Table 2 The indicators of individuals picked up from the feasible and nondominated fronts of last generation.

From: Combining multi-objective genetic algorithm and neural network dynamically for the complex optimization problems in physics

Algorithm

R/QFM [Ω]

Ra FM [MΩ]

fHOM [MHz]

R/QHOM [Ω]

DNMOGA

324.72

12.15

826.75

8.28E-7

NBMOGA

261.09

7.82

806.46

9.46

NSGA-II

284.54

9.93

800.56

18.58

Back to article page