Earth synchronous orbit high-energy electron flux prediction method, prediction model construction method and prediction device

Abstract

The application provides a geosynchronous orbit high-energy electron flux prediction method, a model and a model construction method, and relates to the field of electron flux prediction; the geosynchronous orbit high-energy electron flux prediction method comprises the following steps: constructing a geosynchronous orbit high-energy electron flux prediction model; inputting the following parameters into the geosynchronous orbit high-energy electron flux prediction model: a time point T, spatial coordinates of a spatial point in a radiation belt, and average solar wind speed in a time range of [T-a hours, T-b hours]; calculating high-energy electron flux at the geosynchronous orbit height passing through the spatial point in a quiet period; judging whether the spatial point at the geosynchronous orbit height is in a storm time or not, and outputting high-energy electron flux at the geosynchronous orbit height passing through the spatial point in the quiet period or the storm time. The high-energy electron flux prediction method provided by the application can automatically switch the flux prediction mode in the quiet period or the storm time, and significantly improves the prediction accuracy under different geomagnetic activity conditions.

Description

Technical Field

[0001] This invention relates to the field of electron flux forecasting, specifically to a method, model, and model construction method for forecasting high-energy electron flux in geosynchronous orbit. Background Technology

[0002] The Earth's radiation belts are filled with high-energy charged particles trapped by the geomagnetic field. The flux of these particles varies with their spatial location and is disturbed during geomagnetic storms and substorms. Since the radiation belts coincide with the orbits of most satellites, these high-energy charged particles pose a serious threat to the safety of satellites and astronauts. Studies show that high-energy particle-induced satellite malfunctions account for 40% of all satellite failures. Therefore, establishing comprehensive predictive models for the distribution of high-energy particles in the radiation belts has always been a goal.

[0003] Currently, commonly used high-energy electron flux prediction models for the radiation belt fall into two categories. One category consists of simple static models, which were proposed earlier but have lower accuracy, such as NASA's AE-8 model. These models lack the ability to adjust forecast values ​​in real time based on space bursts, and therefore cannot provide effective radiation warnings for satellites and astronauts. The other category comprises physical models based on numerical simulations. While these models offer relatively accurate predictions, they consume significant computational resources, have numerous parameters, and require long execution times, hindering their widespread adoption. Therefore, we aim to establish a wide-area, dynamic empirical model for high-energy electron flux in the radiation belt based on actual observational data. This model would not only provide real-time radiation warnings but also be convenient and efficient. Summary of the Invention

[0004] Given that the existing technologies described above can only simulate electron flux during quiet periods or storms, this application provides a geosynchronous orbit high-energy electron flux prediction method and model that can autonomously switch between quiet period prediction and storm prediction, thereby improving the accuracy of electron flux prediction.

[0005] This invention provides a method for predicting high-energy electron flux in geosynchronous orbit, comprising:

[0006] Obtain existing electron flux data and construct a high-energy electron flux prediction model for geosynchronous orbit;

[0007] Input the following to the geosynchronous orbit high-energy electron flux prediction model: time point T, spatial coordinates of the spatial point in the radiation belt, and average solar wind velocity within the time range of [Ta hours, Tb hours], where a > b;

[0008] Calculate the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the time point T during a quiet period. ;

[0009] Input the average polar photocurrent index over the time range of [Tc minutes, T] into the geosynchronous orbit high-energy electron flux prediction model, where c≠0;

[0010] If the average polar photoelectric current collection index is less than 300 nT, during the quiet period, at time point T, the high-energy electron flux passing through the space point at the geosynchronous orbit altitude is... ;

[0011] If the average polar photocurrent index is greater than or equal to 300 nT, calculate and output the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the time point T during the burst. .

[0012] Optionally, during a quiet period, at time point T, the high-energy electron flux passing through the space point at the geosynchronous orbit altitude is calculated. Includes the following steps:

[0013] Determine the turning point energy ;

[0014] Determine the reference energy ;

[0015] Calculate the baseline energy of the point in space passing through geosynchronous orbit during a quiet period at the stated time point T. Electron flux :

[0016] ;

[0017] Calculate the flux of high-energy electrons passing through the space point at the geosynchronous orbit altitude at the time point T during a quiet period. :

[0018] ;

[0019] in, This represents the average solar wind speed. These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are normalized geomagnetic latitude values. The slope of the energy spectrum in the lower energy portion. The slope of the energy spectrum in the higher energy portion. α represents the transition energy of the energy spectrum, and α represents the sharpness of the transition energy.

[0020] Optionally, the high-energy electron flux passing through the space point at the geosynchronous orbit altitude during the burst is:

[0021] ;

[0022] in, ;

[0023] in, It refers to the flux during quiet periods under the same solar wind speed conditions and the same spatial coordinates. This is called the burst flux index growth rate. yes The point corresponding to the peak , For bias functions, is the amplitude function.

[0024] Optionally, the for: ;

[0025] in, and That is, the input spatial coordinates of the radiation zone.

[0026] Optionally, the bias function for: ;

[0027] The amplitude function for: ;

[0028] in, and These are the polynomial coefficients, determined by fitting the dataset used. It is a reference energy value used to make electron energy dimensionless.

[0029] Optionally, the reference energy =205 keV;

[0030] During a quiescent period, at the stated time point T, the flux of high-energy electrons passing through a point in space at the geosynchronous orbit altitude. for:

[0031] ;

[0032] in, This represents the average solar wind speed. These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are normalized geomagnetic latitude values. The slope of the energy spectrum in the lower energy portion. The slope of the energy spectrum in the higher energy portion. α represents the transition energy of the energy spectrum, and α represents the sharpness of the transition energy.

[0033] Another aspect of the present invention provides a method for constructing a high-energy electron flux prediction model for geosynchronous orbit, comprising:

[0034] A training database is constructed, which includes historical electron flux data, spatial coordinate data, solar wind speed, and auroral current collection index.

[0035] The design of the model architecture includes modules for predicting calm periods and storm events. The calm period prediction module is designed based on a down-flipping double-fold power-law spectrum and a spectral fitting function. To obtain a model of high-energy electron flux at any energy level during quiescent periods: The burst prediction module includes an exponentially increasing term Q superimposed on the flux during the quiescent period, and a high-energy electron flux module at any energy during the burst. ;

[0036] The calm period prediction module and the storm prediction module are trained based on the training database.

[0037] Optionally, the method further includes preprocessing the data in the training database, the preprocessing including:

[0038] Data cleaning, removing outliers from the training database;

[0039] Spatial coordinate normalization converts MLAT into normalized parameters. , .

[0040] Another aspect of the present invention provides a high-energy electron flux prediction model for geosynchronous orbit, comprising:

[0041] The data acquisition module acquires comprehensive electron flux data, solar wind speed, and auroral current index from geosynchronous orbit.

[0042] A training database is used to store the data acquired by the data acquisition module;

[0043] The comparison module is used to determine whether a spatial point at the geosynchronous orbit altitude is in a storm.

[0044] The high-energy electron flux prediction module for quiescent periods is used to calculate the high-energy electron flux at any energy during quiescent periods. The model for the high-energy electron flux at any energy during quiescent periods is as follows:

[0045] ;

[0046] in, ;

[0047] The high-energy electron flux prediction module during a burst is used to calculate the high-energy electron flux at any energy during a burst. The model for the high-energy electron flux at any energy during a burst is as follows:

[0048] ;

[0049] in, ;

[0050] The flux output module obtains and outputs the flux data predicted by the high-energy electron flux prediction module during the quiet period or the high-energy electron flux prediction module during the burst.

[0051] in, This represents the average solar wind speed. These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are normalized geomagnetic latitude values. The slope of the energy spectrum in the lower energy portion. The slope of the energy spectrum in the higher energy portion. This represents the transition energy of the energy spectrum, and α represents the sharpness of the transition energy. It refers to the flux during quiet periods under the same solar wind speed conditions and at the same spatial coordinates.

[0052] As described above, the geosynchronous orbit high-energy electron flux prediction method, model, and model construction method provided by this invention have at least the following beneficial technical effects:

[0053] The geosynchronous orbit high-energy electron flux prediction model of this invention can significantly improve the prediction accuracy under different geomagnetic activity conditions by automatically switching between a quiescent period flux prediction mode and a storm flux prediction mode by real-time monitoring of the auroral photocurrent index (AE index). This application integrates BeiDou satellite electron flux data, solar wind parameters, AE index and other data, and periodically incorporates new observation data to refit the model parameters to ensure the accuracy of the prediction stage. Attached Figure Description

[0054] Figure 1 The flowchart shown is for implementing the high-energy electron flux prediction method for geosynchronous orbit provided by Implementation 1.

[0055] Figure 2 The flowchart shown is a method for constructing a geosynchronous orbit high-energy electron flux prediction model provided in Example 2.

[0056] Figure 3 The diagram shown is a schematic representation of the composition of the geosynchronous orbit high-energy electron flux prediction model provided in Example 3.

[0057] Figure 4The figure shown is a comparison of the prediction results of the geosynchronous orbit high-energy electron flux prediction model provided in Example 3 with the prediction results of existing technology models. Detailed Implementation

[0058] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0059] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of the present invention. Although the illustrations only show components related to the present invention and are not drawn according to the actual number, shape and size of the components, the shape, quantity, positional relationship and proportion of each component can be arbitrarily changed under the premise of realizing the technical solution of this invention, and the layout of the components may also be more complex.

[0060] Example 1

[0061] This embodiment provides a method for predicting high-energy electron flux in geosynchronous orbit, such as... Figure 1 The diagram shows a flowchart of the geosynchronous orbit high-energy electron flux prediction method provided in this embodiment. The geosynchronous orbit high-energy electron flux prediction method provided in this embodiment includes: acquiring existing electron flux data, storing it in a training database, and constructing a geosynchronous orbit high-energy electron flux prediction model; inputting the following into the geosynchronous orbit high-energy electron flux prediction model: time point T, spatial coordinates of the radiation belt, and the average solar wind velocity within the time range of [Ta hours, Tb hours], where a > b; calculating the high-energy electron flux at the geosynchronous orbit altitude at time point T during a quiet period. Input the average polar photocurrent index over the time range of [Tc min, T] into the geosynchronous orbit high-energy electron flux prediction model, where c ≠ 0; if the average polar photocurrent index is less than 300 nT, output the high-energy electron flux at the geosynchronous orbit altitude during the quiet period. If the average polar photocurrent index is greater than or equal to 300 nT, calculate and output the high-energy electron flux at the geosynchronous orbit altitude at the time point T during the storm period. .

[0062] Specifically, S1: Obtain existing electron flux data, store it in the training database, and construct a high-energy electron flux prediction model for geosynchronous orbit;

[0063] Specifically, existing electron flux data includes: high-energy electron flux data, solar wind velocity data, and auroral photocurrent index (AE index). High-energy electron flux data is acquired using the Peking University Imaging Electron Spectrometer (BD-IES) on a BeiDou inclined geosynchronous orbit satellite. Specifically, the satellite's orbital inclination is 55°, its period is 24 hours, and its altitude is approximately 37,000 km (5.8 km above the Earth's surface). , The Earth's radius), the BD-IES carried by the BeiDou satellite can measure electron flux of 50-600 keV (kiloelectron volts), and its field of view is... Energy resolution In this embodiment, we use omnidirectional average electron flux data provided by BD-IES, specifically covering eight energy levels in the range of 50-600 keV; solar wind speed data can be obtained from the ACE satellite or related space weather monitoring services; and the AE index can be obtained from NOAA / SWPC (National Oceanic and Atmospheric Administration / Space Weather Prediction Center) space weather parameter reports or other related monitoring services.

[0064] Optionally, new observational data can be periodically added to the training database to keep the data in the training database updated regularly and ensure the accuracy of the forecast results.

[0065] Specifically, a high-energy electron flux prediction model for geosynchronous orbit is constructed based on data from the training database. For details on the construction method, please refer to Embodiment 2 of this application; it will not be repeated here.

[0066] Specifically, S2: Input the following to the geosynchronous orbit high-energy electron flux prediction model: time point T, spatial coordinates of the spatial point in the radiation belt, and average solar wind speed within the time range of [Ta hours, Tb hours], where a > b.

[0067] Generally, time point T represents the current moment and is used to mark the target time for forecasting. The geosynchronous orbit high-energy electron flux forecasting method provided in this embodiment integrates historical and real-time data to dynamically output the high-energy electron flux at the geosynchronous orbit altitude at a specific radiation spatial coordinate at the current moment T. Specifically, the spatial point in the radiation belt includes: Magnetic Local Time (MLT) and Magnetic Latitude (MLAT). Generally, Magnetic Local Time (MLT) and Magnetic Latitude (MLAT) can be obtained by converting geographical latitude and longitude into geomagnetic coordinate system parameters through the International Geomagnetic Reference Field Model (IGRF) or the T89 magnetic field model, or by directly obtaining geomagnetic parameters through satellites carrying geomagnetic field detectors, or by obtaining data from databases such as ground magnetic measurement data and space weather services. Specifically, the mean solar wind speed ( Let be the average solar wind velocity over the time range of [Ta hours, Tb hours], where a is greater than b. Specifically, since it takes about 1-3 days for the solar wind to travel from the Sun to the Earth's magnetosphere, the selection of the time window needs to match the delay effect of solar wind disturbances on electrons in the radiation belts. Specifically, this embodiment uses the average solar wind velocity over the range of [T-25 hours, T-15 hours]. (This is to capture the cumulative compression effect of the high-speed solar wind on the magnetosphere.)

[0068] Specifically, S3: Calculate the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the time point T during the quiet period. Specifically, it includes the following steps:

[0069] S31, Determine the turning point energy According to BD-IES energy electron observation data, the electron spectrum at geosynchronous orbital altitude during quiet periods is primarily a downward double power-law (DDPL) spectrum, satisfying a generalized spectral fitting function. Based on data fitting from the training database, the transition energy can be determined. , This is the critical point where the slope of the energy spectrum changes significantly. Specifically, in this embodiment, it is used as... As the critical point for the change in the slope of the energy spectrum.

[0070] S32, Determine the reference energy Choose one that is closer to the turning point energy. The energy is the reference energy. To ensure reference energy The flux value affects the shape parameter of the energy spectrum ( The sensitivity of the data is relatively high, allowing for more effective determination of these parameters through data fitting. Specifically, in this embodiment, 205 keV is selected as the reference energy.

[0071] S33, calculates the baseline energy passing through a point in space on a geosynchronous orbit at time T during a calm period. Electron flux .

[0072] Specifically, (1);

[0073] in, These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are the normalized geomagnetic latitude values:

[0074] (2);

[0075] In equation (2) and That is, the input radiation zone spatial coordinates are all obtained from the training database; Then, with normalized geomagnetic latitude values Relationships with quadratic functions:

[0076] (3);

[0077] Among them, parameters All were determined by fitting the dataset used.

[0078] Specifically, in this embodiment, during a quiet period, at time point T, the flux of high-energy electrons with an energy of 205 keV passing through the space point at the geosynchronous orbit altitude is... for:

[0079] .

[0080] in, The fit can be determined based on the training dataset. And, parameters All were determined by fitting the dataset used.

[0081] S34: Calculate the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the said time point T during a quiet period.

[0082] The electron spectrum at the geosynchronous orbital altitude during quiescent periods satisfies a generalized spectral fitting function, which is:

[0083] (4);

[0084] It can be considered that the electron flux of a reference energy electron passing through a space point in geosynchronous orbit is... The flux of high-energy electrons passing through a point in space at the altitude of geosynchronous orbit At different energy points on the same energy spectrum function The values ​​of E and E are two independent observations from the same distribution. According to the spectral fitting function, their ratio can be expressed as:

[0085] (5);

[0086] By performing a simple transformation on equation (5), we can obtain the flux of high-energy electrons passing through the space point at the geosynchronous orbit altitude. :

[0087] (6).

[0088] Specifically, in this embodiment, during a quiet period, at time point T, the flux of high-energy electrons passing through a space point at the geosynchronous orbit altitude. for:

[0089] .

[0090] in, This represents the average solar wind speed. These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are normalized geomagnetic latitude values. The slope of the energy spectrum in the lower energy portion. The slope of the energy spectrum in the higher energy portion. α represents the transition energy of the energy spectrum, and α represents the sharpness of the transition energy.

[0091] Specifically, S4: Input the average polar photocurrent index over the time range of [Tc minutes, T] into the geosynchronous orbit high-energy electron flux prediction model, where c≠0.

[0092] Generally, the AE index is an indicator that measures the intensity of auroral photocurrent activity and is crucial for assessing the impact of geomagnetic disturbances on the high-energy electron flux of the radiation belt. This invention uses the AE index to determine whether the geomagnetic activity is in a calm period or a storm at the current time T.

[0093] Specifically, the time range [Tc minutes, T] for calculating the average AE exponent is not a fixed interval. The window length c needs to match the physical timescale of electron acceleration. If the window is too short (e.g., c=10 minutes), the cumulative effect of the acceleration process may be missed; if it is too long (e.g., c=6 hours), outdated signals may be introduced. Specifically, in this embodiment, c=30 minutes is selected.

[0094] People generally use an AE index greater than or equal to 300 nT as the standard for the occurrence of a geomagnetic substorm. When the average input AE index is less than 300 nT, geomagnetic activity is considered to be in a calm period; when the average input AE index is greater than or equal to 300 nT, geomagnetic activity is considered to be in a storm.

[0095] Specifically, S5: If the average polar photoelectric current collection index is less than 300 nT, during the quiet period, at time point T, the high-energy electron flux passing through the space point at the geosynchronous orbit altitude is... .

[0096] Specifically, S6: If the average polar photoelectric current collection index is greater than or equal to 300 nT, calculate and output the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the time point T during the burst. .

[0097] Specifically, the high-energy electron flux passing through the aforementioned space point at the geosynchronous orbit altitude during a storm is considered to have increased compared to the calm period. The relationship between the high-energy electron flux passing through the aforementioned space point at the geosynchronous orbit altitude during a storm and during a calm period is as follows:

[0098] (7);

[0099] in, (8);

[0100] in, It refers to the flux during quiet periods under the same solar wind speed conditions and the same spatial coordinates. This is called the burst flux exponential growth rate, parameter yes The point corresponding to the peak Bias function and amplitude function Both are related to electron energy Related to the AE exponent, the function is expressed as a bivariate quadratic polynomial, i.e.:

[0101] (9);

[0102] (10);

[0103] in, and These are the polynomial coefficients, determined by fitting the dataset used. It is a reference energy value used to make electron energy dimensionless.

[0104] The geosynchronous orbit high-energy electron flux prediction method provided in this embodiment uses real-time updated solar wind parameters and auroral current collection index as input parameters to predict the high-energy electron flux at any spatial location at any given moment.

[0105] Example 2

[0106] This embodiment provides a method for constructing a high-energy electron flux prediction model for geosynchronous orbit, such as... Figure 2 The diagram shows a flowchart of the method for constructing a geosynchronous orbit high-energy electron flux prediction model provided in this embodiment; it includes the following steps:

[0107] S1: Construct a training database, which includes historical electron flux data, spatial coordinate data, solar wind speed, and auroral current collection index;

[0108] S2: Design the model architecture, including designing a calm period prediction module and a storm prediction module; the calm period prediction module includes a down-flipping double-fold power-law spectrum and a generalized fitting function. To obtain a model of high-energy electron flux at any energy level during quiescent periods: The burst prediction module includes an exponentially increasing term Q superimposed on the flux during the quiescent period, and a high-energy electron flux module at any energy during the burst. ;

[0109] S3: Train the calm period prediction module and the storm prediction module based on the training database.

[0110] Specifically, S1: Constructing a training database, which includes historical electron flux data, spatial coordinate data, solar wind speed, and auroral current index. This includes steps such as data collection, constructing the training database, and data preprocessing.

[0111] Data sources include: historical electron flux data obtained from the omnidirectional average electron flux data in the range of 50-600 keV acquired by the Imaging Electron Spectrometer (BD-IES) carried by the BeiDou satellite; spatial coordinate data (magnetic local time (MLT) and geomagnetic latitude (MLAT)) converted from the International Geomagnetic Reference Field Model (IGRF) or direct satellite detection data; solar wind speed obtained from solar wind monitoring satellites such as ACE and DSCOVR; and auroral photocurrent index (AE index): calculated based on real-time magnetic field measurement data from a global geomagnetic station network.

[0112] Building the database involves storing data in a tabular database, specifically including time, MLT, MLAT, flux for each energy level, etc. Fields such as AE index.

[0113] Data preprocessing includes data cleaning, removing outliers from the training database; and spatial coordinate normalization, converting MLAT into normalized parameters. , It also includes feature extraction: extracting solar wind speed and AE index within a specific time period.

[0114] Specifically, S2: Design the model architecture, including designing the prediction module for calm periods and the prediction module for storm periods.

[0115] Specifically, a quiet period prediction module was designed. Based on BD-IES energy electron observation data, it was shown that the electron spectrum at the geosynchronous orbit altitude during quiet periods is primarily a downward double power-law (DDPL) spectrum, satisfying a generalized spectral fitting function. The specific steps include:

[0116] First, determine the transition energy based on the data fitting in the training database. , It is the critical point at which the slope of the energy spectrum changes significantly.

[0117] Second, choose one that is closer to the turning point energy. The energy is the reference energy. To ensure reference energy The flux value affects the shape parameter of the energy spectrum ( The sensitivity of the data is high, and these parameters can be determined more effectively through data fitting.

[0118] Third, calculate the baseline energy of the point in space passing through the geosynchronous orbit during the quiet period, at the stated time point T. Electron flux .

[0119] Specifically, (1);

[0120] in, These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are the normalized geomagnetic latitude values:

[0121] (2);

[0122] In equation (2) and That is, the input radiation zone spatial coordinates are all obtained from the training database; Then, with normalized geomagnetic latitude values Relationships with quadratic functions:

[0123] (3);

[0124] Among them, parameters All were determined by fitting the dataset used.

[0125] Fourth, calculate the high-energy electron flux passing through the space point at the geosynchronous orbit altitude at the time point T during a quiet period. During periods of relative calm, the electron spectrum at the geosynchronous orbit altitude satisfies a generalized spectral fitting function, which is:

[0126] (4);

[0127] It can be considered that the electron flux of a reference energy electron passing through a space point in geosynchronous orbit is... The flux of high-energy electrons passing through a point in space at the altitude of geosynchronous orbit At different energy points on the same energy spectrum function The values ​​of E and E are two independent observations from the same distribution. According to the spectral fitting function, their ratio can be expressed as:

[0128] (5);

[0129] By performing a simple transformation on equation (5), we can obtain the flux of high-energy electrons passing through the space point at the geosynchronous orbit altitude. :

[0130] (6).

[0131] Specifically, a storm prediction module is designed.

[0132] The high-energy electron flux passing through the aforementioned space point at the geosynchronous orbit altitude during a storm is considered to have increased compared to the calm period. The relationship between the high-energy electron flux passing through the aforementioned space point at the geosynchronous orbit altitude during a storm and during a calm period is as follows:

[0133] (7);

[0134] in, (8);

[0135] in, It refers to the flux during quiet periods under the same solar wind speed conditions and the same spatial coordinates. This is called the burst flux exponential growth rate, parameter yes The point corresponding to the peak Bias function and amplitude function Both are related to electron energy Related to the AE exponent, the function is expressed as a bivariate quadratic polynomial, i.e.:

[0136] (9);

[0137] (10);

[0138] in, and These are the polynomial coefficients, determined by fitting the dataset used. It is a reference energy value used to make electron energy dimensionless.

[0139] Specifically, S3: Train the calm period prediction module and the storm prediction module based on the training database.

[0140] Optionally, the calm-period prediction module or the storm prediction module can be trained in stages. The model polarity is trained based on data from the training database. Optionally, the calm-period prediction module can be trained first, its parameters fixed, and then the storm prediction module trained. Specifically, training methods include using error analysis combined with adjusting the coefficient of determination. Evaluate the goodness of fit.

[0141] Specifically, it also includes a model selection module. By comparing the magnitude of the input average auroral current index, it determines whether a spatial point at geosynchronous orbit altitude is in a storm phase, and then selects whether to use the calm period module or the storm phase module for calculation. Generally, the AE index is evaluated to determine whether the geomagnetic activity at the current time T is in a calm period or a storm phase. Specifically, an AE index greater than or equal to 300 nT is usually used as the standard for the occurrence of a geomagnetic substorm. When the input average AE index is less than 300 nT, the geomagnetic activity is considered to be in a calm period; when the input average AE index is greater than or equal to 300 nT, the geomagnetic activity is considered to be in a storm phase. Optionally, the specific judgment value can be adjusted according to the actual situation.

[0142] Optionally, methods for constructing geosynchronous orbit high-energy electron flux prediction models also include model integration and implementation deployment. This involves integrating the calm period prediction module and the storm prediction module into a single interface, allowing real-time input of MLT, MLAT, and other parameters. The AE index outputs the total energy flux forecast.

[0143] The method for constructing a geosynchronous orbit high-energy electron flux prediction model provided in this embodiment, combined with data fusion and dynamic mode conversion, achieves high-precision and low-delay prediction of geosynchronous orbit high-energy electron flux. Compared with traditional static models, the model achieves accurate dynamic prediction of radiation belt electrons while ensuring computational efficiency.

[0144] Example 3

[0145] This embodiment provides a high-energy electron flux prediction model for geosynchronous orbit, such as... Figure 3 The diagram shown illustrates the components of the geosynchronous orbit high-energy electron flux prediction model provided in this embodiment. The model includes a data acquisition module for acquiring electron flux data, solar wind speed, and auroral current index across the entire geosynchronous orbit; a training database for storing the data acquired by the data acquisition module; a comparison module for determining whether a spatial point at the geosynchronous orbit altitude is experiencing a burst; and a high-energy electron flux prediction module for quiet periods for calculating the high-energy electron flux at any energy level during quiet periods. The high-energy electron flux model for any energy level during quiet periods is as follows:

[0146] ;

[0147] in, ;

[0148] The high-energy electron flux prediction module during a burst is used to calculate the high-energy electron flux at any energy during a burst. The model for the high-energy electron flux at any energy during a burst is as follows:

[0149] ;

[0150] in, ;

[0151] The flux output module obtains and outputs the flux data predicted by the high-energy electron flux prediction module during the quiet period or the high-energy electron flux prediction module during the burst.

[0152] in, This represents the average solar wind speed. These are the coefficients of a bivariate quadratic polynomial, determined by fitting the dataset used. These are normalized geomagnetic latitude values. The slope of the energy spectrum in the lower energy portion. The slope of the energy spectrum in the higher energy portion. This represents the transition energy of the energy spectrum, and α represents the sharpness of the transition energy. It refers to the flux during quiet periods under the same solar wind speed conditions and at the same spatial coordinates.

[0153] like Figure 4 The diagram shown is a comparison of the prediction results of the geosynchronous orbit high-energy electron flux prediction model provided in this embodiment with the prediction results of the existing AE-8 max model. Figure 4 The red dots represent the prediction results of the existing AE-8 max model, while the black dots represent the prediction results of the geosynchronous orbit high-energy electron flux prediction model provided in this embodiment. Figure 4 The horizontal axis represents the observed electron flux, and the vertical axis represents the model-predicted electron flux. According to... Figure 4 It can be seen that the closer the electron flux predicted by the model is to the actual observed electron flux, the more concentrated the predicted flux is on both sides of the diagonal.

[0154] Specifically, in this embodiment, the following is used: (Adjusted Coefficient of Determination) Quantitatively evaluates the goodness of fit of the model:

[0155] (10);

[0156] in, It is the sample size. It is the number of parameters in the model. These are actual observed values. It is the average of the observed values. These are the model's predicted values. The closer to 1, the better the forecast.

[0157] Depend on Figure 4 It can be seen that the geosynchronous orbit high-energy electron flux prediction model provided in this embodiment... The existing model AE-8 max It can be seen that the model provided in this embodiment... The value is closer to 1, therefore the prediction results of the geosynchronous orbit high-energy electron flux prediction model provided in this embodiment are more accurate.

[0158] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for geosynchronous orbit high-energy electron flux forecast, characterized by, Comprising: Obtaining existing electron flux data, constructing a geosynchronous orbit high-energy electron flux prediction model; Inputting the following to the geosynchronous orbit high-energy electron flux prediction model: time point T, spatial coordinates of the spatial point in the radiation belt, average solar wind speed in the [T-a hours, T-b hours] time range, where a>b; calculating the flux of high-energy electrons at the geosynchronous orbit altitude passing through the space point at the time point T in a quiet period where E is the energy of the high-energy electron to be predicted; Inputting the following to the geosynchronous orbit high-energy electron flux prediction model: average auroral current collection index in the [T-c minutes, T] time range, where c≠0; if said average auroral electrojet current index is less than 300 nT, output a period of calm, at said point in time T, the flux of high energy electrons at geosynchronous orbit altitudes passing through said space point ; wherein the flux of high-energy electrons passing through said space point at geosynchronous orbit altitude at said time point T is calculated comprising the steps of determining a break energy ; determining a reference energy ; calculating the reference energy of high-energy electrons passing through said space point at geosynchronous orbit altitude at said time point T during a quiet period flux of electrons : ; calculating the flux of high-energy electrons passing through said space point at geosynchronous orbit altitude at said time point T during a quiet period : ; wherein denotes the average solar wind speed, is a binary quadratic polynomial coefficient determined by fitting to the data set used, is a normalized geomagnetic latitude value, is the energy spectrum slope of the lower energy portion, is the energy spectrum slope of the higher energy portion, denotes the break energy of the energy spectrum, and a denotes the sharpness of the break energy; if the average auroral electrojet current index is greater than or equal to 300 nT, calculating and outputting a storm time, at which time point T, the flux of high-energy electrons passing through the space point at geosynchronous orbit altitude ; ； wherein ; where E is the energy of the high-energy electron to be predicted, is the flux of high-energy electron at the same solar wind speed condition, the same spatial coordinate, and the quiet period, is the flux exponential growth rate during the storm, AE is the auroral electrojet index, and MLT is the magnetic local time, is is the corresponding , is the bias function, is the amplitude function, and Q(E, AE, MLT) represents that Q is a physical quantity determined by E, AE, and MLT.

2. The geosynchronous orbit high-energy electron flux forecast method according to claim 1, characterized by, The To: ; wherein, is the magnetic local time, is the magnetic latitude.

3. The geosynchronous orbit high-energy electron flux prediction method of claim 1, wherein, The bias function is: ; The amplitude function is: ; wherein, and are polynomial coefficients determined by fitting to the data set used, is a reference energy value used to non-dimensionalize the electron energy.

4. The geosynchronous orbit high-energy electron flux prediction method of claim 1, wherein, the reference energy = 205 keV; The flux of high-energy electrons passing through the space point at geosynchronous orbit altitude at the time point T in the quiet time is: ； where, denotes the average solar wind speed, is a binary quadratic polynomial coefficient determined by fitting to the data set used, is the normalized geomagnetic latitude value, is the spectral slope of the lower energy part, is the spectral slope of the higher energy part, denotes the break energy of the spectrum, and a denotes the sharpness of the break energy.

5. A method for constructing a geosynchronous orbit high-energy electron flux forecast model, characterized by, Comprising: Constructing a training database, the training database comprising historical electron flux data, spatial coordinate data, solar wind speed, and auroral current collection index; Designing a model architecture, including designing a quiet time prediction module and a flare time prediction module; the quiet time prediction module includes fitting functions based on a downward double power law spectrum and a general spectrum , obtaining a high-energy electron flux model at any energy in the quiet time: ; the flare time prediction module includes superimposing an exponential growth term Q on the quiet time flux, a high-energy electron flux model at any energy in the flare time: ; Training the quiet-time prediction module and the storm-time prediction module based on the training database; where E is the energy of the high-energy electron to be predicted, E a is a reference energy, E b is a turning energy of the energy spectrum, is a slope of the energy spectrum in a lower energy portion, is a slope of the energy spectrum in a higher energy portion, and α indicates a sharpness of the turning energy.

6. The method of constructing a geosynchronous orbit high-energy electron flux forecast model according to claim 5, wherein, Further comprising preprocessing the data in the training database, the preprocessing comprising: Data cleaning, excluding outliers in the training database; Spatial coordinates normalization, converting MLAT to normalized parameters , wherein, is the magnetic local time, is the magnetic latitude.

7. A geosynchronous orbit high energy electron flux forecasting device characterized by, Comprising: A data acquisition module that acquires electron flux data, solar wind speed, and auroral current collection index covering all directions in the geosynchronous orbit; A training database for storing the data acquired by the data acquisition module; A comparison module for determining whether a spatial point at a geosynchronous orbit height is in a storm time; A quiet-time high-energy electron flux prediction module for calculating high-energy electron flux at any energy in a quiet time, the high-energy electron flux model at any energy in a quiet time being: ， The flux of high-energy electrons passing a point in space at geosynchronous orbit altitudes when Ea = 205 keV is: ； wherein ; A storm-time high-energy electron flux prediction module for calculating high-energy electron flux at any energy in a storm time, the high-energy electron flux model at any energy in a storm time being: ； wherein ; A flux output module for obtaining and outputting the flux data predicted by the quiet-time high-energy electron flux prediction module or the storm-time high-energy electron flux prediction module; where E is the energy of the high-energy electron to be predicted, denotes the average solar wind speed, is a binary quadratic polynomial coefficient determined by fitting the data set used, AE is the auroral electron current collection index, and MLT is the magnetic local time, is the normalized geomagnetic latitude value, is the energy spectrum slope of the lower energy part, is the energy spectrum slope of the higher energy part, denotes the turning energy of the energy spectrum, and a denotes the sharpness of the turning energy, is the flux of high-energy electrons in the quiet period at the same solar wind speed condition and the same spatial coordinates, is the flux index growth rate during the storm, is the corresponding , is a bias function, is an amplitude function, and Q(E, AE, MLT) indicates that Q is a physical quantity determined by E, AE, and MLT.

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