CN119783892A

CN119783892A - Method, system, device and storage medium for predicting the achievable market demand value of a flight

Info

Publication number: CN119783892A
Application number: CN202411907979.0A
Authority: CN
Inventors: 张毅; 赵耀帅; 张立功; 陈思; 梁巍; 杨璐萌; 宋歌
Original assignee: China Travelsky Technology Co Ltd
Current assignee: China Travelsky Technology Co Ltd
Priority date: 2024-12-23
Filing date: 2024-12-23
Publication date: 2025-04-08
Anticipated expiration: 2044-12-23
Also published as: CN119783892B

Abstract

The present invention belongs to the field of aviation revenue management technology, and provides a method, system, device and storage medium for predicting the achievable market demand value of a flight, the method comprising: obtaining all flight information of a specified flight segment of a specified airline; based on the flight information, obtaining the inventory data and historical market demand value of a future flight Dcp; based on the inventory data, predicting the market demand value of the segment cabin of the latest Dcp of a future flight; based on the historical market demand value, establishing a historical flight data pool with granularity to the cabin level for a future flight; based on the historical flight data pool, drawing a flight booking curve for the segment cabin of a future flight; predicting the achievable demand value of all cabins of a future flight. The present invention utilizes the revenue management system to reflect market constraints by calculating the achievable demand value of the segment (cabin) at the time of departure, thereby improving the function of the revenue management system, the performance of the revenue management system and the efficiency of the revenue management work of the airline.

Description

Method, system, device and storage medium for predicting available market demand value of flight

Technical Field

The invention belongs to the technical field of aviation income management, and particularly relates to a method, a system, equipment and a storage medium for predicting that flights can reach market demand values.

Background

The profit management is that the airlines manage the price and the seats by using scientific means such as prediction, optimization and the like, so that each seat of each leg of each flight is sold to different types of passengers at proper time according to different prices, thereby obtaining the maximum profit.

The revenue management system (basic edition) is a system for automatically managing inventory of non-departure flights based on a prediction and optimization model by using flight schedule, inventory, departure and freight rate data. In the revenue management system, a certain unopened forecast target flight is determined to be that the actual booking number of a certain section (space) of a certain future flight in the latest Dcp is smaller than the historical average booking number of the Dcp, or the market demand of the certain section (space) of the certain future flight in the latest Dcp is influenced by certain limiting factors (airplane seat number, protection number and the like).

The purpose of the technology and method of the revenue management system (foundation edition) is to determine the reachable demand value when each leg (bilge) of a Future flight Future device leaves. The up-to-market demand plays an important role in the revenue management business and the revenue management system, and is not only the main output of the prediction module in the revenue management system, but also the main input of the optimization module. The manual mass calculation is not practical at all, and the system is on the ground and is not supported by the prediction theory and technology, so that the problems of the work and the construction of the yield management system exist for a long time.

How to solve the problems and difficulties and meet the market demand value prediction of each granularity from the flight leg to the cabin level is a domestic blank that the systematic operation of the market demand value prediction business is not filled.

Disclosure of Invention

In order to solve the problems, the invention provides a method, a system, equipment and a storage medium for predicting that a flight can reach a market demand value.

A method of predicting a flight's reachable market demand according to the present invention, the method comprising:

S1, acquiring all flight information of a designated flight section of a designated airline company, and acquiring inventory data and historical market demand values of a future flight Dcp based on the flight information;

s2, predicting market demand values of space segments of the latest Dcp of a future flight based on the inventory data;

S3, establishing a historical flight data pool with granularity reaching a cabin level for the future flights based on the historical market demand value;

s4, drawing a flight reservation curve for the space leg position of the future flight based on the historical flight data pool;

S5, predicting the reachable demand values of all the bilges of the future flights.

Further, the acquiring all the flight information of the designated flight leg of the designated airline company specifically includes:

and acquiring the total information and the incremental information of the designated flight section of the designated airline company, and sorting and warehousing, wherein the incremental information is the latest flight data in the night time of 02 to 04 points per night.

Further, the acquiring inventory data of a future flight Dcp based on the flight information specifically includes:

Acquiring flight stock data of an outgoing flight of the designated airline designated flight section, wherein the historical 3 years of the flight stock data is based on the current date or the system date of the revenue management system, and the flight stock data is used as the outgoing flight stock data;

The method comprises the steps of acquiring a specified flight section of a specified airline company, and taking the future one-year flight stock data based on the current date or the system date of a revenue management system as unoccupied flight stock data.

Further, the flight information further includes astm d aviation standard data provided by the I CS flight control system, and the astm d aviation standard data specifically includes:

flight time data SCH, namely an airline company, a flight number, an origin, a destination, a flight departure date and time, and a flight arrival date and time;

The flight booking data INV comprises an electronic ticket mark, a cabin structure table, a flight physical layout number and a flight maximum marketable seat number;

Flight operation data FLT, the actual departure time of the flight.

Further, the drawing a flight reservation curve for the leg positions of the future flights based on the historical flight data pool specifically includes:

the flight reservation curves comprise an outgoing historical flight reservation curve, an unhooked flight reservation curve and a future flight prediction reservation curve;

the flight reservation curve is composed of the reservation number of each Dcp, wherein the reservation number of each Dcp is the average value of all corresponding Dcp reservation numbers in the historical flight data pool;

If there are N records in the historical flight data pool of Class _i, then the seat count for the j-th Dcp point on the flight seat curve of Class _i is:

Wherein Class _i_DCP_j _H is the seat number of the jth Dcp in the flight seat curve of Class _i, and Class _i_BKD_m is the seat number of Class _i recorded on the mth record in the historical flight data pool of Class _i.

Further, the predicting the reachable demand values of all the bilges of a future flight specifically includes:

S5-1, comparing the booking number BKD of the space Class _i of the latest Dcp of a future flight with the booking number BKD of the corresponding Dcp on the flight booking curve;

if the booking number BKD of the space leg position Classi of the latest Dcp of a future flight is smaller than the booking number BKD of the corresponding Dcp on the flight booking curve, the step S5-4 is entered, otherwise, the step S5-6 is entered;

S5-2, judging whether the voyage hold Class _i of the latest Dcp of a future flight is in a lock hold Posted state;

If the voyage hold Class _i of the latest Dcp of a future flight is not in the lock hold Posted state, entering step S5-5, otherwise entering step S5-6;

s5-3, calculating an reachable demand value Achievable Demand of a voyage hold Class _i of a latest Dcp of a future flight;

If the booking value BKD of the space leg position of the latest Dcp of a future flight is larger than the historical average booking number and is not locked, taking the predicted market Demand value of the space leg position of the flight at the Dcp ₂₃ point as an reachable Demand value, namely Achievable Demand =demand;

S5-4, calculating a Difference between the booking number BKD of the space Class _i of the latest Dcp of a future flight and the booking number corresponding to the Dcp on the flight booking curve, wherein the calculation formula is as follows:

Difference=i_DCP_A_Future-i_DCP_A_History

S5-5, calculating an reachable demand value Achievable Demand of a future flight leg Class _i in a DCP ₂₃ according to a booking number i_Dcp ₂₃ _History corresponding to a flight booking curve, wherein the calculation formula is as follows:

Achievable Demand=i_DCP₂₃_History+Difference

The i_DCP ₂₃ _history is the booking number of the corresponding DCP ₂₃ on the flight booking curve;

S5-6, judging whether the reachable demand values AchievableDemand of all the classes _i of the voyage section of a future flight are all calculated;

S5-7, outputting a reachable demand value Achievable Demand.

Further, the method for determining whether the cabin level is in the lock cabin Posted state is as follows:

In the Chinese avigation ICS system, the main judgment basis is as follows:

the maximum available value LSS of the inventory data of the flight booking INV of the cabin is a positive integer, and the cabin sales state IND is marked as EK\EAK\ELK\ EALK, the cabin of the flight section is not locked Posted, and the cabin is in a saleable state;

the maximum available value LSS of the stock data of the flight booking INV of the flight space is smaller than or equal to 0, or the sales state IND of the flight space is marked as EPK\ EALP \ EAPK \ EALPK, the space of the flight space is locked Posted, and the space of the flight space is stopped for sales;

in the overseas ICS system, the main judgment basis is:

If the BKD seat number of the flight leg's seat reaches the AU maximum available value of the seat Class _i, the flight leg's seat is locked Posted and the flight leg's seat is stopped from being sold, otherwise the flight leg's seat is not locked Posted and the seat is in a marketable state.

The present invention also provides a system for predicting a flight's reachable market demand value, the system comprising:

The system comprises an acquisition module, a history market demand value and a storage module, wherein the acquisition module is used for acquiring all flight information of a designated flight section of a designated airline company;

a predicted market demand module for predicting a market demand for a leg position of a latest Dcp of a future flight based on the inventory data;

a historical flight data pool module is constructed and used for establishing a historical flight data pool with granularity reaching a cabin level for the future flights based on the historical market demand value;

the drawing flight reservation curve module is used for drawing a flight reservation curve for the space leg position of the future flight based on the historical flight data pool;

And the predicted reachable demand value module is used for predicting reachable demand values of all the billboards of the future flights.

The invention also provides a device comprising a processor coupled to a memory, the processor for reading and executing the computer program stored in the memory to implement the aforementioned method of predicting a flight's up to market demand.

The present invention also provides a computer readable storage medium storing a program or instructions that when run on a computer cause the computer to perform a method of predicting a flight's up to market demand as described above.

Compared with the prior art, the invention has the following advantages:

The invention utilizes the revenue management system to embody market limiting factors by calculating the reachable demand value of the voyage (bilge) when leaving the port, improves the function of the revenue management system and improves the performance of the revenue management system and the revenue management work efficiency of the airlines.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method of predicting a flight's reachable market demand according to the present invention;

FIG. 2 is a schematic diagram of a system for predicting a flight's reachable market demand according to the present invention;

FIG. 3 is a schematic diagram of an electronic device according to the present invention;

FIG. 4 is a business flow diagram of a predictive specified airline specified flight segment (hold) market demand value for an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The following are some specialized terms that illustrate the present invention:

And a revenue management system (basic edition) for automatically managing the inventory of the unopened flights based on the prediction and optimization model by using the flight schedule, inventory, departure and freight rate data.

Inventory refers to a list of information on the Availability of seats on the flight, seat reservation values (Seat solution), available Seat numbers (Seat Open), and various control parameters (Inventory Parameter) that affect the sales decisions of the seats on the flight.

ICS (Inventory Control System) an airline booking system, also referred to herein as an inventory control system.

The data acquisition points Dcp (Data Collection Points) are set by an airline company according to the consideration factors such as the quality of the own route and the flight attribute, the data acquisition codes determined by the distance departure days are in one-to-one correspondence with the distance departure days, and the value of Dcp is larger when the airline company sets 24 Dcp to the closer the flight departure days. For example, the data acquisition point Dcp is referred to as the departure Dcp and corresponds to a distance of 0 days from the departure day.

Fixed data acquisition Point Fixed-DCP the data acquisition Point set by the airline is determined by the number of days of departure, and the airline can set two sets of data acquisition points in total of domestic flight route and international flight route in the flight control system (or revenue management system).

The Floating data acquisition point is a Floating data acquisition point, for example, the designated flight distance is 20 days from the harbor date, but Dcp ₁₁ is 24 days from the harbor date, and Dcp ₁₂ is 18 days from the harbor date, and can be recorded as Dcp _11.5.

The Final data acquisition point Final-DCP is the data acquisition point on the same day of departure of the flight, and can also be called as departure Dcp;

the latest data acquisition point Last actual-DCP is the data acquisition point of the latest acquired data of the non-departure flight, and the return management prediction and optimization module applies the data with the aviation section level stock acquired based on Last actual-DCP as the independent variable.

The booking number BKD is the space or weight of the seats, sleeping space, luggage or goods reserved by the passengers and allocated to the passengers in advance;

The passenger pays the ticket price of the service and the seat provided for the passenger;

The reachable demand value Achievable Demand is understood to be the achievable demand, the number of passengers that can purchase for a flight product consisting of such a price or service during a reservation period and under the preconditions of a certain price and service.

Lock the cabin Posted, state or action of stopping sales of the voyage section (cabin level);

the number of seats is Authorized Booking Level, which is recorded as AU, of foreign ICS logic;

LSS (domestic ICS logic), number of seats that the bunk level allows to sell;

Market Demand-passengers have a willing and purchasable amount for a flight product consisting of such price or service in a reservation period and under the preconditions of a certain price and service.

Booking value Bkg the passenger subscribes to and pre-allocates to the passenger's seat, sleeping space, space for luggage or cargo, or weight.

In one embodiment of the present invention, a method of predicting a flight's reachable market demand is provided, as shown in FIGS. 1 and 4, comprising:

s1, acquiring all flight information of a designated flight section of a designated airline company according to two-word codes of the airline company, and acquiring inventory data and historical market demand values of a future flight Dcp based on the flight information;

The acquiring all flight information of the designated flight leg of the designated airline company specifically includes:

and acquiring full-quantity information and incremental information of the designated flight section of the designated airline company, and sorting and warehousing, wherein the incremental information is the latest flight data in night time from 02 to 04 points per night.

Based on the flight information, the method for acquiring inventory data of a future flight Dcp specifically includes:

The flight information also comprises ASTD aviation standard data provided by an I CS flight control system, and specifically comprises the following steps:

The flight booking data INV is an electronic ticket mark, a cabin structure table, a flight physical layout number and a flight maximum marketable seat number;

Flight operation data FLT, the actual departure time of the flight.

And S3, establishing a historical flight data pool with granularity reaching a cabin level for the future flights based on the market demand value.

the flight reservation curves comprise an outgoing historical flight reservation curve, an unhooked flight reservation curve and a future prediction reservation curve;

the flight reservation curve is composed of each Dcp reservation number, and the reservation number of each Dcp is the average value of all corresponding Dcp reservation numbers in the historical flight data pool;

S5, predicting the reachable demand value AchievableDemand of all the classes _i of the future flights, which specifically comprises the following steps:

if the booking number BKD of the space leg Class _i of the latest Dcp of a future flight is smaller than the booking number BKD of the corresponding Dcp on the flight booking curve, the step S5-4 is entered, otherwise, the step S5-6 is entered;

For example, for a Future flight, the currently processed flight gap Class is the highest gap Y-Class of economy, the latest Dcp is Dcp ₁₀, the seat count BKD of Y-Class on Dcp ₁₀ is 40, i.e. Y_Dcp ₁₀ _future=40, and the seat count BKD of Dcp ₁₀ on the flight seat curve is 50, i.e. Y_Dcp ₁₀ _history=50, and thus step S5-4 is entered.

the method for judging whether the cabin Posted is locked or not by the cabin position comprises the following steps:

In the Chinese avigation ICS system, the main judgment basis is as follows:

the maximum available value LSS of the stock data of the flight booking INV of the flight leg is smaller than or equal to 0, or the sales state IND of the flight leg is marked as EPK\ EALP \ EAPK \ EALPK, the flight leg is locked Posted, and the flight leg is stopped from being sold.

In the overseas ICS system, the main judgment basis is:

When the BKD booking number of the space of the flight leg reaches the AU (Available Units) maximum Available value of the space Class _i, the space of the flight leg is locked Posted, and the space of the flight leg is stopped from being sold, otherwise, the space of the flight leg is not locked Posted, and the space is in a saleable state;

For example, for a Future flight, the currently processed flight level Class is the highest economy level Y-bin, the latest Dcp is Dcp ₁₀, the number of seats BKD of Y-bin at Dcp ₁₀ is 40, i.e. Y_Dcp ₁₀ _future=40, and the maximum available value LSS=45 of Y-bin at this time, i.e. Y-bin is not locked, and thus step S5-5 is entered.

If the booking value BKD of the space leg position of the latest Dcp of a future flight is larger than the historical average booking number and is not locked, taking the predicted market Demand value of the space leg position of the flight at the point DcP ₂₃ as an reachable Demand value, namely Achievable Demand =demand;

For example, for a future flight, the currently processed flight berth Class is the highest berth Y cabin of the economy Class, the latest Dcp is Dcp ₁₀, the booking number BKD of the Y cabin on Dcp ₁₀ is 40, and the booking number BKD of Dcp ₁₀ on the flight booking curve is 38, namely Y_Dcp ₁₀_Future>Y_Dcp₁₀ _History;

the maximum available value LSS of the Y cabin is 45, and the Y cabin is in an unlocked state;

the market Demand value Demand of Dcp ₂₃ of the Y cabin obtained by prediction is 80 when the Y cabin leaves a port;

thus, the achievable Demand Achievable Demand for the Y-bay is equal to the market Demand for Dcp ₂₃ at departure, which is 80.

Difference=i_DCP_A_Future-i_DCP_A_History

For example, if a future flight has a Class of the highest Class of economy Class, Y Class, the latest Dcp is Dcp ₁₀, Y Class has a booking number BKD of Dcp ₁₀ of 40, and the booking number BKD of Dcp ₁₀ on the flight booking curve is 50

Difference=YDcp₁₀Future-YDcp₁₀History=-10。

Achievable Demand=i_DCP₂₃_History+Difference

For example, for a future flight, the currently processed flight berth Class is the highest berth Y cabin of the economy Class, the market Demand of Dcp ₂₃ on the booking curve is 80, the difference is calculated by the step S5-4 to be-10, and the berth Y cabin is AchievableDemand =80+ (-10) =70 at the point of Dcp ₂₃ in departure.

S5-7, outputting a reachable demand value Achievable Demand.

Embodiments of the present invention also provide a system for predicting a flight's reachable market demand value, as shown in FIG. 2, comprising:

an acquisition module 201, configured to acquire all flight information of a specified flight leg of a specified airline company;

a forecasted market demand module 202 for forecasting market demand for the leg positions of a latest Dcp for a future flight based on the inventory data;

a historical flight data pool building module 203, configured to build a historical flight data pool with granularity reaching a cabin level for the future flights based on the historical market demand value;

A drawing flight booking curve module 204, configured to draw a flight booking curve for the leg positions of the future flight based on the historical flight data pool;

the predicted reachable demand value module 205 is configured to predict reachable demand values of all billboards of the future flight.

As shown in FIG. 3, an embodiment of the present invention also provides an apparatus comprising a processor 301, the processor 301 being coupled to a memory 302, the processor 301 being configured to read and execute a computer program stored in the memory 302 to implement a method of predicting a flight reachable market demand value as described in the method embodiment above.

Embodiments of the present invention also provide a computer-readable storage medium storing a program or instructions that, when executed on a computer, cause the computer to perform a method of predicting a flight-up to market demand as described in the method embodiments above.

It will be apparent to those skilled in the art that the modules or steps of the embodiments of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a storage device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than what is shown or described, or they may be separately fabricated into individual integrated circuit modules, or a plurality of modules or steps in them may be fabricated into a single integrated circuit module. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.

The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and various modifications and variations can be made to the embodiments of the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the market demand value that a flight can reach, characterized in that the method comprises:

S1. Obtain all flight information of a specified flight segment of a specified airline; based on the flight information, obtain inventory data and historical market demand value of a future flight Dcp;

S2. Based on the inventory data, predict the market demand value of the latest Dcp of a future flight segment space;

S3. Based on the historical market demand value, establish a historical flight data pool with granularity down to cabin level for the future flight;

S4. Drawing a flight booking curve for the flight segment space of the future flight based on the historical flight data pool;

S5. Predicting the achievable demand values of all seats of the future flight.

2. The method according to claim 1, characterized in that

The acquisition of all flight information of a specified flight segment of a specified airline specifically includes:

Obtain the full information and incremental information of the specified flight segment of the specified airline, and organize and store them in the database; the incremental information is the latest flight data during the night maintenance time from 02:00 to 04:00 every night.

3. The method according to claim 1, characterized in that

The obtaining of inventory data of a future flight Dcp based on the flight information specifically includes:

Obtain the flight inventory data of the specified flight segment of the specified airline, and the flight inventory data of the departed flights in the past three years based on the current date or the system date of the revenue management system as the departed flight inventory data;

Get the flight inventory data of the specified flight segment of the specified airline, based on the current date or the system date of the revenue management system for the next year, as the flight inventory data that has not departed.

4. The method according to claim 1, characterized in that:

The flight information also includes ASTD aviation standard data provided by the ICS flight control system. The ASTD aviation standard data specifically includes:

Flight schedule data SCH: airline, flight number, origin, destination, flight departure date and time, flight arrival date and time;

Flight booking data INV: electronic ticket identification, cabin structure table, flight physical layout number, and maximum number of seats available for sale on the flight;

Flight operation data FLT: actual departure time of the flight.

5. The method according to claim 1, characterized in that

Drawing a flight booking curve for the flight segment space of the future flight based on the historical flight data pool specifically includes:

The flight booking curve includes the booking curve of historical flights that have departed, the booking curve of flights that have not departed, and the predicted booking curve of future flights;

The flight booking curve is composed of the number of bookings for each Dcp, and the number of bookings for each Dcp is the average of the number of bookings for all corresponding Dcps in the historical flight data pool;

If there are N records in the historical flight data pool of Class _i , the number of reservations for the jth Dcp point on the flight reservation curve of Class _i is:

Among them, Class _i _DCP _j _H is the number of bookings for the jth DCP in the flight booking curve of Class _i , and Class _i _BKD _m is the number of bookings for Class _{i in the mth record in the historical flight data pool of Class i} _.

6. The method according to claim 1, characterized in that

The predicted achievable demand value of all seats of a future flight specifically includes:

S5-1. Compare the number of bookings BKD of the flight class _i of the latest Dcp of a future flight with the number of bookings BKD of the corresponding Dcp on the flight booking curve;

If the number of bookings BKD of the class _i of the latest Dcp of a future flight is less than the number of bookings BKD of the corresponding Dcp on the flight booking curve, then go to step S5-4, otherwise go to step S5-6;

S5-2, determine whether the flight segment cabin Class _i of the latest Dcp of a future flight is in the locked cabin Posted state;

If the class _i of the latest Dcp of a future flight is not in the locked state, then go to step S5-5, otherwise go to step S5-6;

S5-3, calculate the Achievable Demand of the class _i of the latest Dcp of a future flight;

If the booking value BKD of the latest Dcp of a future flight is greater than the historical average booking number and is not locked, the predicted market demand value of the flight segment at Dcp ₂₃ points is used as the achievable demand value, that is, AchievableDemand = Demand;

S5-4. Calculate the difference between the number of bookings BKD for the class _i of the latest Dcp of a future flight and the number of bookings for the corresponding Dcp on the flight booking curve. The calculation formula is:

Difference=i_DCP _A _Future-i_DCP _A _History

S5-5. According to the number of bookings i_Dcp ₂₃ _History corresponding to the flight booking curve, the Achievable Demand of a future flight segment Class _i in DCP ₂₃ is calculated. The calculation formula is:

Achievable Demand=i_DCP ₂₃ _History+Difference

Among them, i_DCP ₂₃ _History is the number of bookings corresponding to DCP ₂₃ on the flight booking curve;

S5-6, determining whether all the achievable demand values of Class _i of a future flight segment are fully calculated;

S5-7. Output the achievable demand value Achievable Demand.

7. The method according to claim 6, characterized in that

The method to determine whether the space is in the locked and posted state is:

In the ICS system of China Aviation Information Network, the main judgment basis is:

If the maximum available value LSS of the flight booking INV inventory data of the space is a positive integer, and the space sales status IND is marked as EK\EAK\ELK\EALK, the space of the flight segment is not locked and posted, and the space is in a saleable state;

If the maximum available value LSS of the flight booking INV inventory data of the space is less than or equal to 0, or the space sales status IND is marked as EPK\EALP\EAPK\EALPK, the space of the flight segment is locked and posted, and the space of the flight segment is stopped from being sold;

In overseas ICS systems, the main basis for judgment is:

If the number of BKD bookings for a class of a flight segment reaches the maximum available AU value of that class Class _i , the class of that flight segment is posted and the sale of the class of that flight segment is stopped; otherwise, the class of that flight segment is not posted and is available for sale.

8. A system for predicting the market demand value of a flight, characterized in that the system comprises:

An acquisition module is used to acquire all flight information of a specified flight segment of a specified airline; based on the flight information, acquire inventory data and historical market demand value of a future flight Dcp;

A module for predicting market demand value, used to predict the market demand value of the flight segment space of the latest Dcp of a future flight based on the inventory data;

Constructing a historical flight data pool module, for establishing a historical flight data pool with a granularity down to the cabin level for the future flight based on the historical market demand value;

A flight booking curve drawing module is used to draw a flight booking curve for the flight segment space of the future flight based on the historical flight data pool;

The module for predicting the achievable demand value is used to predict the achievable demand value of all seats of the future flight.

9. A device, characterized in that:

comprising a processor coupled to a memory;

The processor is used to read and execute the computer program stored in the memory to implement a method for predicting the market demand value of a flight as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that:

A program or instruction is stored, and when the program or instruction is executed on a computer, the computer is caused to execute a method for predicting the market demand value of a flight as described in any one of claims 1-7.