1. The method for selecting the optimal frequency of the flash bird repelling based on the simulated annealing algorithm is characterized by comprising the following steps of:

s1, driving birds based on the flash bird driving equipment under the preset initial flash frequency, and obtaining the relative distance of the birds driven under the preset initial flash frequency, wherein the relative distance is the difference between the distance of the birds relative to the position of the flash bird driving equipment in the preset time after the flash driving is started and the distance of the birds relative to the position of the flash bird driving equipment before the flash driving is started, and when the birds are successfully driven, the relative distance is larger than 0;

s2, forming a pair of mapping data by the preset initial flashing frequency and the relative distance, and storing the mapping data into a mapping database;

s3, adjusting the preset initial flashing frequency, and repeating the steps S1-S2 until the logarithm of the mapping data in the mapping database reaches a preset logarithm;

s4, fitting the mapping data in the mapping database based on a least square method to form a fitting curve, and obtaining a fitting curve function;

s5, calculating the fitting curve function based on a simulated annealing algorithm to obtain the optimal flashing frequency;

and S6, replacing the preset initial flashing frequency with the optimal flashing frequency, applying the optimal flashing frequency to the flashing bird repelling device, and repeating the steps S1-S6 so as to continuously and iteratively replace the flashing frequency of the flashing bird repelling device.

2. The method for selecting the optimal frequency for flashing bird repelling based on the simulated annealing algorithm according to claim 1, wherein the step S1 is preceded by: selecting the preset initial flashing frequency specifically comprises the following steps: the preset initial flashing frequency is selected according to a probability density function meeting normal distribution or selected according to historical flashing frequency data.

3. The method for selecting the optimal frequency for flashing and bird repelling based on the simulated annealing algorithm according to claim 1, wherein the step of adjusting the preset initial flashing frequency in the step S3 specifically comprises:

updating the preset initial flashing frequency according to the following formula,

f1＝f0+(-1)^vγ(θ)

where f1 denotes the flash frequency after update, f0 denotes the flash frequency before update, v is a random number of 1 or 2, γ (θ) denotes a value range of (f0, θ)_max-f0]Wherein θ is_max represents the maximum flashing frequency of the flashing bird repellent device.

4. The method for selecting the optimal frequency for flashing bird repelling according to the simulated annealing algorithm as claimed in claim 1, wherein the fitted curve function in the step S4 is,

f(x)＝a₁α₁(x)+a₂α₂(x)+...+a_nα_n(x)

in the formula, alpha_k(k) N is a set of linearly independent functions, a_kk 1, 2, n represents a pending coefficient;

assume that the mapped data point value to be fitted is y_i1, 2.. n, then the mapped data point values y to be fitted are fitted_iThe sum of the squares of the distances to the fitted curve function f (x) is minimal, and the corresponding fitted curve function f (x) is the best fitted curve function.

5. The method for selecting the optimal frequency for flashing bird repelling based on the simulated annealing algorithm according to claim 1, wherein the step S5 specifically comprises:

s501, initializing parameters of a simulated annealing algorithm, assuming that the initial temperature of the simulated annealing is T, the lowest temperature of the simulated annealing is T _ min, and the maximum iteration number is L;

s502, randomly generating an initial solution theta in a solution space, and calculating a function value f (theta) of the fitting curve function according to the initial solution theta;

s503, applying disturbance to the initial solution to generate a new solution theta ', and calculating a function value f (theta ') of the fitted curve function according to the new solution theta ';

s504, calculating a difference between the function value f (θ) of the fitted curve function and the function value f (θ ') of the fitted curve function, where Δ f is f (θ) -f (θ'), and Δ f represents the difference;

s505, judging whether the difference delta f is smaller than 0, if so, accepting the new solution theta ', and if not, judging whether accepting the new solution theta' according to Metropolis criterion;

s506, if the new solution theta ' is accepted, the new solution theta ' is taken as the current solution, and if the new solution theta ' is not accepted, the initial solution theta is taken as the current solution;

s507, according to the current solution serving as an initial solution of the next iteration, repeating the steps S502-S507 to perform iterative calculation, continuously iterating for N times in the iteration process, and if the generated new solutions are accepted, reducing the current temperature of the simulated annealing, wherein N is less than L;

s508, judging whether an iteration ending condition is met, if not, reducing the current temperature of the simulated annealing until the current temperature of the simulated annealing reaches the lowest temperature T _ min of the simulated annealing and iteration is ended or until the iteration times reaches the maximum iteration times L, and outputting a new solution obtained by the last iteration as the optimal flash frequency, wherein the reduction of the current temperature of the simulated annealing meets a temperature attenuation function, and the temperature attenuation function is T_k+1＝αT_k，T_kTemperature at time k, T_k+1The temperature at the time k +1, α represents the temperature cooling coefficient, α ∈ (0.95, 0.99).

6. The method for selecting the optimal frequency for flashing bird repelling based on the simulated annealing algorithm as claimed in claim 5, wherein the step of applying the perturbation to the initial solution to generate the new solution θ' in step S503 specifically comprises:

s5031, taking the initial solution as an initial point, and generating a new solution along a gradient reverse direction by adopting a steepest descent method;

s5032, if the generated new solution is not accepted, decreasing the step size of the gradient descent returns to step S5031 for recalculation, wherein the step size may be determined by a one-dimensional optimization method.

7. The method for selecting the optimal frequency for flashing bird repelling based on the simulated annealing algorithm as claimed in claim 5, wherein the step of judging whether to accept the new solution θ' according to Metropolis criterion in step S505 specifically comprises:

when the initial temperature of the simulated annealing is T, calculating the internal energy of the initial solution and the new solution, and if the internal energy satisfies E_j＜E_iAccepting the new solution, wherein E_i、E_jRespectively representing the internal energy of the initial solution and the internal energy of the new solution; if not satisfying E_j＜E_iAccording to a probability formulaWhether the solution is larger than the random number in the interval of [0,1), if the judgment is yes, the new solution is accepted, and if the judgment is no, the new solution is not accepted, wherein p represents the solution of the probability formula, and K represents the self-defined parameter.

8. The flash bird repelling optimal frequency selection system based on the simulated annealing algorithm is used for executing the flash bird repelling optimal frequency selection method based on the simulated annealing algorithm, and is characterized by comprising a relative distance module, a mapping module, a flash frequency adjusting module, a fitting module, a simulated annealing module and a frequency replacing module;

the relative distance module is used for acquiring the relative distance of birds driven under the preset initial flashing frequency based on the flashing bird driving equipment under the preset initial flashing frequency, the relative distance is the difference between the distance of the birds relative to the position of the flashing bird driving equipment in the preset time after the flashing driving is started and the distance of the birds relative to the position of the flashing bird driving equipment before the flashing driving is started, and when the birds are driven successfully, the relative distance is larger than 0;

the mapping module is used for forming a pair of mapping data by the preset initial flashing frequency and the relative distance and storing the mapping data into a mapping database;

the flash frequency adjusting module is used for adjusting the preset initial flash frequency;

the fitting module is used for fitting the mapping data in the mapping database based on a least square method to form a fitting curve so as to obtain a fitting curve function;

the simulated annealing module is used for calculating the fitting curve function based on a simulated annealing algorithm to obtain the optimal flash frequency;

the frequency replacing module is used for replacing the preset initial flashing frequency with the optimal flashing frequency and applying the optimal flashing frequency to the flashing bird repelling device.

Background

Because birds frequently move on the power transmission line to bring certain harm to the safe operation of the power transmission line, the line fault frequency brought by the birds is higher and higher.

Most of existing bird repelling equipment is installed on a transmission tower, and birds are repelled to be away from a transmission area through modes of flashing, sound, visual stimulation and the like. The flashing frequency of the existing flashing bird repelling device is fixed and unchanged, and birds have certain adaptability to the flashing frequency, so that the effectiveness of repelling the birds is greatly reduced, and line faults are easy to occur.

Disclosure of Invention

The application provides a method and a system for selecting optimal flashing bird-repelling frequency based on a simulated annealing algorithm, which are used for solving the technical problem that the effectiveness of bird repelling is greatly reduced due to the fact that the flashing frequency of the existing flashing bird-repelling equipment is fixed.

In view of this, the first aspect of the present application provides a method for selecting an optimal frequency for flashing bird repelling based on a simulated annealing algorithm, including the following steps:

s1, driving birds based on the flash bird driving equipment under the preset initial flash frequency, and obtaining the relative distance of the birds driven under the preset initial flash frequency, wherein the relative distance is the difference between the distance of the birds relative to the position of the flash bird driving equipment in the preset time after the flash driving is started and the distance of the birds relative to the position of the flash bird driving equipment before the flash driving is started, and when the birds are successfully driven, the relative distance is larger than 0;

s2, forming a pair of mapping data by the preset initial flashing frequency and the relative distance, and storing the mapping data into a mapping database;

s3, adjusting the preset initial flashing frequency, and repeating the steps S1-S2 until the logarithm of the mapping data in the mapping database reaches a preset logarithm;

s4, fitting the mapping data in the mapping database based on a least square method to form a fitting curve, and obtaining a fitting curve function;

s5, calculating the fitting curve function based on a simulated annealing algorithm to obtain the optimal flashing frequency;

and S6, replacing the preset initial flashing frequency with the optimal flashing frequency, applying the optimal flashing frequency to the flashing bird repelling device, and repeating the steps S1-S6 so as to continuously and iteratively replace the flashing frequency of the flashing bird repelling device.

Preferably, step S1 is preceded by: selecting the preset initial flashing frequency specifically comprises the following steps: the preset initial flashing frequency is selected according to a probability density function meeting normal distribution or selected according to historical flashing frequency data.

Preferably, the step of adjusting the preset initial flashing frequency in step S3 specifically includes:

updating the preset initial flashing frequency according to the following formula,

f1＝f0+(-1)^vγ(θ)

where f1 denotes the flash frequency after update, f0 denotes the flash frequency before update, v is a random number of 1 or 2, γ (θ) denotes a value range of (f0, θ)_max-f0]Wherein θ is_maxIndicating the maximum flashing frequency of the flashing bird repellent device.

Preferably, the fitted curve function in step S4 is,

f(x)＝a₁α₁(x)+a₂α₂(x)+...+a_nα_n(x)

in the formula, alpha_k(x) N is a set of linearly independent functions, a_kk 1, 2, n represents a pending coefficient;

assume that the mapped data point value to be fitted is y_i1, 2.. n, then the mapped data point values y to be fitted are fitted_iThe sum of the squares of the distances to the fitted curve function f (x) is minimal, and the corresponding fitted curve function f (x) is the best fitted curve function.

Preferably, step S5 specifically includes:

s501, initializing parameters of a simulated annealing algorithm, assuming that the initial temperature of the simulated annealing is T, the lowest temperature of the simulated annealing is T _ min, and the maximum iteration number is L;

s502, randomly generating an initial solution theta in a solution space, and calculating a function value f (theta) of the fitting curve function according to the initial solution theta;

s503, applying disturbance to the initial solution to generate a new solution theta ', and calculating a function value f (theta ') of the fitted curve function according to the new solution theta ';

s504, calculating a difference between the function value f (θ) of the fitted curve function and the function value f (θ ') of the fitted curve function, where Δ f is f (θ) -f (θ'), and Δ f represents the difference;

s505, judging whether the difference delta f is smaller than 0, if so, accepting the new solution theta ', and if not, judging whether accepting the new solution theta' according to Metropolis criterion;

s506, if the new solution theta ' is accepted, the new solution theta ' is taken as the current solution, and if the new solution theta ' is not accepted, the initial solution theta is taken as the current solution;

s507, according to the current solution serving as an initial solution of the next iteration, repeating the steps S502-S507 to perform iterative calculation, continuously iterating for N times in the iteration process, and if the generated new solutions are accepted, reducing the current temperature of the simulated annealing, wherein N is less than L;

s508, judging whether an iteration ending condition is met, if not, reducing the current temperature of the simulated annealing until the current temperature of the simulated annealing reaches the lowest temperature T _ min of the simulated annealing and iteration is ended or until the iteration times reaches the maximum iteration times L, and outputting a new solution obtained by the last iteration as the optimal flash frequency, wherein the reduction of the current temperature of the simulated annealing meets a temperature attenuation function, and the temperature attenuation function is T_k+1＝αT_k，T_kTemperature at time k, T_k+1The temperature at the time k +1, α represents the temperature cooling coefficient, α ∈ (0.95, 0.99).

Preferably, the step of applying a perturbation to the initial solution in step S503 to generate a new solution θ' specifically includes:

s5031, taking the initial solution as an initial point, and generating a new solution along a gradient reverse direction by adopting a steepest descent method;

s5032, if the generated new solution is not accepted, decreasing the step size of the gradient descent returns to step S5031 for recalculation, wherein the step size may be determined by a one-dimensional optimization method.

Preferably, the step of judging whether to accept the new solution θ' according to the Metropolis criterion in step S505 specifically includes:

when the initial temperature of the simulated annealing is T, calculating the internal energy of the initial solution and the new solution, and if the internal energy satisfies E_j＜E_iAccepting the new solution, wherein E_i、E_jRespectively representing the internal energy of the initial solution and the internal energy of the new solution; if not satisfying E_j＜E_iAccording to a probability formulaWhether the solution of (1) is greater than the random number of the interval of [0,1), if the judgment is yes, the new solution is accepted, if the judgment is no, the new solution is not accepted, wherein, p representsThe solution of the probability formula, K, represents the custom parameter.

In a second aspect, the invention provides a flash bird repelling optimal frequency selection system based on a simulated annealing algorithm, which is used for executing the flash bird repelling optimal frequency selection method based on the simulated annealing algorithm and comprises a relative distance module, a mapping module, a flash frequency adjusting module, a fitting module, a simulated annealing module and a frequency replacing module;

the relative distance module is used for acquiring the relative distance of birds driven under the preset initial flashing frequency based on the flashing bird driving equipment under the preset initial flashing frequency, the relative distance is the difference between the distance of the birds relative to the position of the flashing bird driving equipment in the preset time after the flashing driving is started and the distance of the birds relative to the position of the flashing bird driving equipment before the flashing driving is started, and when the birds are driven successfully, the relative distance is larger than 0;

the mapping module is used for forming a pair of mapping data by the preset initial flashing frequency and the relative distance and storing the mapping data into a mapping database;

the flash frequency adjusting module is used for adjusting the preset initial flash frequency;

the fitting module is used for fitting the mapping data in the mapping database based on a least square method to form a fitting curve so as to obtain a fitting curve function;

the simulated annealing module is used for calculating the fitting curve function based on a simulated annealing algorithm to obtain the optimal flash frequency;

the frequency replacing module is used for replacing the preset initial flashing frequency with the optimal flashing frequency and applying the optimal flashing frequency to the flashing bird repelling device.

According to the technical scheme, the invention has the following advantages:

the invention utilizes the mapping relation between different flash frequencies and the corresponding relative distance of the driven birds to be fitted into a fitting curve function, forms the dynamic prediction relation between the dynamic flash frequencies and the corresponding relative distances of the driven birds, then obtains the optimal flash frequency by calculating the fitting curve function based on a simulated annealing algorithm, applies the optimal flash frequency to flash bird driving equipment, and obtains different optimal flash frequencies by continuous iteration processing, thereby ensuring that the optimal flash frequency can be dynamically changed and improving the effectiveness of bird driving.

Drawings

Fig. 1 is a flowchart of a flash bird repelling optimal frequency selection method based on a simulated annealing algorithm according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a flash bird repelling optimal frequency selection system based on a simulated annealing algorithm according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Most of existing bird repelling equipment is installed on a transmission tower, and birds are repelled to be away from a transmission area through modes of flashing, sound, visual stimulation and the like. The flashing frequency of the existing flashing bird repelling device is fixed and unchanged, and birds have certain adaptability to the flashing frequency, so that the effectiveness of repelling the birds is greatly reduced, and line faults are easy to occur.

Therefore, referring to fig. 1, the invention provides a flash bird repelling optimal frequency selection method based on a simulated annealing algorithm, which comprises the following steps:

s1, driving birds based on the flash bird driving equipment under the preset initial flash frequency, obtaining the relative distance of the birds driven under the preset initial flash frequency, wherein the relative distance is the difference between the distance of the birds relative to the position of the flash bird driving equipment in the preset time after the flash driving is started and the distance of the birds relative to the position of the flash bird driving equipment before the flash driving is started, and when the birds are driven successfully, the relative distance is larger than 0;

s2, forming a pair of mapping data by the preset initial flashing frequency and the relative distance, and storing the mapping data into a mapping database;

s3, adjusting the preset initial flashing frequency, and repeating the steps S1-S2 until the logarithm of the mapping data in the mapping database reaches the preset logarithm;

s4, fitting the mapping data in the mapping database based on a least square method to form a fitting curve, so as to obtain a fitting curve function;

s5, calculating the fitting curve function based on the simulated annealing algorithm to obtain the optimal flashing frequency;

and S6, replacing the preset initial flashing frequency with the optimal flashing frequency, applying the optimal flashing frequency to the flashing bird repelling device, and repeating the steps S1-S6 so as to continuously and iteratively replace the flashing frequency of the flashing bird repelling device.

In the embodiment, the mapping relation between different flashing frequencies and the corresponding relative distance of the repelled birds is fitted into a fitting curve function to form a dynamic prediction relation between the dynamic flashing frequencies and the corresponding relative distances of the repelled birds, the fitting curve function is operated based on a simulated annealing algorithm to obtain the optimal flashing frequency, the optimal flashing frequency is applied to flashing bird repelling equipment, and different optimal flashing frequencies are obtained through continuous iteration processing, so that the optimal flashing frequency can be dynamically changed, and the bird repelling effectiveness is improved.

The following is a detailed description of an embodiment of the method for selecting the optimal frequency for flashing bird repelling based on the simulated annealing algorithm.

The invention provides a flash bird repelling optimal frequency selection method based on a simulated annealing algorithm, which comprises the following steps of:

s100, selecting a preset initial flashing frequency, and specifically comprising the following steps: selecting preset initial flashing frequency according to a probability density function meeting normal distribution or selecting according to historical flashing frequency data;

it should be noted that in one embodiment, the flash light is emittedThe initial flashing frequency of the bird repelling device can be selected according to historical flashing frequency data, or selected according to a probability density function which meets normal distribution, wherein the probability density function is phi ═ phi + (-1)^vf(s) phi, phi denotes the flashing frequency, v denotes the random number 1 or 2,is a value range of [0,1]In the formula, μ represents a mean value, and σ represents a variance.

S200, driving birds based on the flash bird driving equipment under the preset initial flash frequency, obtaining the relative distance of the birds driven under the preset initial flash frequency, wherein the relative distance is the difference between the distance of the birds relative to the position of the flash bird driving equipment in the preset time after the flash driving is started and the distance of the birds relative to the position of the flash bird driving equipment before the flash driving is started, and when the birds are driven successfully, the relative distance is larger than 0;

it should be noted that, under the action of the flashing frequency, the relative distance of the birds is the difference between the distance of the birds relative to the position of the flashing bird repelling device within the preset time after the flashing driving is started and the distance of the birds relative to the position of the flashing bird repelling device before the flashing driving is started; if the birds are successfully driven under the action of the flash frequency, the distance between the birds and the device is increased compared with that before the flash is started, the relative distance can be obtained through radar detection, and the relative distance larger than 0 represents the state of successful bird driving, which indicates that the flash bird driving equipment is effective in driving the birds under the flash frequency.

S300, forming a pair of mapping data by the preset initial flashing frequency and the relative distance, and storing the mapping data into a mapping database;

s400, adjusting the preset initial flashing frequency, and repeating the steps S200-S300 until the logarithm of the mapping data in the mapping database reaches the preset logarithm;

it should be noted that, when the preset initial flashing frequency is adjusted, the relative distance of the birds driven under the preset initial flashing frequency can be adjusted, so that the effectiveness of driving away the birds is ensured.

In one embodiment, the preset initial flashing frequency is updated according to the following formula,

f1＝f0+(-1)^vγ(θ)

where f1 denotes the flash frequency after update, f0 denotes the flash frequency before update, v is a random number of 1 or 2, γ (θ) denotes a value range of (f0, θ)_max-f0]Wherein θ is_maxIndicating the maximum flashing frequency of the flashing bird repellent device.

In addition, the preset logarithm may be based on the maximum storage capacity of the mapping database, and assuming that the maximum storage capacity of the mapping database is 10, only mapping data of 10 flash frequencies and relative distances may exist.

S500, fitting the mapping data in the mapping database based on a least square method to form a fitting curve, so as to obtain a fitting curve function;

specifically, the fitted curve function in step S500 is,

f(x)＝a₁α₁(x)+a₂α₂(x)+...+a_nα_n(x)

in the formula, alpha_k(x) N is a set of linearly independent functions, a_kk 1, 2, n represents a pending coefficient;

assume that the mapped data point value to be fitted is y_i1, 2.. n, then the mapped data point values y to be fitted are fitted_iAnd (3) the square sum of the distances from the fitting curve function f (x) is minimum, the corresponding fitting curve function f (x) is the best fitting curve function, and the best fitting curve function is the curve target function obtained by final fitting.

S600, calculating the fitted curve function based on a simulated annealing algorithm to obtain the optimal flash frequency;

specifically, step S600 specifically includes:

s601, initializing parameters of a simulated annealing algorithm, assuming that the initial temperature of the simulated annealing is T, the lowest temperature of the simulated annealing is T _ min, and the maximum iteration number is L;

it should be noted that the initial temperature T can be as large as possible to satisfyWhere θ is the initial solution, f (θ) is the fitted curve objective function value, and f (θ) ═ f (x).

The lowest temperature T _ min is the termination condition of algorithm iteration, and in order to obtain the optimal solution, the lowest temperature should be as low as possible; for each iteration of the temperature, the number of iterations is set to be in a decreasing trend as the temperature decreases.

S602, randomly generating an initial solution theta in a solution space, and calculating a function value f (theta) of a fitting curve function according to the initial solution theta;

s603, applying disturbance to the initial solution to generate a new solution theta ', and calculating a function value f (theta ') of the fitting curve function according to the new solution theta ';

it should be noted that the step of applying a perturbation to the initial solution to generate a new solution θ' in S503 specifically includes:

s6031, taking the initial solution as an initial point, and generating a new solution along the gradient reverse direction by adopting a steepest descent method;

s6032, if the generated new solution is not accepted, reducing the step length of the gradient descent, returning to the step S6031 for recalculation, wherein the step length can be determined by adopting a one-dimensional optimization method, and specifically, enabling the step length to be determined by adopting a one-dimensional optimization methodIn the formula (I), the compound is shown in the specification,is the function f at point x_kThe gradient of (d); so that f (x)_k+1) The minimum t is the optimal step size.

S604, calculating a difference between the function value f (θ) of the fitted curve function and the function value f (θ ') of the fitted curve function, where Δ f is f (θ) -f (θ'), and Δ f represents the difference;

s605, judging whether the difference delta f is smaller than 0, if so, accepting the new solution theta ', and if not, judging whether accepting the new solution theta' according to the Metropolis criterion;

it should be noted that the step of judging whether to accept the new solution θ' according to the Metropolis criterion specifically includes:

when the initial temperature of the simulated annealing is T, calculating the internal energy of the initial solution and the new solution, and if the internal energy satisfies E_j＜E_iThen accept a new solution, wherein E_i、E_jRespectively representing the internal energy of the initial solution and the internal energy of the new solution; if not satisfying E_j＜E_iAccording to a probability formulaIs greater than the random number in the interval of [0,1), if the judgment is yes, the new solution is accepted, if the judgment is no, the new solution is not accepted, wherein, p represents the solution of the probability formula, and K represents the self-defined parameter.

S606, if the new solution theta ' is accepted, the new solution theta ' is taken as the current solution, and if the new solution theta ' is not accepted, the initial solution theta is taken as the current solution;

s607, according to the current solution as the initial solution of the next iteration, repeating the steps S602 to S607 for iterative calculation, continuously iterating for N times in the iteration process, and if the generated new solutions are all accepted, reducing the current temperature of the simulated annealing, wherein N is less than L;

s608, judging whether an iteration ending condition is met, if not, reducing the current temperature of the simulated annealing until the current temperature of the simulated annealing reaches the lowest temperature T _ min of the simulated annealing and iteration ends or until the iteration times reaches the maximum iteration times L, and outputting a new solution obtained by the last iteration as the optimal flash frequency, wherein the reduction of the current temperature of the simulated annealing meets a temperature attenuation function, and the temperature attenuation function is T_k+1＝αT_k，T_kTemperature at time k, T_k+1The temperature at the time k +1, α represents the temperature cooling coefficient, α ∈ (0.95, 0.99).

S700, replacing the preset initial flashing frequency with the optimal flashing frequency, applying the optimal flashing frequency to the flashing bird repelling device, and repeating the steps S200-S700, thereby continuously and iteratively replacing the flashing frequency of the flashing bird repelling device.

The invention also provides a selection system for executing the flash bird repelling optimal frequency selection method based on the simulated annealing algorithm, and for convenience of understanding, please refer to fig. 2, the flash bird repelling optimal frequency selection system based on the simulated annealing algorithm provided by the invention comprises a relative distance module 100, a mapping module 200, a flash frequency adjusting module 300, a fitting module 400, a simulated annealing module 500 and a frequency replacing module 600:

the relative distance module 100 is configured to drive birds based on the flash bird repelling device at a preset initial flash frequency, obtain a relative distance of the birds driven at the preset initial flash frequency, where the relative distance is a difference between a distance of the birds from the position of the flash bird repelling device within a preset time after the flash driving is started and a distance of the birds from the position of the flash bird repelling device before the flash driving is started, and when the birds are successfully driven, the relative distance is greater than 0;

the mapping module 200 is configured to store a pair of mapping data, which is formed by a preset initial flashing frequency and a relative distance, in a mapping database;

a flash frequency adjusting module 300 for adjusting a preset initial flash frequency;

a fitting module 400, configured to fit the mapping data in the mapping database based on a least square method to form a fitting curve, so as to obtain a fitting curve function;

the simulated annealing module 500 is used for calculating the fitting curve function based on a simulated annealing algorithm to obtain the optimal flash frequency;

the frequency replacing module 600 is configured to replace the preset initial flashing frequency with an optimal flashing frequency, and further configured to apply the optimal flashing frequency to the flashing bird repelling device.

It should be noted that the working process in this embodiment is consistent with the working flow of the method for selecting the optimal frequency for flashing and bird repelling based on the simulated annealing algorithm in the above embodiment, and details are not repeated here.

According to the system for selecting the optimal flashing bird-repelling frequency based on the simulated annealing algorithm, the mapping relation between different flashing frequencies and the corresponding relative distances of the repelled birds is utilized to be fitted into a fitting curve function, the dynamic prediction dynamic relation between the flashing frequencies and the corresponding relative distances of the repelled birds is formed, the optimal flashing frequencies are obtained through the operation of the fitting curve function based on the simulated annealing algorithm and are applied to flashing bird-repelling equipment, and different optimal flashing frequencies are obtained through continuous iteration processing, so that the optimal flashing frequencies can be dynamically changed, and the effectiveness of repelling the birds is improved.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.