@inbook{75efc52894324b6d8c235e83d9de38ea,
title = "Evaluation of Surrogate Modelling Methods for Turbo-Machinery Component design Optimization",
abstract = "Surrogate models are used to approximate complex problems in order to reduce the final cost of the design process. This study has evaluated the potential for employing surrogate modelling methods in turbo-machinery component design optimization. Specifically four types of surrogate models are assessed and compared, namely: neural networks, Radial Basis Function (RBF) Networks, polynomial models and Kriging models. Guidelines and automated setting procedures are proposed to set surrogate models, which are applied to two turbo-machinery application studies.",
keywords = "Surrogate models, Neural networks, Turbo-machinery",
author = "Gianluca Badjan and Carlos Poloni and Andrew Pike and Nadir Ince",
year = "2015",
month = jan,
day = "31",
language = "English",
isbn = "978-3-319-11540-5",
series = "Computational Methods in Applied Sciences",
publisher = "Springer",
pages = "209--223",
editor = "David Greiner and { Galv{\'a}n}, { Blas} and P{\'e}riaux, { Jacques} and Nicolas Gauger and Giannakoglou, {Kyriakos C.} and Gabriel Winter",
booktitle = "Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences.",
address = "United Kingdom",
}