Name
Abstract | ||
|---|---|---|
•Soft computing methods are explored for tuning the parameters of washout algorithms.•Objective motion fidelity functions are used upon simulated motion platforms.•The proposed PSO-based tuning method is assessed with the classical washout.•Results show that the PSO solution outperforms other methods such as a GA.•PSO is faster, provides better results, and needs fewer parameters than a GA. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.asoc.2018.03.044 | Applied Soft Computing |
Keywords | Field | DocType |
Optimization,Particle swarm,Motion cueing,Washout,MCA,Tuning,Vehicle simulation,Motion platform | Convergence (routing),Inertial frame of reference,Particle swarm optimization,Mathematical optimization,Fidelity,Correctness,Algorithm,Optimization algorithm,Parameter space,Mathematics,Genetic algorithm | Journal |
Volume | ISSN | Citations |
68 | 1568-4946 | 2 |
PageRank | References | Authors |
0.40 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergio Casas | 1 | 21 | 9.66 |
| Cristina Portalés | 2 | 21 | 8.26 |
| Pedro Morillo | 3 | 129 | 14.20 |
| Marcos Fernández | 4 | 34 | 5.47 |