Patent ID: 11932209
Assignee: CENTRAL SOUTH UNIVERSITY
Field: Measurement (Instruments)
Classification: CPC B  G  Y | IPC B  G

Claim 5:
6. The method for protecting the operation of the train under an air pollution environment according to claim 1, wherein in step 4, the calculation model of pollutant condition for the underbody component is trained with a GRU deep network algorithm, wherein the weight and threshold of the GRU deep network are obtained by optimization using a chaotic bat algorithm, comprising:
step B1: using the position of a bat individual as the weight and threshold of the calculation model of pollutant condition for the underbody component based on the GRU deep network, initializing bat swarms, and setting parameters of the bat swarms;
wherein the size of a bat swarm is in a range of [300, 600], the maximum pulse frequency r0 of the bat individual is in a range of [0.3, 0.6], the maximum pulse sound intensity A0 is in a range of [0.3, 0.6], the search accuracy is in a range of [0.002, 0.2], the pulse frequency is in a range of [0, 1.8], the increased coefficient of bat search frequency is in a range of [0.04, 0.1], the sound intensity attenuation coefficient is in a range of [0.75, 0.1], the maximum number of iterations is in a range of [200, 800], and the maximum search accuracy is in a range of [0.02, 0.15];

step B2: setting a fitness function, and determining a position of an initial optimal bat individual and the number of iterations t, t=1;
substituting the weight and threshold corresponding to the position of the bat individual into the calculation model of pollutant condition for the underbody component based on the GRU deep network, obtaining a detection result by using the calculation model of pollutant condition for the underbody component based on the GRU deep network determined from the position of the bat individual, and constructing a first fitness function f1(E) from the difference E between the detection result and the actual situation, f1(E)=1/(E+1);
calculating the fitness of the position of each bat individual by using the first fitness function, and using the position of the bat individual corresponding to the maximum fitness as a position of the initial optimal bat individual;

step B3: updating the speed and position of the bat individual by using a set pulse frequency;
step B4: if Rand1>ri, randomly disturbing the bat at the optimal individual position to generate a disturbed position of the bat individual;
wherein Rand1 is a random number uniformly distributed on [0, 1], and ri is a pulse frequency of the i-th bat;

step B5: if Rand2>Ai, and the fitness of the disturbed position of the bat individual is superior to the fitness of the position of the bat individual before disturbance, moving the bat individual to the disturbed position, or else keeping the bat individual at the original position;
wherein Rand2 is a random number uniformly distributed on [0, 1], and Ai is a sound intensity of the i-th bat;
step B6: if the condition of step B5 is satisfied, updating the pulse frequency and pulse sound intensity of the bat individual by using the increased coefficient of bat search frequency and the sound intensity attenuation coefficient, and returning to step B4, or else continuing to step B7;
step B7: calculating the fitness of the position of each bat individual in the current bat swarm, and performing chaotic optimization of position and speed on top m % bat individuals in descending order to obtain updated top m % bat individuals, wherein m is in a range of [4, 25]; and
step B8: determining whether the maximum number of iterations or the maximum search accuracy is reached; if it is reached, selecting a global optimal bat individual from the updated top m % bat individuals according to the fitness value, and outputting the optimal weight and threshold of the calculation model of pollutant condition for the underbody component based on the GRU deep network corresponding to the global optimal bat individual; otherwise, assuming t=t+1, and performing step B3 to continue next iteration.