General aviation flight data processing method and device

Abstract

The invention discloses a general aviation flight data processing method and device. The method comprises the following steps: acquiring general aviation flight data; according to the general aviation flight data, general aviation flight multi-dimensional relation data is obtained, and the multi-dimensional relation data comprises a general aviation enterprise set, an operation place set, an operation project set and a flight quantity data set; generating a general aviation flight multi-dimensional relational data image according to the general aviation flight multi-dimensional relational data; converting the general aviation flight multi-dimensional relation data into a matrix according to the image; determining the flight type of the general aviation enterprise in each operation site and the flight amount corresponding to each flight type according to the matrix; and according to the flight type of the general aviation enterprise in each workplace and the flight amount corresponding to each flight type, determining the flight service tendency degree of the general aviation enterprise in any workplace. According to the method, the flight service tendency degree of the general aviation enterprise in any operation site can be efficiently and accurately determined.

Description

Technical Field

[0001] The present invention relates to the technical field of big data, and in particular to a method and device for processing general aviation flight data. Background Art

[0002] This section aims to provide background or context for the embodiments of the present invention described in the claims. The description herein is not admitted to be prior art merely by virtue of being included in this section.

[0003] General aviation flight data refers to the civil aviation flight service data other than public air transportation using civil aircraft, including flight service data for industrial, agricultural, forestry, fishery and construction operations, as well as flight service data in aspects such as medical and health, emergency rescue, meteorological exploration, ocean monitoring, scientific experiments, education and training, culture and sports. However, general aviation has problems such as a large number of enterprises, many operation items, complicated operation locations, and messy flight data. There is no effective unified method for processing various general aviation flight data, and there is a problem that it is impossible to efficiently and accurately determine the flight service tendency of general aviation enterprises in any operation area, which is not conducive to promoting the development of general aviation. Summary of the Invention

[0004] Embodiments of the present invention provide a method for processing general aviation flight data to efficiently and accurately determine the flight service tendency of general aviation enterprises in any operation area. The method includes:

[0005] Collect general aviation flight data;

[0006] According to the general aviation flight data, obtain general aviation flight multi-dimensional relationship data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operation area set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation area element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set;

[0007] Generate a general aviation flight multi-dimensional relationship data image according to the general aviation flight multi-dimensional relationship data;

[0008] According to the general aviation flight multi-dimensional relationship data image, convert the general aviation enterprise set, the operation area set, and the operation item set into an all-enterprise operation item matrix for each operation area of general aviation flight, and convert the general aviation enterprise set, the operation area set, and the flight volume data set into a flight volume matrix for each operation item of all general aviation enterprises;

[0009] Determine the flight types of general aviation enterprises in each operating area and the flight volume corresponding to each flight type according to the matrix of operation items of all enterprises in each operating area of general aviation flights and the flight volume matrix of all enterprises in each operation item of general aviation flights.

[0010] Determine the flight service inclination of general aviation enterprises in any operating area according to the flight types of general aviation enterprises in each operating area and the flight volume corresponding to each flight type.

[0011] An embodiment of the present invention further provides a processing device for general aviation flight data, which is used to efficiently and accurately determine the flight service inclination of general aviation enterprises in any operating area. The device includes:

[0012] An acquisition unit, configured to acquire general aviation flight data;

[0013] A multi-dimensional relationship data determination unit, configured to obtain multi-dimensional relationship data of general aviation flights according to the general aviation flight data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operating area set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operating area element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set;

[0014] A multi-dimensional relationship data image generation unit, configured to generate a multi-dimensional relationship data image of general aviation flights according to the multi-dimensional relationship data of general aviation flights;

[0015] A matrix conversion unit, configured to convert the general aviation enterprise set, the operating area set, and the operation item set into a matrix of operation items of all enterprises in each operating area of general aviation flights according to the multi-dimensional relationship data image of general aviation flights, and convert the general aviation enterprise set, the operating area set, and the flight volume data set into a flight volume matrix of all enterprises in each operation item of general aviation flights;

[0016] A flight type and flight volume determination unit, configured to determine the flight types of general aviation enterprises in each operating area and the flight volume corresponding to each flight type according to the matrix of operation items of all enterprises in each operating area of general aviation flights and the flight volume matrix of all enterprises in each operation item of general aviation flights;

[0017] A flight service inclination determination unit, configured to determine the flight service inclination of general aviation enterprises in any operating area according to the flight types of general aviation enterprises in each operating area and the flight volume corresponding to each flight type.

[0018] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for processing general aviation flight data is implemented.

[0019] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned method for processing general aviation flight data is implemented.

[0020] An embodiment of the present invention further provides a computer program product including a computer program, and when the computer program is executed by a processor, the above-mentioned method for processing general aviation flight data is implemented.

[0021] The processing solution for general aviation flight data provided by the embodiment of the present invention includes: collecting general aviation flight data; obtaining multi-dimensional relationship data of general aviation flight based on the general aviation flight data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set; generating an image of multi-dimensional relationship data of general aviation flight based on the multi-dimensional relationship data of general aviation flight; converting the general aviation enterprise set, the operation location set, and the operation item set into a matrix of operation items of all enterprises within each operation location of general aviation flight, and converting the general aviation enterprise set, the operation location set, and the flight volume data set into a flight volume matrix of each operation item of all enterprises of general aviation flight according to the image of multi-dimensional relationship data of general aviation flight; determining the flight type of general aviation enterprises within each operation location and the flight volume corresponding to each flight type according to the matrix of operation items of all enterprises within each operation location of general aviation flight and the flight volume matrix of each operation item of all enterprises of general aviation flight; and determining the flight service inclination degree of general aviation enterprises within any operation location according to the flight type of general aviation enterprises within each operation location and the flight volume corresponding to each flight type, so as to efficiently and accurately determine the flight service inclination degree of general aviation enterprises within any operation location. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0023] Figure 1 This is a schematic flowchart of the method for processing general aviation flight data in an embodiment of the present invention;

[0024] Figure 2 This is a schematic flowchart of the data cleaning operation for general aviation flight data in an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of the general aviation flight multi-dimensional relationship data image in an embodiment of the present invention;

[0026] Figure 4 This is a schematic structural diagram of the device for processing general aviation flight data in an embodiment of the present invention;

[0027] Figure 5 This is a schematic structural diagram of a computer device according to an embodiment of the present invention. Detailed implementation manners

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer and more understandable, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings. Herein, the illustrative embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.

[0029] In the technical solution of this application, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of laws and regulations.

[0030] Figure 1 This is a schematic flowchart of the method for processing general aviation flight data in an embodiment of the present invention. As Figure 1 shown, the method includes the following steps:

[0031] Step 101: Collect general aviation flight data;

[0032] Step 102: Obtain general aviation flight multi-dimensional relationship data according to the general aviation flight data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set;

[0033] Step 103: Generate a general aviation flight multi-dimensional relationship data image according to the general aviation flight multi-dimensional relationship data;

[0034] Step 104: According to the multi-dimensional relationship data image of general aviation flights, convert the general aviation enterprise set, the operation location set, and the operation item set into the operation item matrix of all enterprises within each operation location of general aviation flights, and convert the general aviation enterprise set, the operation location set, and the flight volume data set into the flight volume matrix of all enterprises for each operation item of general aviation flights;

[0035] Step 105: Determine the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type according to the operation item matrix of all enterprises within each operation location of general aviation flights and the flight volume matrix of all enterprises for each operation item of general aviation flights;

[0036] Step 106: Determine the flight service preference of general aviation enterprises within any operation location according to the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type.

[0037] The general aviation flight data processing method provided by the embodiment of the present invention, when working: collect general aviation flight data; obtain multi-dimensional relationship data of general aviation flights according to the general aviation flight data; the multi-dimensional relationship data includes: general aviation enterprise set, operation location set, operation item set, and flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set; generate a multi-dimensional relationship data image of general aviation flights according to the multi-dimensional relationship data of general aviation flights; convert the general aviation enterprise set, the operation location set, and the operation item set into the operation item matrix of all enterprises within each operation location of general aviation flights according to the multi-dimensional relationship data image of general aviation flights, and convert the general aviation enterprise set, the operation location set, and the flight volume data set into the flight volume matrix of all enterprises for each operation item of general aviation flights; determine the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type according to the operation item matrix of all enterprises within each operation location of general aviation flights and the flight volume matrix of all enterprises for each operation item of general aviation flights; determine the flight service preference of general aviation enterprises within any operation location according to the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type, and can efficiently and accurately determine the flight service preference of general aviation enterprises within any operation location. The following is combined with Figures 2 to 3 for a detailed introduction.

[0038] In the above step 101, in one embodiment, collecting general aviation flight data may include: obtaining the general aviation flight data by parsing the structured flight data of the general aviation management system.

[0039] In specific implementation, the general aviation flight data in the embodiments of the present invention refers to the civil aviation flight service data other than engaging in public air transportation using civil aircraft, including the operation flight data for industrial, agricultural, forestry, fishery and construction industries, as well as the flight service data in aspects such as medical and health, emergency rescue, meteorological detection, ocean monitoring, scientific experiments, education and training, culture and sports, etc.

[0040] In specific implementation, the data in the embodiments of the present invention is collected from the real general aviation flight data in the general aviation management system, and the general aviation flight data is obtained by parsing the structured flight data in the general aviation management system.

[0041] After the above step 101, in one embodiment, the processing method of the general aviation flight data may further include: performing data cleaning operations on the collected general aviation flight data, such as missing value processing, outlier processing, and redundant data removal processing.

[0042] In specific implementation, the embodiments of the present invention perform data cleaning operations on the collected general aviation flight data, such as missing value processing, outlier processing, and redundant data removal processing, which improves the efficiency and accuracy of subsequent general aviation flight data processing.

[0043] Figure 2 It is a schematic flow diagram of the data cleaning operation for the general aviation flight data in the embodiments of the present invention. As Figure 2 shown, in one embodiment, the data cleaning operation for the collected general aviation flight data, such as missing value processing, outlier processing, and redundant data removal processing, may include:

[0044] Step 201: If any general aviation flight data item has a null value or missing data, delete the entire structured data corresponding to the general aviation flight data item with the null value or missing data, and obtain the general aviation flight data after missing value processing;

[0045] Step 202: For the general aviation flight data items after missing value processing with non-numeric flight volumes, delete the entire structured data corresponding to the general aviation flight data items with non-numeric flight volumes, and obtain the general aviation flight data after outlier processing;

[0046] Step 203: Identify and eliminate the duplicate row data in the general aviation flight data after outlier processing, and obtain the general aviation flight data after redundant data removal processing as the general aviation flight data after the data cleaning operation.

[0047] In specific implementation, the data cleaning operations adopted in the implementation of the present invention mainly include: (1) Missing value processing method: when any core data item has a null value or missing data, the entire structured data corresponding to this core data item will be deleted; (2) Outlier processing method: for data items with non-numeric "flight number", the entire structured data corresponding to this core data item will be removed; (3) Removal of duplicate and redundant data: identify and eliminate completely duplicate row data in the structured data, and only retain the unique one to reduce duplicate data generated by system anomalies; for data with "flight volume" being 0 as redundant and invalid data, data deletion will be performed; (4) Data standardization processing: set the ranges of the administration set, supervision bureau set, flight project set, and general aviation enterprise set, and standardize the corresponding set ranges of the collected core data items.

[0048] In specific implementation, the above specific implementation methods of data cleaning operations for missing value processing, outlier processing, and redundant data removal of the collected general aviation flight data improve the efficiency and accuracy of subsequent general aviation flight data processing.

[0049] In specific implementation, in the embodiment of the present invention, there are a general aviation flight enterprise set Q, an operation location set D, an operation project set X, a flight data volume set F, a national administration set G, and a national supervision bureau set J. The Q set includes tens of thousands of general aviation enterprises, and each general aviation enterprise is represented as q; for the operation location set D, according to the characteristics of the general aviation field here, a large-area operation location corresponds to the jurisdiction ranges of multiple, for example, 40 supervision bureaus (supervision agencies), and the supervision bureau set J, and each type of supervision bureau is represented as j; the operation location set D includes multiple operation locations, and each operation location is represented as d; the operation project set X includes multiple, for example, 29 types of operation projects with business licenses, and each type of operation project is represented as x; the flight data volume set F includes flight hours f; the administration (management agency) set G can include multiple (for example, 7) regional administrations, and each administration is represented as g.

[0050] The relationships among sets Q, D, X, F, G, and J are as follows: For any enterprise element q in set Q, there is a unique corresponding regulatory bureau element j in set J. For any regulatory bureau element j in set J, it can correspond to multiple different enterprise elements q. For any regulatory bureau element j in set J, there is a unique corresponding management bureau element g in set G. For any management bureau element g in set G, it can correspond to multiple different regulatory bureau elements j. Set D = set J. Any enterprise element q in set Q can have multiple project elements x. Each project element x in set X can be carried out simultaneously by multiple enterprise elements q. Any enterprise element q in set Q can carry out operation projects in any operation location element d in set D. The operation projects that enterprise element q can carry out include one or more in set X. Enterprise element q can carry out multiple projects x in one operation location element d. X = {x1, x2... x 29}. Any operation project in the operation project set corresponds to the flight volume in the flight volume data set, that is, the flight volume corresponding to any operation project in the operation project set is in the flight volume data set.

[0051] As can be seen from the above, in step 102, based on the collected general aviation flight data, the obtained general aviation flight multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation project set, and a flight volume data set. Among them: any enterprise element in the enterprise set corresponds to at least one operation project element in the operation project set and at least one operation location element in the operation location set. Any operation project element in the operation project set corresponds to at least one enterprise element in the enterprise set.

[0052] As can be seen from the above, in step 102, in one embodiment, the multi-dimensional relationship data may further include: a regulatory agency set, and each regulatory agency element in the regulatory agency set corresponds to the corresponding supervised operation location element in the operation location set.

[0053] As can be seen from the above, in step 102, in one embodiment, the multi-dimensional relationship data may further include: a management agency set, and each management agency element in the management agency set corresponds to the corresponding supervised operation location element in the operation location set. Any general aviation enterprise element in the general aviation enterprise set uniquely corresponds to one regulatory agency element in the regulatory agency set. Any regulatory agency element in the regulatory agency set corresponds to at least one enterprise element in the general aviation enterprise set. Any regulatory agency element in the regulatory agency set uniquely corresponds to one management agency element in the management agency set. Any management agency element in the management agency set corresponds to at least one regulatory agency element in the regulatory agency set.

[0054] In step 103, the generated general aviation flight multi-dimensional relationship data image can be as Figure 3As shown Figure 3 This is a schematic diagram of the multi-dimensional relationship data image of general aviation flight in the embodiment of the present invention.

[0055] In the above step 104, according to the multi-dimensional relationship data image of general aviation flight, the core data of general aviation flight after cleaning is stored, and the collected structured data is processed by matrix storage according to the many-to-many characteristics of general aviation flight data. The many-to-many relationship can be: one enterprise can carry out multiple operation projects, and one operation project can be carried out by multiple enterprises.

[0056] Specifically, in the above step 105, according to the multi-dimensional relationship data image of general aviation flight, the general aviation enterprise set, the operation location set and the operation project set are converted into the operation project matrix of all enterprises in each operation location of general aviation flight, and the general aviation enterprise set, the operation location set and the flight volume data set are converted into the flight volume matrix of all enterprises in each operation project of general aviation flight.

[0057] Specifically, the flight project matrix of all enterprises in any operation location (the operation project matrix of all enterprises in each operation location of general aviation flight) is: Where a = 1, 2... n, representing the number of enterprises, b = 1, 2... 29, representing the operation project number; x a,b Represents the b-th project corresponding to the a-th enterprise; x a,b ∈{0, 1}, representing the situation of the enterprise operation project approved by the administration, x a,b When it is 0, it means that the a-th enterprise cannot operate the b-th operation project, x a,b When it is 1, it means that the a-th enterprise can operate the b-th operation project.

[0058] The flight numbers of all enterprises for each operation project (the flight volume matrix of all enterprises in each operation project of general aviation flight) are: Where a = 1, 2... n, representing the number of enterprises, b = 1, 2... 29, representing the operation project number; f a,b Represents the flight number of the b-th project corresponding to the a-th enterprise, f a,b Is the flight volume after data cleaning, f a,b ≥0.

[0059] The flight volume in any operation location, or the flight volume of enterprises in the jurisdiction of the supervision bureau (supervision agency) can be uniformly expressed as:

[0060] In the formula, x a,b Is the b-th project corresponding to the a-th enterprise, f a,b Is the flight volume after data cleaning of the b-th project corresponding to the a-th enterprise.

[0061] Further, the flight volume of the operating locations in the jurisdiction of the management agency can be obtained by accumulating the flight volumes of the enterprises in the jurisdiction of the regulatory agencies within the jurisdiction of the management agency.

[0062] Through the above formula (model) F, the above step 105 can be implemented: according to the matrix of the operation items of all enterprises in each operating location of general aviation flight and the flight volume matrix of each operation item of all enterprises in general aviation flight, determine the flight types of general aviation enterprises in each operating location and the flight volume corresponding to each flight type.

[0063] In specific implementation, the embodiment of the present invention may further include an optimization scheme for setting weights for parameters. The optimization scheme includes: setting weights for parameters, and the weights set for parameters are represented by variables and are not fixed settings that remain unchanged. It mainly includes two parts: (1) x 1，1 to x 1，29 represent 29 flight items of the first enterprise. 29 items are the maximum values of general aviation operation licenses. If the first enterprise is approved for 4 flight items, namely the 1st, 5th, 11th, and 23rd flight items, then x 1，1 , x 1，5 , x 1，11 , x 1，23 will have a value of 1, and the other 25 values will be 0. If the nth enterprise is approved for 28 items and only the 2nd flight item is not permitted, then the x n，2 of the nth enterprise will be 0, and the rest will be 1. (2) f a,b is the actual flight hours (flight volume) of the enterprise, but is also related to x a,b . When x a,b is 0, it means that the bth flight item of the ath enterprise is not permitted and is 0. Therefore, f a,b is also 0. When x a,b is 1, it means that the bth flight item of the ath enterprise is permitted. The flight hours corresponding to this permitted item may be 0 or may not be 0, but as long as the enterprise has flown this item, f a,b must be greater than 0 hours. The optimization scheme for setting weights for parameters can further improve the accuracy of general aviation flight data processing.

[0064] In the embodiment of the present invention, in the process of matrix data processing, considering the characteristics of multi-dimension, wide data distribution, and uncertainty of general aviation flight data, the complex multi-dimensional data is transformed into a matrix form, and the multi-dimensional data is operated by using the properties of the matrix through matrix multiplication, which is convenient for data expression and improves the calculation efficiency of general aviation flight data.

[0065] In the above step 106, according to the flight types of general aviation enterprises in each operation area and the flight volume corresponding to each flight type, the flight service preference of general aviation enterprises in any operation area is determined.

[0066] In an embodiment of the present invention, the method for processing general aviation flight data may further include: determining the flight service preference of general aviation enterprises in any operation area or the flight service preference of general aviation enterprises in any regulatory agency jurisdiction according to the flight types of general aviation enterprises in each operation area and the flight volume corresponding to each flight type (the flight volume within the operation area or determined by the flight volume formula F of enterprises in the regulatory agency jurisdiction).

[0067] In an embodiment of the present invention, the method for processing general aviation flight data may further include: determining the flight service preference of general aviation enterprises in any management agency jurisdiction according to the flight service preference of general aviation enterprises in any regulatory agency jurisdiction, that is, accumulating the flight service preferences in all regulatory agency jurisdictions within the management agency jurisdiction to obtain the flight service preference of general aviation enterprises in any management agency jurisdiction.

[0068] In summary, the embodiment of the present invention discovers the internal correlation between multi-dimensional relationship data of general aviation flights and the flight service preference in the operation area, regulatory agency jurisdiction, or management agency jurisdiction. Among them, the flight service preference can be characterized by the flight volume corresponding to the flight type. The higher the flight volume corresponding to the flight type in the operation area, regulatory agency jurisdiction, or management agency jurisdiction, the higher the flight service preference. This solves the technical problem of how to improve the accuracy of analyzing the flight service preference of enterprises in the operation area, regulatory agency jurisdiction, or management agency jurisdiction, and obtains the technical effect of promoting the sustainable and healthy development of the aviation flight field.

[0069] To facilitate understanding of how the present invention is implemented, the following is combined with Figure 3 an example for illustration.

[0070] Taking Figure 3 as an example, there are 9 regulatory bureaus in the jurisdiction of the g1 administration. Then the flight volume types of enterprises in the jurisdiction of the j1 regulatory bureau are as follows: a total of three types of flight data, namely 1, 2, and 3. The first type of data is the flight of enterprises in the jurisdiction of the j1 regulatory bureau within its own jurisdiction. The second type of data is the flight of enterprises in the jurisdiction of the j1 regulatory bureau within the same administration jurisdiction but outside the jurisdiction of the j1 regulatory bureau. The third type of data is the flight of enterprises in the jurisdiction of the j1 regulatory bureau outside the jurisdiction of the g1 administration. Through such flight volume calculations, the activity level of enterprises in any regional jurisdiction and the distribution of flight volumes of regional enterprises can be analyzed, that is, the flight service preference of enterprises in any regional jurisdiction is determined.

[0071] Taking Figure 3For example, there are 9 regulatory bureaus in the jurisdiction of the g1 Administration. The types of flight volumes at the operating sites in the jurisdiction of the j1 Regulatory Bureau include a total of three types of flight data: 1, 4, and 5. The first type of data is the flight of enterprises in the jurisdiction of the j1 Regulatory Bureau within the jurisdiction of the j1 itself. The fourth type of data is the flight of enterprises in the same administration as j1 but in different regulatory bureaus within the jurisdiction of the j1. The fifth type of data is the flight of enterprises not in the jurisdiction of the same administration as j1 and not in the jurisdiction of the same regulatory bureau within the jurisdiction of the j1. Through such flight volume calculations, the general aviation tendency in any regional jurisdiction can be analyzed. From this, the flight volume activity of internal and external enterprises coming to this area for aerial operations can be analyzed, as well as the distribution volume of enterprises flying here at their registered locations and other situations.

[0072] Combined with Figure 3 Illustrate the three types of flight data, namely 1, 2, and 3, here. Figure 3 In the jurisdiction of the g1 Administration, there are a total of 9 regulatory bureaus. Among them, during the same period, the first type of data is that the flight hours of enterprises in the jurisdiction of the j1 Regulatory Bureau within the jurisdiction of the j1 Regulatory Bureau are 26,296.80 hours. The second type of data is the flight volume of enterprises in the jurisdiction of the j1 Regulatory Bureau within the jurisdiction of the g1 Administration but not within the jurisdiction of the j1 Regulatory Bureau, and this data is 6,296.32 hours. The third type of data is the flight volume of enterprises in the jurisdiction of the j1 Regulatory Bureau outside the jurisdiction of the g1 Administration, which is 7,416.42 hours. From this, it can be analyzed that 65.73% of the flight volume of enterprises in the jurisdiction of the j1 Regulatory Bureau occurs within the jurisdiction of the j1 Regulatory Bureau, 81.46% of the flight volume occurs within the jurisdiction of the g1 Administration, and 18.54% of the flight volume occurs outside the jurisdiction of the g1 Administration. From this, it is found that the general aviation flight volume in the jurisdiction of the g1 Administration and the jurisdiction of the j1 Regulatory Bureau is active, the tendency of enterprises in this area is high, the local operation tasks are mainly carried out by local enterprises, providing good flight resources and environment for local enterprises. At the same time, local enterprises have the ability and resources to undertake long-distance operation tasks outside the A Administration, that is, it is determined that the flight service tendency of general aviation enterprises in the jurisdiction of the A Administration and the jurisdiction of the A1 Regulatory Bureau is high.

[0073] The embodiments of the present invention can better and comprehensively analyze the distribution of flight data, and then can determine the flight service tendency of general aviation enterprises in any operating site, or determine the flight service tendency of general aviation enterprises in the jurisdiction of any regulatory agency, and further determine the flight service tendency of general aviation enterprises in the jurisdiction of any administrative agency, promoting the sustainable and healthy development of the aviation flight field.

[0074] In the embodiments of the present invention, a processing device for general aviation flight data is also provided, as described in the following embodiments. Since the principle of the device for solving problems is similar to the method for processing general aviation flight data, the implementation of the device can refer to the implementation of the method for processing general aviation flight data, and the repeated parts will not be elaborated.

[0075] Figure 4The following is a schematic structural diagram of a general aviation flight data processing device in an embodiment of the present invention. As Figure 4 shown, the device includes:

[0076] An acquisition unit 01, configured to acquire general aviation flight data;

[0077] A multi-dimensional relationship data determination unit 02, configured to obtain general aviation flight multi-dimensional relationship data according to the general aviation flight data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set;

[0078] A multi-dimensional relationship data image generation unit 03, configured to generate a general aviation flight multi-dimensional relationship data image according to the general aviation flight multi-dimensional relationship data;

[0079] A matrix conversion unit 04, configured to convert the general aviation enterprise set, the operation location set, and the operation item set into all enterprise operation item matrices within each operation location of general aviation flight according to the general aviation flight multi-dimensional relationship data image, and convert the general aviation enterprise set, the operation location set, and the flight volume data set into a flight volume matrix of all enterprises for each operation item of general aviation flight;

[0080] A flight type and flight volume determination unit 05, configured to determine the general aviation enterprise flight type within each operation location and the flight volume corresponding to each flight type according to all enterprise operation item matrices within each operation location of general aviation flight and the flight volume matrix of all enterprises for each operation item of general aviation flight;

[0081] A flight service propensity determination unit 06, configured to determine the flight service propensity of a general aviation enterprise within any operation location according to the general aviation enterprise flight type within each operation location and the flight volume corresponding to each flight type.

[0082] In one embodiment, the multi-dimensional relationship data further includes: a regulatory agency set, and each regulatory agency element in the regulatory agency set corresponds to the corresponding supervised operation location element in the operation location set;

[0083] The flight service propensity determination unit is further configured to: determine the flight service propensity of a general aviation enterprise within the jurisdiction of any regulatory agency according to the general aviation enterprise flight type within each operation location and the flight volume corresponding to each flight type.

[0084] In one embodiment, the multi-dimensional relationship data further includes: a set of management institutions, where each management institution element in the set of management institutions corresponds to the corresponding supervised operation site element in the set of operation sites. Any general aviation enterprise element in the set of general aviation enterprises uniquely corresponds to one regulatory agency element in the set of regulatory agencies. Any regulatory agency element in the set of regulatory agencies corresponds to at least one enterprise element in the set of general aviation enterprises. Any regulatory agency element in the set of regulatory agencies uniquely corresponds to one management institution element in the set of management institutions. Any management institution element in the set of management institutions corresponds to at least one regulatory agency element in the set of regulatory agencies;

[0085] The flight service propensity determination unit is further configured to: determine the flight service propensity of a general aviation enterprise within the jurisdiction of any management institution according to the flight service propensity of the general aviation enterprise within the jurisdiction of any regulatory agency.

[0086] In one embodiment, the above-mentioned processing device for general aviation flight data further includes: a data cleaning unit, which is used to perform data cleaning operations such as missing value processing, outlier processing, and redundant data removal processing on the collected general aviation flight data.

[0087] In one embodiment, the data cleaning unit is specifically configured to:

[0088] If any general aviation flight data item has a null value or missing data, delete the entire structured data corresponding to the general aviation flight data item with the null value or missing data to obtain the general aviation flight data after missing value processing;

[0089] For the general aviation flight data item after missing value processing where the flight volume is non-numeric, delete the entire structured data corresponding to the general aviation flight data item with non-numeric flight volume to obtain the general aviation flight data after outlier processing;

[0090] Identify and eliminate duplicate row data in the general aviation flight data after outlier processing to obtain the general aviation flight data after redundant data removal processing as the general aviation flight data after data cleaning operations.

[0091] In one embodiment, the acquisition unit is specifically configured to: obtain the general aviation flight data by parsing the structured flight data of the general aviation management system.

[0092] Based on the foregoing inventive concept, as Figure 5 shown, the present invention also proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, the foregoing method for processing general aviation flight data is implemented.

[0093] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the above method for processing general aviation flight data.

[0094] An embodiment of the present invention further provides a computer program product including a computer program, which when executed by a processor, implements the above method for processing general aviation flight data.

[0095] The general aviation flight data processing solution provided by the embodiment of the present invention includes: collecting general aviation flight data; obtaining multi-dimensional relationship data of general aviation flight based on the general aviation flight data; the multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set; generating a multi-dimensional relationship data image of general aviation flight based on the multi-dimensional relationship data of general aviation flight; converting the general aviation enterprise set, the operation location set, and the operation item set into an operation item matrix of all enterprises within each operation location of general aviation flight, and converting the general aviation enterprise set, the operation location set, and the flight volume data set into a flight volume matrix of each operation item of all enterprises in general aviation flight according to the multi-dimensional relationship data image of general aviation flight; determining the flight type of general aviation enterprises within each operation location and the flight volume corresponding to each flight type based on the operation item matrix of all enterprises within each operation location of general aviation flight and the flight volume matrix of each operation item of all enterprises in general aviation flight; and determining the flight service inclination of general aviation enterprises within any operation location based on the flight type of general aviation enterprises within each operation location and the flight volume corresponding to each flight type, so as to efficiently and accurately determine the flight service inclination of general aviation enterprises within any operation location.

[0096] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0098] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operating steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0100] The specific embodiments described above further elaborate on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing general aviation flight data, characterized in that Including: Collecting general aviation flight data; Obtaining multi-dimensional relationship data of general aviation flights based on the general aviation flight data; The multi-dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element in the operation item set and at least one operation location element in the operation location set, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set; Generating an image of multi-dimensional relationship data of general aviation flights based on the multi-dimensional relationship data of general aviation flights; According to the image of multi-dimensional relationship data of general aviation flights, converting the general aviation enterprise set, the operation location set, and the operation item set into a matrix of enterprise operation items within each operation location of general aviation flights, and converting the general aviation enterprise set, the operation location set, and the flight volume data set into a flight volume matrix of each operation item of all general aviation enterprises; Determining the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type according to the matrix of enterprise operation items within each operation location of general aviation flights and the flight volume matrix of each operation item of all general aviation enterprises; Determining the flight service inclination of general aviation enterprises within any operation location according to the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type; 2. The method according to claim 1, wherein The multi-dimensional relationship data further includes: a regulatory agency set, and each regulatory agency element in the regulatory agency set corresponds to the corresponding operation location element to be regulated in the operation location set; The processing method of the general aviation flight data further includes: determining the flight service inclination of general aviation enterprises within the jurisdiction of any regulatory agency according to the flight types of general aviation enterprises within each operation location and the flight volume corresponding to each flight type; 3. The method according to claim 2, wherein The multi-dimensional relationship data further includes: a management agency set, and each management agency element in the management agency set corresponds to the corresponding operation location element to be regulated in the operation location set. Any general aviation enterprise element in the general aviation enterprise set uniquely corresponds to one regulatory agency element in the regulatory agency set. Any regulatory agency element in the regulatory agency set corresponds to at least one enterprise element in the general aviation enterprise set. Any regulatory agency element in the regulatory agency set uniquely corresponds to one management agency element in the management agency set. Any management agency element in the management agency set corresponds to at least one regulatory agency element in the regulatory agency set; The processing method of the general aviation flight data further includes: determining the flight service inclination of general aviation enterprises within the jurisdiction of any management agency according to the flight service inclination of general aviation enterprises within the jurisdiction of any regulatory agency; 4. The method according to claim 1, wherein Also including: A data cleaning operation for processing missing values, outliers, and removing redundant data from the collected general aviation flight data.

5. The method according to claim 4, wherein The data cleaning operation for processing missing values, outliers, and removing redundant data from the collected general aviation flight data includes: If any general aviation flight data item has a null value or missing data, delete the entire structured data corresponding to the general aviation flight data item with the null value or missing data to obtain the general aviation flight data after missing value processing; For the general aviation flight data item after missing value processing where the flight volume is non - numeric, delete the entire structured data corresponding to the general aviation flight data item with non - numeric flight volume to obtain the general aviation flight data after outlier processing; Identify and eliminate duplicate row data in the general aviation flight data after outlier processing to obtain the general aviation flight data after redundant data removal processing as the general aviation flight data after data cleaning operations.

6. The method according to claim 1, characterized in that, Collecting general aviation flight data includes: obtaining the general aviation flight data by parsing the structured flight data of the general aviation management system.

7. A processing device for general aviation flight data, characterized in that, Including: A collection unit for collecting general aviation flight data; A multi - dimensional relationship data determination unit for obtaining general aviation flight multi - dimensional relationship data based on the general aviation flight data; The multi - dimensional relationship data includes: a general aviation enterprise set, an operation location set, an operation item set, and a flight volume data set, where: any enterprise element in the enterprise set corresponds to at least one operation item element and at least one operation location element in the operation item set and the operation location set respectively, and any operation item element in the operation item set corresponds to at least one enterprise element in the enterprise set; A multi - dimensional relationship data image generation unit for generating a general aviation flight multi - dimensional relationship data image based on the general aviation flight multi - dimensional relationship data; A matrix conversion unit for converting the general aviation enterprise set, the operation location set, and the operation item set into a matrix of all enterprise operation items within each operation location of general aviation flight according to the general aviation flight multi - dimensional relationship data image, and converting the general aviation enterprise set, the operation location set, and the flight volume data set into a flight volume matrix of all enterprises for each operation item of general aviation flight; A flight type and flight volume determination unit for determining the general aviation enterprise flight type within each operation location and the flight volume corresponding to each flight type according to the matrix of all enterprise operation items within each operation location of general aviation flight and the flight volume matrix of all enterprises for each operation item of general aviation flight; A flight service propensity determination unit for determining the flight service propensity of general aviation enterprises within any operation location according to the general aviation enterprise flight type within each operation location and the flight volume corresponding to each flight type.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer - readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by the processor, it implements the method according to any one of claims 1 to 6.

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