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The efficiency of the proposed algorithm is assessed on several benchmarks before applying the algorithm to identify the most relevant inputs of a double-diffusive convection model.
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The performance of the proposed algorithm is assessed by numerical experiments on 12 benchmark problems.
The performance of the proposed algorithm is assessed resorting to real experiments based on the Rawseeds dataset as well as further realistic simulations.
The potential of the proposed algorithm is assessed by means of an extensive comparative study of the numerical results on sixteen benchmark test functions.
The proposed algorithm is assessed by simulations.
Note that the performance of the proposed algorithm is assessed under different conditions.
The performance of proposed algorithm is assessed using a range of model systems.
The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data.
The proposed algorithm was assessed and applied on bacteriophage genomes.
Finally, in Section 4, the performances of the proposed algorithm are assessed through numerical simulations and compared with existing methods.
The performance of the proposed algorithm is extensively assessed and comparisons are made with Particle Swarm Optimization (PSOs), Genetic Algorithm (GA) and graph theoretical approach (GTA) applied on the 54 and 100-bus primary power distribution systems.
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