| Autor: |
Linhan Ouyang, Liangqi Wan, Chanseok Park, Jianjun Wang, Yizhong Ma |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Journal of Management Science and Engineering, Vol 4, Iss 2, Pp 105-118 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2096-2320 |
| DOI: |
10.1016/j.jmse.2019.05.005 |
| Popis: |
This paper proposes an ensemble radial basis function neural network that selects important RBF subsets based on Pareto chart using Bootstrap samples. Then, the analysis of variance method is used to determine the choice of the unequal/equal weights. The effectiveness of the proposed technique is illustrated with a micro-drilling process. The comparison results show that the proposed technique can not only improve the model prediction performance, but also generate a reliable scheme for quality design. Keywords: RBF model, Ensemble model, Model selection, Pareto chart, Process optimization |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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