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Table 2 Implementation details of genetic algorithm

From: Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems

Parameters
Number of genetic algorithm iterations 5
Population 100
Maximum number of generations 100
Crossover probability 0.8
Elite count 2
Mutation probability 0.2
Selection Binary selection tournament
Crossover Laplace crossover
Mutation Power mutation
Stopping criteria Average change in best fitness value is less than 10−6 for 50 generations or number of generations = 100