Delay propagation recovery simulation method based on regional perception and route perception coefficients

Abstract

The invention relates to the field of aviation networks, and provides a delay propagation recovery simulation method based on regional perception and route perception coefficients, which comprises the following steps of: constructing a multi-time window delay propagation route network with delay propagation characteristics; establishing a delay propagation model according to the multi-time window delay propagation route network; obtaining change characteristics of the delay propagation rate in time and degree according to a delay propagation model; obtaining a delay propagation balance point model according to the change characteristics of the delay propagation rate in time and degree, and obtaining a delay propagation rate threshold through the delay propagation balance point model; obtaining the relation between the effective connection consciousness and the delay propagation rate and the relation between the reverse pre-judgment recovery consciousness and the delay propagation rate through the delay propagation rate threshold value; and using matlab to verify the influence of reverse pre-judgment recovery consciousness and effective connection consciousness on the delay propagation threshold. According to the method, a region sensing coefficient and a route sensing coefficient are introduced into a traditional propagation simulation model so as to reduce delay simulation errors.

Description

Technical Field

[0001] The present invention relates to the field of aviation delay network technology, and in particular to a delay propagation recovery simulation method based on area perception and route perception coefficients. Background Art

[0002] In aviation network delays, due to the large number of airports and complex route relationships, it is impossible to understand the diffusion characteristics of delays only from the information at the level of a single airport. It is necessary to construct a new aviation delay network (ADN) with delay characteristics to evolve the global structure and dynamic characteristics of delays and reveal the direction and scope of delay propagation at the network level. At present, in the analysis of complex delay networks, most available delay network models lack the idea of ​​dividing the delay network sublayer from the perspective of dynamic time sliding of aircraft, resulting in the topological analysis of the delay network still remaining at the static structural division; at the same time, the existing aviation delay network lacks causal transmission analysis between routes, so that the constructed delay network does not test the propagability of delays between routes, resulting in the inaccuracy of the topological analysis of the delay network, and the increase of network calculation amount and difficulty.

[0003] The delay propagation model is a core simulation tool for exploring the source of delay propagation and verifying the propagation of delays. The complexity of the aviation network structure and the variability of delay interference factors make it more difficult to describe the delay propagation phenomenon. In addition, the explosive development of the data information age has caused the propagation of flight delays to present a dynamic and self-healing phenomenon. This is because the key factors affecting the propagation of delays are no longer just delays caused by time movement and quantity association between flights within the aviation network. The reverse predictive recovery factors generated by emerging technologies and awareness methods such as artificial intelligence, cloud technology, and employee proficiency are gradually expanding their impact on the propagation of flight delays. The current delay propagation model lacks consideration of these predictive recovery factors, and the impact of these factors on delay propagation is still unknown. In addition, distinguishing initial delays is also a key element in studying delay propagation. Initial delays are delays caused by special events such as airport operations and crew members, and are not propagable. It is necessary to consider the changes in initial delays in the delay propagation model in order to more effectively characterize the propagation of delays, which is very important for the entire flight delay propagation analysis. Therefore, when establishing a delay propagation simulation model, it is necessary to quantify the external interference factors and establish a delay propagation mathematical model that takes the initial delay into account. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the related art. To this end, the present invention provides a delay propagation recovery simulation method based on regional perception and route perception coefficients, introduces regional perception coefficients and route perception coefficients into the traditional propagation simulation model to reduce the delay simulation error, and introduces a flight delay propagation model based on interference awareness based on the constructed delay propagation network. The model takes into account the external factors of delay propagation interference and the influence of internal regulation on delay propagation, constructs a multi-time window delayed aviation network with delay propagation causality, uses the time and space characteristics of hourly time window data, analyzes the behavior of delay propagation, and clarifies the influence of effective connection awareness and reverse prediction recovery awareness on delay propagation rate.

[0005] The present invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient, comprising: S1: Construct a multi-time window delay propagation route network with delay propagation characteristics; S2: A delay propagation model is established based on the probability that a normal flight in the multi-time window delay propagation route network is delayed due to the impact of the previous moment, the ratio of the number of delayed flights to the total number of delayed flights, and the number of effective direct connecting flights of delayed flights; S3: Obtain the variation characteristics of delay propagation rate in time and route connectivity based on the delay propagation model; S4: Obtain a delay propagation equilibrium point model based on the variation characteristics of the delay propagation rate in time and route connectivity, and obtain a delay propagation rate threshold through the delay propagation equilibrium point model; S5: Through the delay propagation rate threshold, the relationship between effective connection awareness and delay propagation rate and the relationship between reverse prediction recovery awareness and delay propagation rate are obtained; S6: Use MATLAB to fit the actual parameter values ​​of reverse prediction recovery awareness and effective connection awareness, and verify the influence of reverse prediction recovery awareness and effective connection awareness on the delayed propagation threshold.

[0006] According to the present invention, a delay propagation recovery simulation method based on regional perception and route perception coefficients further includes: in the step S1, the calculation expression of the multi-time window delay propagation route network with delay propagation characteristics is: in, for The total number of flights at the time, for The normal number of flights at the time; for The number of flight delays due to delay propagation at the given moment; for The number of flight delays due to spontaneous reasons at the time.

[0007] According to a delay propagation and recovery simulation method based on regional perception and route perception coefficients provided by the present invention, the method further includes the probability of a normal flight in a multi-time window delayed aviation network being affected by the previous moment and causing delay, the ratio of the number of delayed flights recovered to the total number of delayed flights, and the number of effective directly connected flights of delayed flights in the step S2 to establish a delay propagation model. The calculation expression of the delay propagation model is: in, for The number of flight delays due to delay propagation at the time, To delay the transmission rate; for The ratio of the number of flights that have been delayed to the total number of flights that have been delayed; for The number of valid direct connecting flights for the delayed flight, is the change in time; Set up the differential equation: in, For flights with 0-hour delay, is the initial number of delayed flights; By solving the differential equation, we can obtain the expression for the change of the number of delayed flights over time: The number of flights with delayed propagation is positively correlated with the number of effective direct connections of flights and the delay propagation rate.

[0008] According to a delay propagation recovery simulation method based on regional perception and route perception coefficients provided by the present invention, it also includes extracting route connectivity structural features of the delay propagation route network in each time window to establish a multi-dimensional aviation sub-network.

[0009] According to a delay propagation recovery simulation method based on regional perception and route perception coefficient provided by the present invention, the method further includes the step S3, in which the degree is In the aviation subnetwork of The probability that a normal flight in the aviation network at a certain time is delayed due to the influence of the previous time is affected by the degree of flights in the area and effectively connected flights. The calculation expression for the total number of flights is: in, is the total number of flights, is the degree of the aviation subnetwork, ( ) is the degree The total number of flights, For degree The number of normal flights; For degree The number of flight delays due to delay propagation; For degree The number of flight delays caused by spontaneous reasons, for The number of valid connections at the moment; Degree Flights Degree Delayed flights The probability of infection is: in, For degree Reverse prediction to restore consciousness , The extent to which flight delays interfere with staff's delay recovery work, The level of emergency response adopted according to the scope of delay propagation. is the number of adjacent linked flights of the delayed flight; For degree Effective connection awareness, For degree The probability of For degree The delayed propagation rate, For degree The delayed propagation rate, For degree The degree distribution rate of the aviation subnetwork, For degree The density of delayed flights; The probability of a flight having delay propagation among all its linked flights: in, is the probability of a flight with delay propagation among all the linked flights of the flight; have Delayed flights and The probability of a normal flight: in, For degree The number of connected flights for the flight; For Delayed flights and The probability of a normal flight; Degree The flights were The probability of delayed flights spreading is: in, Degree Delayed transmission rate; The probability of a normal flight being delayed is: in, is the probability of a normal flight being delayed, and E is the probability.

[0010] A delay propagation recovery simulation method based on area perception and route perception coefficients provided by the present invention also includes a discrete dynamics model: in, for The ratio of the number of delayed flights recovered to the total number of delayed flights, for The time scale is The density of delayed flights; From the discrete dynamics model, we can get: Finding the limit gives: in, To effectively connect consciousness, For degree The probability of the number of connected flights for a flight with For degree The interference level is The probability of the number of connected flights for the flight ; Through the matrix generation function, the probability can be realized Parameter estimates for : in, is a matrix, For the matrix The exponential function of is the probability of a flight having delay propagation among all its linked flights, is the initial matrix transpose, For degree and the interference level is The matrix of the number of connected flights for flights , For degree and the interference level is The probability of the number of connected flights for the flight ; , for The higher order terms.

[0011] According to a delay propagation recovery simulation method based on area perception and route perception coefficient provided by the present invention, the delay propagation equilibrium point model is also included in the step S4: The coefficient matrix can be established: in, is the coefficient matrix, is the first cofactor, , As the second cofactor, ; The eigenvalues ​​of the coefficient matrix are: The characteristic value of , ; when When , the delay propagation equilibrium point of the aviation network is in an unbalanced state. When , the delay propagation equilibrium point is in equilibrium state, and the delay propagation equilibrium point is: in: is the delay propagation equilibrium point, for The number of delayed valid connections at the time; when , the delayed propagation reaches the propagation threshold, and the delayed propagation threshold calculation expression is: in, is the delay propagation threshold; As awareness of reverse prediction recovery increases and / or awareness of effective connectivity increases, the threshold of the delayed propagation rate will gradually increase.

[0012] According to a delay propagation recovery simulation method based on regional perception and route perception coefficient provided by the present invention, the method further includes fitting the actual parameter values ​​of reverse prediction recovery awareness and the actual parameter values ​​of effective connection awareness using Matlab in the step S6; including: S61: Through effective connection awareness and reverse prediction and recovery awareness, the threshold of the final delay propagation rate is obtained to determine the outbreak of flight delay propagation; S62: The actual parameter value of effective connection awareness is determined based on the impact of effective connection awareness on the delay propagation rate, the degree of interference of flight delays on the delay recovery work of the staff, and the level of emergency response adopted according to the scope of delay propagation. S63: Determine the impact of reverse prediction recovery awareness on the delay propagation rate by changing the delayed flight propagation rate in the degree structure; S64: The effectiveness of the delayed propagation model is verified by taking values ​​of reverse prediction recovery awareness and effective connection awareness.

[0013] The above one or more technical solutions in the embodiments of the invention have at least one of the following technical effects: The present invention provides a delay propagation recovery simulation method based on regional perception and route perception coefficients, introduces regional perception coefficients and route perception coefficients into the traditional propagation simulation model to reduce the delay simulation error, and introduces a flight delay propagation model based on interference awareness based on the constructed delay propagation network. The model considers the influence of external factors and internal regulation of delay propagation interference on delay propagation, constructs a multi-time window delayed aviation network with delay propagation causality, uses the time and space characteristics of hourly time window data, analyzes the behavior of delay propagation, and clarifies the influence of effective connection awareness and reverse prediction recovery awareness on delay propagation rate.

[0014] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A schematic flow chart of a delay propagation recovery simulation method based on area perception and route perception coefficients provided by the present invention.

[0017] Figure 2 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficients, which shows the spatial variation of delay propagation of a navigation network with delay propagation characteristics and the evolution of its connectivity.

[0018] Figure 3 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient and a temporal variation characteristic of the delay propagation rate.

[0019] Figure 4 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient and a delay propagation rate variation characteristic in degree.

[0020] Figure 5 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient, and the time variation of the number of delayed effective connections.

[0021] Figure 6 The present invention provides a delay propagation recovery simulation method based on area perception and route perception coefficients, and shows the changing relationship between the number of delayed effective connections and the number of delayed flights.

[0022] Figure 7 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient, and discloses an influence of effective connection awareness on delay propagation rate.

[0023] Figure 8 The invention provides a delay propagation recovery simulation method based on area perception and route perception coefficient, and discusses the impact of reverse prejudgment recovery awareness on the delay propagation rate.

[0024] Fig. 9 The invention provides a delay propagation recovery simulation method based on regional perception and route perception coefficient to illustrate the propagation of flight delays. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme in the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0026] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0027] Combine the following Figures 1 to 9 The present invention describes a delay propagation recovery simulation method based on area perception and route perception coefficients.

[0028] A delay propagation recovery simulation method based on area perception and route perception coefficients, comprising: S1: Construct a multi-time window delay propagation route network with delay propagation characteristics; The calculation expression of the multi-time window delay propagation route network with delay propagation characteristics is: in, for The total number of flights at the time, for The normal number of flights at the time; for The number of flight delays due to delay propagation at the given moment; for The number of flight delays due to spontaneous reasons at the time.

[0029] S2: A delay propagation model is established based on the probability that a normal flight in the multi-time window delay propagation route network is delayed due to the impact of the previous moment, the ratio of the number of delayed flights to the total number of delayed flights, and the number of effective direct connecting flights of delayed flights; The delay propagation model is established based on the probability that a normal flight in a multi-time window delayed aviation network is affected by the previous moment and is delayed, the ratio of the number of delayed flights to the total number of delayed flights, and the number of effective direct connecting flights of delayed flights. The calculation expression of the delay propagation model is: in, for The number of flight delays due to delay propagation at the time, To delay the transmission rate; for The ratio of the number of flights that have been delayed to the total number of flights that have been delayed; for The number of valid direct connecting flights for the delayed flight, is the change in time; Set up the differential equation: in, For flights with 0-hour delay, is the initial number of delayed flights; Will Differential equation, we get: The left side of the equation is 0, and we get: in, ; By scoring points, you can obtain: Where c is a constant; Will Substituting into the differential equation, we obtain: in, , ; because , so we get ,Will Substituting into the above formula, we get: Integrate both sides: in, , ; By solving the differential equation, we can obtain the expression for the change of the number of delayed flights over time: The number of flights with delayed propagation is positively correlated with the number of effective direct connections of flights and the delay propagation rate.

[0030] S3: Obtain the variation characteristics of delay propagation rate in time and route connectivity based on the delay propagation model; By extracting the route connectivity structural features of the delay propagation route network in each time window, a multi-dimensional aviation sub-network is established; In degree In the aviation subnetwork of The probability that a normal flight in the aviation network at a certain time is delayed due to the influence of the previous time is affected by the degree of flights in the area and effectively connected flights. The calculation expression for the total number of flights is: in, is the total number of flights, is the degree of the aviation subnetwork, ( ) is the degree The total number of flights, For degree The number of normal flights; For degree The number of flight delays due to delay propagation; For degree The number of flight delays caused by spontaneous reasons, for The number of valid connections at the moment; Degree Flights Degree Delayed flights The probability of infection is: in, For degree Reverse prediction to restore consciousness , The extent to which flight delays interfere with staff's delay recovery work, The level of emergency response adopted according to the scope of delay propagation. is the number of adjacent linked flights of the delayed flight; For degree Effective connection awareness, For degree The probability of For degree The delayed propagation rate, For degree The delayed propagation rate, For degree The degree distribution rate of the aviation subnetwork, For degree The density of delayed flights; The probability of a flight having delay propagation among all its linked flights: in, is the probability of a flight with delay propagation among all the linked flights of the flight; have Delayed flights and The probability of a normal flight: in, For degree The number of connected flights for the flight; For Delayed flights and The probability of a normal flight; Degree The flights were The probability of delayed flights spreading is: in, Degree Delayed transmission rate; The probability of a normal flight being delayed is: in, is the probability of a normal flight being delayed, and E is the probability.

[0031] S4: Obtain a delay propagation equilibrium point model according to the variation characteristics of the delay propagation rate in time and degree, and obtain a delay propagation rate threshold through the delay propagation equilibrium point model; The discrete dynamics model is: in, for The ratio of the number of delayed flights recovered to the total number of delayed flights, for The time scale is The density of delayed flights; From the discrete dynamics model, we can get: Finding the limit gives: in, To effectively connect consciousness, For degree The probability of the number of connected flights for a flight with For degree The interference level is The probability of the number of connected flights for the flight ; Through the matrix generation function, the probability can be realized Parameter estimates for : in, is a matrix, For the matrix The exponential function of is the probability of a flight having delay propagation among all its linked flights, is the initial matrix transpose, For degree and the interference level is The matrix of the number of connected flights for flights , For degree and the interference level is The probability of the number of connected flights for the flight ; The delay propagation equilibrium model is: The coefficient matrix can be established: in, is the coefficient matrix, is the first cofactor, , As the second cofactor, ; The eigenvalue calculation expression of the coefficient matrix is: The characteristic value of , ; when When , the propagation equilibrium point of aviation network delay is in an unbalanced state. When , the delayed propagation equilibrium point is in equilibrium; in: is the delay propagation equilibrium point, for The number of delayed valid connections at the time; when , the delayed propagation reaches the propagation threshold, and the delayed propagation threshold calculation expression is: in, is the delay propagation threshold; As awareness of reverse prediction recovery increases and / or awareness of effective connectivity increases, the threshold of the delayed propagation rate will gradually increase.

[0032] S5: Through the delay propagation rate threshold, the relationship between effective connection awareness and delay propagation rate and the relationship between reverse prediction recovery awareness and delay propagation rate are obtained; S6: Use matlab to fit the actual parameter values ​​of reverse prediction recovery consciousness and effective connection consciousness, and verify the influence of reverse prediction recovery consciousness and effective connection consciousness on the delay propagation threshold. Use matlab to fit the actual parameter values ​​of reverse prediction recovery consciousness and effective connection consciousness; including: S61: Through effective connection awareness and reverse prediction and recovery awareness, the threshold of the final delay propagation rate is obtained to determine the outbreak of flight delay propagation; S62: The actual parameter value of effective connection awareness is determined based on the impact of effective connection awareness on the delay propagation rate, the degree of interference of flight delays on the delay recovery work of the staff, and the level of emergency response adopted according to the scope of delay propagation. S63: Determine the impact of reverse prediction recovery awareness on the delay propagation rate by changing the delayed flight propagation rate in the degree structure; S64: The effectiveness of the model is verified by taking values ​​of reverse prediction recovery consciousness and effective connection consciousness.

[0033] In a specific embodiment of the present invention, based on 38,017 pieces of flight information in China, involving 235 airports, 5,979 routes are formed, of which 6,219 flights are delayed. The network propagation is divided into 21-hour time windows from 5 a.m. to 1 a.m. the next day, and propagation characteristics are analyzed for each time window. The 6,219 delayed flights are sorted out, and 2,998 valid flight delay time series are sorted out. Granger causality analysis is performed on the time series, and finally 1,557 flights with delay causal relationships are calculated, thereby forming a delay propagation route network of 21 time windows.

[0034] like Figure 2As shown in the figure, in the delay propagation route network of 21 time windows, the delay propagation characteristics are as follows: starting from 6:00, the route volume increases sharply in the next three hours, and then remains at a high level until there is a relatively slight decline at 13:00, but it returns to a high level at the next moment, and the route volume reaches a peak at 17:00, and then the route volume begins to decline sharply from 18:00 to 1:00 in the morning, and finally returns to zero. Because there is no passenger traffic between 2:00 and 4:00 in the morning, the flight volume is zero. The data shows that 76.3% of flight delay propagation occurs between 7:00 and 18:00, with peak times from 11:00 to 12:00 and 14:00 to 18:00, accounting for 50.48% of all flights. Different from the analysis results of the traditional aviation network, the commuting time of the aviation network with delay propagation does not show two obvious peaks, but shows a longer peak cycle. This shows that in addition to the influencing factors of new flights, the continuity and regionality of delay propagation have changed the flight volume and structure of the aviation network.

[0035] The subnetworks from 5:00 to 6:00 and 23:00 to 01:00 show low connectivity and sparse spatial distribution characteristics. On the one hand, compared with the subnetwork from 5:00 to 6:00, the connectivity of the time period from 23:00 to 01:00 is higher than that of 5:00 to 6:00 because the transportation pressure of each airport during peak hours is relieved. On the other hand, the subnetworks of these two time windows show flight characteristics of long flight time and flight distance (average flight time is 5 hours), and most of the aircraft airports are Class I busy airports (mainly Beijing Capital International Airport and Chengdu Shuangliu International Airport). After 6 o'clock, the number of routes increased significantly, and the structural characteristics of high connectivity and rapid diffusion of spatial distribution began to appear. The evolutionary characteristics of connectivity are characterized by airport connections between provincial capital cities first, followed by airport route connections from provincial capital cities to prefecture-level cities to county-level cities. The spatial diffusion process shows the distribution characteristics from east to west and from north to south.

[0036] Based on the delay propagation model, the delay propagation rate is obtained In time and degree The changing characteristics of It fluctuates wildly during the dawn and evening, but is relatively stable the rest of the time. The decrease and increase of means the change of the speed and scope of delayed flights propagating in the network. The larger the value, the wider and faster the delay of the delayed flight will spread; Figure 3 As shown, There are two peaks in time, at 6:00 and 23:00. Figure 4 As shown in Figure 2, these two time windows are also the critical values ​​for the sudden change in the number of sub-network routes over time.

[0037] When considering the time effect of the link, Number of routes There is a negative correlation. When the number of routes is small, there are fewer factors that hinder the spread of delays, and the spread rate is large. On the contrary, the sub-network structure with a large number of routes is complex. In addition to external awareness interference, the internal route delay recovery ability has a strong inhibitory effect on the spread of delays, so the spread rate is reduced. On the other hand, With degree Negatively correlated. The changes in the route determine the connectivity of the route. , the routes are independent and single, without connectivity. When an aircraft airport is delayed, there is almost no other external effect to hinder the propagation of route delays except for recovering from the delay during the flight. The delay propagation rate is 0.94. With the increase of the number of flights, the network is highly connected, and there are connections between routes, which can interact and influence each other. When delay propagation occurs, it can be controlled by adjusting the relevant routes, so the delay propagation rate shows a downward trend. The consequence of lack of connectivity is one of the reasons for the subsequent increase in the number of airport delays.

[0038] < >Average degree centrality indicates the average number of connections involved in a node. Figure 5 As shown, in the time dimension, < >Shows a peak and a non-peak pattern with fluctuations similar to those observed for route volume, however, the increase in dawn hours (6:00 to 9:00) and the decrease in night hours (23:00 to 1:00) both change at a faster rate, implying that a small increase in dawn and night hours flights leads to a significant increase in the centralization of the delay propagation network. Figure 6 As shown, it reflects The relationship between the number of delayed flights and the number of delayed flights I is that due to the large base of the network itself, the number of delayed flights increases with However, the fluctuation curve of delayed flights tends to be flat, which once again proves the negative correlation between connectivity and the speed and scope of delay propagation.

[0039] Through the constructed sub-network and flight delay information, Matlab is used to fit the reverse prediction recovery consciousness and effective connection awareness The actual parameter value ( =0.4186, =0.1006, =2), by and The influence of interference awareness on the delay propagation threshold is verified by taking different values ​​of the parameters.

[0040] The final delay propagation rate threshold is obtained, and the outbreak of the delay propagation rate threshold is determined. When >0.5944, the flight delay propagation will explode and the delay control equilibrium point will be unstable. The impact on the transmission rate. Figure 7 As shown, =0.1006, =2, change , The values ​​are 0.4186, 0.2, and 0.8 respectively.

[0041] According to the change of the delay propagation rate in degree, the data show that effective connection awareness can change the size of the delay propagation rate and the stability of the propagation rate threshold. With the enhancement of effective connection awareness, the propagation rate threshold also increases, and the delay propagation rate decreases. Effective connection awareness can effectively control the outbreak of delay propagation. Considering the actual propagation rate threshold, there is >0.5944, and the actual effective connection awareness has not reached a more ideal range This proves that the existing aviation network needs to appropriately increase the number of routes with strong connections to share the delay propagation, thereby reducing the delay propagation rate. Figure 8 As shown, the reverse prediction of recovery consciousness was determined The effect on the transmission rate is achieved by changing The value of =0.1006, =0.5, =0.8) found that reverse prediction recovery awareness and effective connection awareness were the same. With the enhancement of reverse prediction recovery awareness ( Increase, Reduce, Increase) The propagation rate threshold also increases, and the delay propagation rate decreases. In the current regional awareness of the delay propagation network, the interference of delay information to staff is relatively low ( =0.1006), by changing , the delay propagation rate threshold can be lower than 0.5944, so there is no need to make additional adjustments to regional awareness. Fig. 9 As shown, it reflects the propagation of flight delays and verifies the feasibility of the delay propagation model.

[0042] From an overall perspective, the delays began to spread rapidly from 6:00 to 10:00, and after being suppressed in a small area at 13:00, they broke out again and gradually dissipated after 19:00. The fluctuation of the delay propagation is the same as the propagation rate. The error between the flight delay propagation curve simulated by the propagation model and the actual fluctuation is controlled between [-5, +5], which proves that the delay propagation model is constructed correctly and effectively.

[0043] The beneficial effects of the present invention are as follows: the present invention provides a delay propagation recovery simulation method based on regional perception and route perception coefficients, introduces regional perception coefficients and route perception coefficients into the traditional propagation simulation model to reduce the delay simulation error, and introduces a flight delay propagation model based on interference awareness based on the constructed delay propagation network. The model considers the influence of external factors and internal regulation of delay propagation interference on delay propagation, constructs a multi-time window delayed aviation network with delay propagation causality, uses the time and space characteristics of hourly time window data, analyzes the behavior of delay propagation, and clarifies the influence of effective connection awareness and reverse prediction recovery awareness on delay propagation rate.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A delay propagation recovery simulation method based on area perception and route perception coefficients, characterized in that: include: S1: Construct a multi-time window delay propagation route network with delay propagation characteristics; S2: Establish a delay propagation model based on the probability that a normal flight in the multi-time window delay propagation route network is delayed due to the impact of the previous moment, the ratio of the number of delayed flights to the total number of delayed flights, and the number of effective direct connecting flights of delayed flights; S3: Obtain the variation characteristics of delay propagation rate in time and route connectivity based on the delay propagation model; S4: Obtain a delay propagation equilibrium point model based on the variation characteristics of the delay propagation rate in time and route connectivity, and obtain a delay propagation rate threshold through the delay propagation equilibrium point model; S5: Through the delay propagation rate threshold, the relationship between effective connection awareness and delay propagation rate and the relationship between reverse prediction recovery awareness and delay propagation rate are obtained; S6: Use MATLAB to fit the actual parameter values ​​of reverse prediction recovery awareness and effective connection awareness, and verify the influence of reverse prediction recovery awareness and effective connection awareness on the delayed propagation threshold.

2. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 1, characterized in that: In the step S1, the calculation expression of the multi-time window delay propagation route network with delay propagation characteristics is: in, for The total number of flights at the time, for The normal number of flights at the time; for The number of flight delays due to delay propagation at the given moment; for The number of flight delays due to spontaneous reasons at the time.

3. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 2, characterized in that: In step S2, the probability of a normal flight in the multi-time window delayed aviation network being affected by the previous moment and causing delay, the ratio of the number of delayed flights to the total number of delayed flights, and the number of effective direct connecting flights of delayed flights are used to establish a delay propagation model. The calculation expression of the delay propagation model is: in, for The number of flight delays due to delay propagation at the time, To delay the transmission rate; for The ratio of the number of flights that have been delayed to the total number of flights that have been delayed; for The number of valid direct connecting flights for the delayed flight, is the change in time; Set up the differential equation: in, For flights with 0-hour delay, is the initial number of delayed flights; By solving the differential equation, we can obtain the expression for the change of the number of delayed flights over time: The number of flights with delayed propagation is positively correlated with the number of effective direct connections of flights and the delay propagation rate.

4. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 1, characterized in that: By extracting the route connectivity structural features of the delay propagation route network in each time window, a multi-dimensional aviation sub-network is established.

5. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 4, characterized in that: In the step S3, the In the aviation subnetwork of The probability that a normal flight in the aviation network at a certain time is delayed due to the influence of the previous time is affected by the degree of flights in the area and effectively connected flights. The calculation expression for the total number of flights is: in, is the total number of flights, is the degree of the aviation subnetwork, ( ) is the degree The total number of flights, For degree The number of normal flights; For degree The number of flight delays due to delay propagation; For degree The number of flight delays caused by spontaneous reasons, for The number of valid connections at the moment; Degree Flights Degree Delayed flights The probability of infection is: in, For degree Reverse prediction to restore consciousness , The extent to which flight delays interfere with staff's delay recovery work, The level of emergency response adopted according to the scope of delay propagation. is the number of adjacent linked flights of the delayed flight; For degree Effective connection awareness, For degree The probability of For degree The delayed propagation rate, For degree The delayed propagation rate, For degree The degree distribution rate of the aviation subnetwork, For degree The density of delayed flights; The probability of a flight having delay propagation among all its linked flights: in, is the probability of a flight with delay propagation among all the linked flights of the flight; have Delayed flights and The probability of a normal flight: in, For degree The number of connected flights for the flight; For Delayed flights and The probability of a normal flight; Degree The flights were The probability of delayed flights spreading is: in, Degree Delayed transmission rate; The probability of a normal flight being delayed is: in, is the probability of a normal flight being delayed, and E is the probability.

6. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 5, characterized in that: The discrete dynamics model is: in, for The ratio of the number of delayed flights recovered to the total number of delayed flights, for The time scale is The density of delayed flights; From the discrete dynamics model, we can get: Finding the limit gives: in, To effectively connect consciousness, For degree The probability of the number of connected flights for a flight with For degree The interference level is The probability of the number of connected flights for the flight ; Through the matrix generation function, the probability can be realized Parameter estimates for : in, is a matrix, For the matrix The exponential function of is the probability of a flight having delay propagation among all its linked flights, is the initial matrix transpose, For degree and the interference level is The matrix of the number of connected flights for flights , For degree and the interference level is The probability of the number of connected flights for the flight ; , for The higher order terms.

7. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 6, characterized in that: In step S4, the delay propagation equilibrium point model is: The coefficient matrix can be established: in, is the coefficient matrix, is the first cofactor, , As the second cofactor, ; The eigenvalues ​​of the coefficient matrix are: The characteristic value of , ; when When , the delay propagation equilibrium point of the aviation network is in an unbalanced state. When , the delay propagation equilibrium point is in equilibrium state, and the delay propagation equilibrium point is: in: is the delay propagation equilibrium point, for The number of delayed valid connections at the time; when , the delayed propagation reaches the propagation threshold, and the delayed propagation threshold calculation expression is: in, is the delay propagation threshold; As awareness of reverse prediction recovery increases and / or awareness of effective connectivity increases, the threshold of the delayed propagation rate will gradually increase.

8. The delay propagation recovery simulation method based on area perception and route perception coefficient according to claim 1, characterized in that: In the step S6, Matlab is used to fit the actual parameter values ​​of reverse prediction recovery consciousness and the actual parameter values ​​of effective connection consciousness; including: S61: Through effective connection awareness and reverse prediction and recovery awareness, the threshold of the final delay propagation rate is obtained to determine the outbreak of flight delay propagation; S62: The actual parameter value of effective connection awareness is determined based on the impact of effective connection awareness on the delay propagation rate, the degree of interference of flight delays on the delay recovery work of the staff, and the level of emergency response adopted according to the scope of delay propagation. S63: Determine the impact of reverse prediction recovery awareness on the delay propagation rate by changing the delayed flight propagation rate in the degree structure; S64: The effectiveness of the delayed propagation model is verified by taking values ​​of reverse prediction recovery awareness and effective connection awareness.

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