysis unit, and infers whether the external factor analysis is normal based on the comparison of the external factor analysis coefficient;

[0012] The internal factor analysis unit performs internal factor analysis on the analysis unit, obtains the internal factor information of each analysis unit, substitutes it into the formula to obtain the internal factor analysis coefficient corresponding to the analysis unit, and infers whether the internal factor analysis is normal based on the comparison of the internal factor analysis coefficient;

[0013] After completing the external factor analysis and the internal factor analysis, and when they are all normal, the risk warning unit will issue a risk warning to the analysis units that are not affected by the external and internal factors.

[0014] As a preferred embodiment of the present invention, the external factor analysis information includes the analysis unit's scheduled flight's parking period, the corresponding numerical ratio of the increase in the span of the equipment operation and maintenance time during the standby period and the decrease in the remaining time of the current standby period excluding the operation and maintenance time, the analysis unit's scheduled flight's current time prediction of the floating span of weather parameters in the take-off area and the actual floating span, the analysis unit's scheduled flight's current time prediction of the floating span and the actual floating span, the analysis unit's scheduled flight's flight trajectory overlaps with the actual external flight trajectory and the set flight passage time interval shortening speed.

[0015] As a preferred implementation of the present invention, if the external factor analysis coefficient corresponding to the analysis unit exceeds the external factor analysis coefficient threshold, the current external factor analysis is judged to be abnormal; if the external factor analysis coefficient corresponding to the analysis unit does not exceed the external factor analysis coefficient threshold, the current external factor analysis is judged to be normal.

[0016] As a preferred embodiment of the present invention, the internal factor information includes the shortest travel time of all means of transportation corresponding to the distance between the current location of the analysis unit and the airport location of the scheduled flight, the floating span of the real-time travel speed in the travel period starting from the current moment corresponding to the distance, and the non-overlapping duration between the shortest travel time and the flight departure time corresponding to the shortest travel time transportation plan selected by the analysis unit.

[0017] As a preferred embodiment of the present invention, if the intrinsic factor analysis coefficient corresponding to the analysis unit exceeds the intrinsic factor analysis coefficient threshold, the intrinsic factor analysis of the analysis unit is judged to be abnormal; if the intrinsic factor analysis coefficient corresponding to the analysis unit does not exceed the intrinsic factor analysis coefficient threshold, the intrinsic factor analysis of the analysis unit is judged to be normal.

[0018] As a preferred embodiment of the present invention, the risk warning unit operates as follows:

[0019] The current system time and the flight departure time of the analysis unit are set as the risk warning period, and the external factor analysis coefficient and the internal factor analysis coefficient of the analysis unit at each time are collected during the risk warning period. At the same time, the external factor analysis coefficient curve and the internal factor analysis coefficient curve are connected at each time according to the two types of systems, and they are marked as the external coefficient curve and the internal coefficient curve respectively.

[0020] As a preferred implementation of the present invention, the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period are obtained. If the external coefficient curve is an increasing trend and the floating trend of the internal coefficient curve is a decreasing trend, the image area constructed by the two current curves is set as a warning parameter, and the floating trend of the warning parameter is obtained. If the floating trend of the warning parameter is an increasing trend, the current analysis unit has no risk warning.

[0021] If the floating trend of the warning parameter is a downward trend, and the actual area value of the warning parameter decreases to the set upper limit of the area threshold, a reminder signal for the analysis unit is generated and the signal is sent to the authorized terminal of the analysis unit in the form of information. If there is no change in the trend of the corresponding warning parameter of the analysis unit, a warning signal is generated and sent to the authorized terminal of the analysis unit, and a flight rescheduling alternative analysis is performed on the analysis unit.

[0022] As a preferred implementation mode of the present invention, the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period are obtained. If the external coefficient curve is a downward trend and the floating trend of the internal coefficient curve is an increasing trend, the floating trend of the warning parameter is obtained. If the floating trend of the warning parameter is an increasing trend, the current analysis unit has no risk warning. On the contrary, if the floating trend of the warning parameter is an increasing trend, and the actual area value of the warning parameter increases toward the set area threshold lower limit, an analysis unit delay signal is generated and the signal is sent to the authorized terminal of the analysis unit in the form of information. If there is no change in the corresponding warning parameter trend of the analysis unit, a rescheduling signal is generated and sent to the authorized terminal of the analysis unit, and flight rescheduling options are selected for the analysis unit.

[0023] As a preferred implementation manner of the present invention, the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period are obtained. If the external coefficient curve is an increasing trend and the floating trend of the internal coefficient curve is an increasing trend, or the external coefficient curve is a decreasing trend and the floating trend of the internal coefficient curve is a decreasing trend, the external factors or the internal factors are re-analyzed for the analysis unit.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. In the present invention, an external factor analysis is performed on the analysis unit, and the analysis unit is inferred whether it needs to reschedule its flight ticket through the external factor analysis, so as to avoid the analysis unit being unable to timely monitor the external impact of the flight when approaching the flight time, and to provide itinerary warning to the analysis unit, thereby improving the timeliness of adjustment after itinerary planning deviations; at the same time, it is avoided that the analysis unit sets an inappropriate airport arrival time, thereby minimizing the difficulty of rescheduling;

[0026] Conduct an internal factor analysis on the analysis unit to infer whether the analysis unit can arrive within the specified time of the scheduled flight. Perform data analysis based on the real-time location of the analysis unit to monitor the real-time arrival risk, so as to facilitate timely flight ticket rescheduling when the analysis unit is unable to arrive, thereby reducing the impact of internal factors on the analysis unit.

[0027] 2. In the present invention, risk warnings are issued to analysis units that are not affected by external factors and internal factors, and predictions are made based on real-time risk warnings so that flights can be rescheduled reasonably; real-time data collection and analysis is performed on analysis units that need flight rescheduling, and flight rescheduling alternatives or choices are provided to the analysis units through data collection and analysis, so that appropriate routes can be matched in time when flights need to be rescheduled, thereby ensuring the rescheduling efficiency of the analysis units and reducing the impact of the rescheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0029] Figure 1 This is a principle block diagram of Embodiment 1 of the present invention;

[0030] Figure 2 This is a principle block diagram of the second embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] Embodiment 1

[0034] See also Figure 1 As shown, a flight ticket rescheduling recommendation system based on data analysis includes a flight ticket planning platform, wherein the flight ticket planning platform is communicatively connected to an external factor analysis unit, an internal factor analysis unit, a risk warning unit, and a real-time data collection unit;

[0035] In this embodiment, risk planning and assessment are performed on passengers to be departed on the corresponding flight according to flight information. The ticket planning platform sets all passengers on all current flights as analysis units. After the analysis unit completes online check-in for the aircraft, positioning analysis is performed on the analysis unit, and the current online check-in device is asked whether it can be used as a real-time positioning terminal for the analysis unit. Otherwise, positioning analysis is performed based on the authorized device of the analysis unit.

[0036] After determining the authorized device of the analysis unit, the ticket planning platform generates an external factor analysis signal and an internal factor analysis signal, and sends them to the external factor analysis unit and the internal factor analysis unit respectively;

[0037] After receiving the external factor analysis signal, the external factor analysis unit performs external factor analysis on the analysis unit. The external factors are external factors such as the operation of flight equipment and weather. Through the external factor analysis, it is inferred whether the current analysis unit needs to reschedule the flight ticket, so as to avoid the analysis unit being unable to timely monitor the external impact of the flight when approaching the flight time, resulting in the inability to adjust the itinerary planning deviation in time, and at the same time increasing the analysis unit to set an inappropriate airport arrival time, which in turn increases the difficulty of rescheduling;

[0038] The numerical ratio of the increase span of the equipment operation and maintenance time ratio during the standby period of the flight scheduled by the analysis unit to the speed of decrease of the remaining time of the current standby period excluding the operation and maintenance time is obtained, wherein the numerical ratio only compares the values ​​of the two parameters, and the dimensions are uniformly removed before comparison to exclude the unit influence; and the numerical ratio of the increase span of the equipment operation and maintenance time ratio during the standby period of the flight scheduled by the analysis unit to the speed of decrease of the remaining time of the current standby period excluding the operation and maintenance time is marked as SZB; the numerical deviation between the floating span predicted by the analysis unit for the weather parameters of the take-off area at the current time and the actual floating span is obtained, and the numerical deviation between the floating span predicted by the analysis unit for the weather parameters of the take-off area at the current time and the actual floating span is marked as SZP;

[0039] The speed of shortening the interval between the overlapping time of the flight trajectory of the flight set by the analysis unit and the actual external flight trajectory and the set flight passage time is obtained, and the speed of shortening the interval between the overlapping time of the flight trajectory of the flight set by the analysis unit and the actual external flight trajectory and the set flight passage time is marked as SDS; wherein the actual external flight trajectory is represented by a flock of birds, other flight trajectories, etc.;

[0040] The above collected data are uniformly marked as external factor information, and substituted into the formula to obtain the external factor analysis coefficient WF corresponding to the analysis unit. The formula is: Among them, fqa1, faq2 and faq3 are the corresponding numerical ratio of the increase span of the duration proportion and the speed of the remaining duration reduction, the numerical deviation of the floating span and the actual floating span, and the preset proportional coefficient of the interval duration reduction speed, respectively. e is a natural constant, and β is an error correction factor with a value of 1.80;

[0041] Compare the external factor analysis coefficient WF corresponding to the analysis unit with the external factor analysis coefficient threshold:

[0042] If the external factor analysis coefficient WF corresponding to the analysis unit exceeds the external factor analysis coefficient threshold, the current external factor analysis is judged to be abnormal, and an external high impact signal is generated and sent to the air ticket planning platform. After receiving the external high impact signal, the air ticket planning platform adjusts the flight scheduled by the analysis unit and sets the analysis unit as a planning unit when the risk cannot be completely avoided;

[0043] If the external factor analysis coefficient WF corresponding to the analysis unit does not exceed the external factor analysis coefficient threshold, it is determined that the current external factor analysis is normal, and an external low impact signal is generated and sent to the air ticket planning platform;

[0044] After receiving the internal factor analysis signal, the internal factor analysis unit performs internal factor analysis on the analysis unit, and infers whether the analysis unit can arrive within the specified time of the scheduled flight through the internal factor analysis. Data analysis is performed according to the real-time location of the analysis unit to monitor the real-time arrival risk, so as to facilitate timely ticket rescheduling when the unit cannot arrive, thereby reducing the impact of the internal factors on the analysis unit;

[0045] The shortest travel time of all transportation means corresponding to the distance between the current location of the analysis unit and the location of the scheduled flight airport is obtained, and the floating span of the real-time travel speed during the travel period starting from the current time corresponding to the distance is obtained, and the shortest travel time of all transportation means corresponding to the distance between the current location of the analysis unit and the location of the scheduled flight airport and the floating span of the real-time travel speed during the travel period starting from the current time corresponding to the distance are marked as TS and FV respectively; the non-overlapping duration between the shortest travel time and the flight departure time corresponding to the transportation scheme with the shortest travel time selected by the analysis unit is obtained, and the non-overlapping duration between the shortest travel time and the flight departure time corresponding to the transportation scheme with the shortest travel time selected by the analysis unit is marked as CS;

[0046] The above collected data are uniformly marked as internal factor information, and substituted into the formula to obtain the internal factor analysis coefficient NZ corresponding to the analysis unit. The formula is: Among them, hj1, hj2 and hj3 are the shortest travel time, the floating span of the real-time travel speed, and the preset proportional coefficient of the non-overlapping time, and α is the error correction factor, which is 0.79;

[0047] Compare the internal factor analysis coefficient NZ corresponding to the analysis unit with the internal factor analysis coefficient threshold:

[0048] If the internal factor analysis coefficient NZ corresponding to the analysis unit exceeds the internal factor analysis coefficient threshold, the internal factor analysis of the analysis unit is determined to be abnormal, an internal factor analysis abnormality signal is generated and the internal factor analysis abnormality signal is sent to the air ticket planning platform. After receiving the internal factor analysis abnormality signal, the air ticket planning platform performs air ticket planning for the current analysis unit and pre-selects an alternative;

[0049] If the internal factor analysis coefficient NZ corresponding to the analysis unit does not exceed the internal factor analysis coefficient threshold, the internal factor analysis of the analysis unit is determined to be normal, and a normal internal factor analysis signal is generated and sent to the air ticket planning platform;

[0050] After completing the analysis of external factors and internal factors, a risk warning signal is generated and sent to the risk warning unit. After receiving the risk warning signal, the risk warning unit issues a risk warning to the analysis units that have no impact on external factors and internal factors, and makes predictions based on real-time risk warnings, so that flights can be rescheduled reasonably;

[0051] The current system time and the flight departure time of the analysis unit are set as the risk warning period, and the external factor analysis coefficient and internal factor analysis coefficient of the analysis unit at each time are collected during the risk warning period. At the same time, the external factor analysis coefficient curve and the internal factor analysis coefficient curve are constructed by connecting each time according to the two types of systems, and they are marked as the external coefficient curve and the internal coefficient curve respectively;

[0052] The floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period are obtained. If the external coefficient curve is an increasing trend and the floating trend of the internal coefficient curve is a decreasing trend, the image area constructed by the two current curves is set as the warning parameter, and the floating trend of the warning parameter is obtained. If the floating trend of the warning parameter is an increasing trend, the current analysis unit has no risk warning; on the contrary, if the floating trend of the warning parameter is a decreasing trend, and the actual area value of the warning parameter decreases to the upper limit of the set area threshold, an analysis unit reminder signal is generated and sent to the authorized terminal of the analysis unit in the form of information, and if there is no change in the corresponding warning parameter trend of the analysis unit, a warning signal is generated and sent to the authorized terminal of the analysis unit, and at the same time, a flight rescheduling alternative analysis is performed on the analysis unit;

[0053] The floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period are obtained. If the external coefficient curve is a downward trend and the floating trend of the internal coefficient curve is an increasing trend, the floating trend of the warning parameter is obtained. If the floating trend of the warning parameter is an increasing trend, the current analysis unit has no risk warning. On the contrary, if the floating trend of the warning parameter is an increasing trend, and the actual area value of the warning parameter increases toward the lower limit of the set area threshold, a delay signal of the analysis unit is generated and sent to the authorized terminal of the analysis unit in the form of information. If there is no change in the trend of the corresponding warning parameter of the analysis unit, a rescheduling signal is generated and sent to the authorized terminal of the analysis unit, and at the same time, the flight rescheduling alternatives for the analysis unit are selected;

[0054] Obtain the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period. If the external coefficient curve is an increasing trend and the floating trend of the internal coefficient curve is an increasing trend, or the external coefficient curve is a decreasing trend and the floating trend of the internal coefficient curve is a decreasing trend, then re-analyze the external factors or re-analyze the internal factors for the analysis unit;

[0055] Embodiment 2

[0056] The previous embodiment monitors the risk of flight rescheduling. This embodiment analyzes and monitors the flight rescheduling plan based on the previous embodiment. Please refer to Figure 2 As shown, the air ticket planning platform generates a real-time data collection signal and sends the real-time data collection signal to the real-time data collection unit. After receiving the real-time data collection signal, the real-time data collection unit performs real-time data collection and analysis on the analysis unit that needs to reschedule the flight. Through data collection and analysis, the analysis unit is provided with flight rescheduling alternatives or options, so that when the flight needs to be rescheduled, the appropriate route can be matched in time, the rescheduling efficiency of the analysis unit is guaranteed, and the impact of the rescheduling is reduced;

[0057] The flight of the current analysis unit is set as a rescheduled flight, and flights that are consistent with the destination of the rescheduled flight or flights that can transfer to the destination of the rescheduled flight are collected and uniformly marked as pending rescheduled flights, and the deviation between the estimated travel time of the pending rescheduled flight and the original estimated time of the rescheduled flight is obtained. At the same time, the span deviation between the real-time remaining ticket booking speed of the pending rescheduled flight warning and the corresponding numerical growth ratio of the shortest rescheduled flight handling time of the current rescheduled flight of the analysis unit is obtained, and the deviation between the estimated travel time of the pending rescheduled flight and the original estimated time of the rescheduled flight, and the span deviation between the real-time remaining ticket booking speed of the pending rescheduled flight warning and the corresponding numerical growth ratio of the shortest rescheduled flight handling time of the current rescheduled flight of the analysis unit are marked as time consumption data and rescheduling data, respectively, and compared with the time consumption deviation threshold and span deviation threshold range respectively:

[0058] If the deviation between the estimated travel time of the waiting flight and the original estimated travel time of the rescheduled flight exceeds the time deviation threshold, or the span deviation between the real-time remaining ticket booking speed of the waiting flight warning and the corresponding numerical growth ratio of the shortest rescheduling time of the current rescheduled flight of the analysis unit is not within the span deviation threshold range, the current waiting flight will be set as an excluded flight;

[0059] If the deviation between the estimated travel time of the waiting flight and the original estimated travel time of the rescheduled flight does not exceed the time deviation threshold, and the span deviation between the real-time remaining ticket booking speed of the waiting flight warning and the corresponding numerical growth ratio of the shortest rescheduling time of the current rescheduled flight of the analysis unit is within the span deviation threshold range, the current waiting flight is set as the flight to be selected;

[0060] The selected flights are sent to the air ticket planning platform, which receives them and sends them to the authorized terminal of the analysis unit. If the number of analysis units that need to reschedule the current flights exceeds the rescheduling threshold, the analysis unit will control the number of people who choose the corresponding flights to be selected when the number of people increases, that is, the current flights to be rescheduled will be excluded when the number of people is full.

[0061] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0062] When the present invention is in use, the external factor analysis unit performs external factor analysis on the analysis unit, obtains the external factor information of each analysis unit, substitutes the information into the formula to obtain the external factor analysis coefficient corresponding to the analysis unit, and infers whether the external factor analysis is normal based on the comparison of the external factor analysis coefficients; the internal factor analysis unit performs internal factor analysis on the analysis unit, obtains the internal factor information of each analysis unit, substitutes the information into the formula to obtain the internal factor analysis coefficient corresponding to the analysis unit, and infers whether the internal factor analysis is normal based on the comparison of the internal factor analysis coefficients; after completing the external factor analysis and the internal factor analysis, and if both are normal, the risk warning unit issues a risk warning to the analysis unit that is not affected by the external factors and the internal factors.

[0063] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A flight ticket rescheduling recommendation system based on data analysis, characterized in that: Including the air ticket planning platform, the air ticket planning platform communication links are: The external factor analysis unit performs external factor analysis on the analysis unit, obtains the external factor information of each analysis unit, substitutes it into the formula to obtain the external factor analysis coefficient corresponding to the analysis unit, and infers whether the external factor analysis is normal based on the comparison of the external factor analysis coefficient; The internal factor analysis unit performs internal factor analysis on the analysis unit, obtains the internal factor information of each analysis unit, substitutes it into the formula to obtain the internal factor analysis coefficient corresponding to the analysis unit, and infers whether the internal factor analysis is normal based on the comparison of the internal factor analysis coefficient; After completing the external factor analysis and the internal factor analysis, and when they are all normal, the risk warning unit will issue a risk warning to the analysis units that are not affected by the external and internal factors.

2. The air ticket rescheduling recommendation system based on data analysis according to claim 1, characterized in that: The external factor analysis information includes the corresponding numerical ratio of the increase in the proportion of the equipment operation and maintenance time during the waiting period of the flight scheduled by the analysis unit and the decrease in the remaining time of the current waiting period excluding the operation and maintenance time, the numerical deviation between the floating span of the weather parameters predicted for the take-off area at the current time of the flight scheduled by the analysis unit and the actual floating span, and the shortening speed of the interval between the overlapping time of the flight trajectory of the flight scheduled by the analysis unit and the actual external flight trajectory and the set flight passage time.

3. The air ticket rescheduling recommendation system based on data analysis according to claim 2, characterized in that: If the external factor analysis coefficient corresponding to the analysis unit exceeds the external factor analysis coefficient threshold, the current external factor analysis is judged to be abnormal; if the external factor analysis coefficient corresponding to the analysis unit does not exceed the external factor analysis coefficient threshold, the current external factor analysis is judged to be normal.

4. The air ticket rescheduling recommendation system based on data analysis according to claim 1, characterized in that: The internal factor information includes the shortest travel time of all transportation tools corresponding to the distance between the current location of the analysis unit and the airport location of the scheduled flight, the floating span of the real-time travel speed during the travel period starting from the current time corresponding to the distance, and the non-overlapping time between the shortest travel time and the flight departure time corresponding to the shortest travel time transportation plan selected by the analysis unit.

5. The air ticket rescheduling recommendation system based on data analysis according to claim 4, characterized in that: If the intrinsic factor analysis coefficient corresponding to the analysis unit exceeds the intrinsic factor analysis coefficient threshold, the intrinsic factor analysis of the analysis unit is judged to be abnormal; if the intrinsic factor analysis coefficient corresponding to the analysis unit does not exceed the intrinsic factor analysis coefficient threshold, the intrinsic factor analysis of the analysis unit is judged to be normal.

6. The air ticket rescheduling recommendation system based on data analysis according to claim 1, characterized in that: The operation process of the risk warning unit is as follows: The current system time and the flight departure time of the analysis unit are set as the risk warning period, and the external factor analysis coefficient and the internal factor analysis coefficient of the analysis unit at each time are collected during the risk warning period. At the same time, the external factor analysis coefficient curve and the internal factor analysis coefficient curve are connected at each time according to the two types of systems, and they are marked as the external coefficient curve and the internal coefficient curve respectively.

7. The air ticket rescheduling recommendation system based on data analysis according to claim 6, characterized in that: Obtain the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period. If the external coefficient curve is an increasing trend and the floating trend of the internal coefficient curve is a decreasing trend, then the image area constructed by the two current curves is set as the warning parameter, and obtain the floating trend of the warning parameter. If the floating trend of the warning parameter is an increasing trend, then the current analysis unit has no risk warning. If the floating trend of the warning parameter is a downward trend, and the actual area value of the warning parameter decreases to the set upper limit of the area threshold, a reminder signal for the analysis unit is generated and the signal is sent to the authorized terminal of the analysis unit in the form of information. If there is no change in the trend of the corresponding warning parameter of the analysis unit, a warning signal is generated and sent to the authorized terminal of the analysis unit, and a flight rescheduling alternative analysis is performed on the analysis unit.

8. The air ticket rescheduling recommendation system based on data analysis according to claim 7, characterized in that: Obtain the floating trends of the external coefficient curve and the internal coefficient curve within the risk warning period. If the external coefficient curve is a downward trend and the floating trend of the internal coefficient curve is an increasing trend, then obtain the floating trend of the warning parameter. If the floating trend of the warning parameter is an increasing trend, then the current analysis unit has no risk warning. On the contrary, if the floating trend of the warning parameter is an increasing trend, and the actual area value of the warning parameter increases towards the lower limit of the set area threshold, a delay signal of the analysis unit is generated and the signal is sent to the authorized terminal of the analysis unit in the form of information. If there is no change in the trend of the corresponding warning parameter of the analysis unit, a rescheduling signal is generated and sent to the authorized terminal of the analysis unit, and flight rescheduling options are selected for the analysis unit.

9. The air ticket rescheduling recommendation system based on data analysis according to claim 8, characterized in that: Obtain the floating trends of the external coefficient curve and the internal coefficient curve during the risk warning period. If the external coefficient curve shows an increasing trend and the floating trend of the internal coefficient curve is an increasing trend, or the external coefficient curve shows a decreasing trend and the floating trend of the internal coefficient curve is a decreasing trend, then re-analyze the external factors or the internal factors for the analysis unit.

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