Modeling the Electrical Activity of the Heart via Transfer Functions and Genetic Algorithms

. 2024 May 18;9(5):300. doi: 10.3390/biomimetics9050300

Algorithm 1 Pseudocode for the used GA

1:
Begin
2:
Select hyperparameters
3:
Set the initial population $P$ ; each individual is a vector with random coefficients corresponding to Equation (12).
4:
while fitness function ≤ 30,000 do
5:
Calculate fitness of each individual of $P$ , defined by the Integral Square Error.
6:
Selection of $P$ members with lower fitness value, according to biological pressure.
7:
Crossover parents with lowest fitness, using a random single point to create the union.
8:
Random change of a value in individuals (mutation).
9:
Generate a new generation of individuals $P$ using elitism and the members with the lowest fitness.
10:
end while
11:
Keep the best solution (minimum fitness)
12:
end