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The experimental results on 40 benchmark test functions demonstrate that, compared with five representative PSO algorithms, ALPSO performs much better than the others in more cases, on both convergence accuracy and convergence speed.
Similar(59)
Stability, convergence, accuracy and statistics.
The four methods were compared in terms of convergence, accuracy and computation time.
Several numerical examples are presented to demonstrate the convergence, accuracy and validity of the proposed method.
Several examples are solved to demonstrate the convergence, accuracy and validity of the proposed method.
Further, each of the evolutionary algorithms has its own advantages and disadvantages in convergence accuracy and computational time.
Convergence, accuracy and robustness of the proposed method, i.e. GSM/ALE, are examined through a series of benchmark tests.
The convergence, accuracy and computational efficiency of the presented element are validated through comparisons with experimental and numerical results available from the literature.
An elitist self-adaptive step-size search (ESASS) algorithm is proposed wherein two approaches are considered for improving (i) convergence accuracy, and (ii) computational efficiency.
Moreover, it gives competitive results in terms of convergence, accuracy and search-ability when compared with the state-of-the-art algorithms.
The results of the statistical analyses are used to validate the consistency of the proposed normalized fractional adaptive methodologies in terms of convergence, accuracy and robustness.
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CEO of Professional Science Editing for Scientists @ prosciediting.com