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Both of the algorithms are compared in terms of convergence rate and success of converging to an optimal solution.
In terms of convergence speed, the graph-based technique with the simultaneous scheduling converges faster than that with random scheduling, as in all the previous cases.
The four methods were compared in terms of convergence, accuracy and computation time.
Furthermore, an additional experimentation has been performed in terms of convergence.
Results show that the proposed method outperforms the existing methods in terms of convergence performance and forecasting accuracy.
The performance of the FD-SCA in terms of convergence rate is further enhanced using normalization in frequency bins.
Simulation results show high performance for Modified Firefly Algorithm as compared to conventional Firefly Algorithm in terms of convergence rate.
The friendship centers significantly improved RIO in terms of convergence speed and stability with a minor 37.47% additional time cost.
Experimental studies demonstrate that the proposed HMOGWO outperforms other algorithms in terms of convergence, spread and coverage.
Modifications on this algorithm were proposed in order to enhance its performance in terms of convergence speed and computational effort.
In addition the performance of both optimization techniques in terms of convergence rate and computational time is compared.
More suggestions(15)
in terms of congruence
in terms of closeness
in terms of alignment
in terms of articulation
in terms of approximation
in terms of harmonization
in terms of intersection
in terms of attainment
in terms of crossover
in terms of consistency
in terms of race
in terms of coulda
in terms of fund-raising
in terms of temperature
in terms of surveillance
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