Variables Screening Method Based on the Algorithm of Combining Fruit Fly Optimization Algorithm and RBF Neural Network

DOI

10.2991/iccia.2012.377How to use a DOI?

Keywords

FOA, RBF neural network, Parameter optimization, MIV, Variables screen

Abstract

The form of fruit fly optimization algorithm (FOA) is easy to learn and has the characteristics of quick convergence and not readily dropping into local optimum. This paper presents the optimization of RBF neural network by means of FOA and establishment of network model, adopting it with the combination of the evaluation of the mean impact value(MIV) to select variables. The validity of this model is tested by two actual examples, furthermore, it is simpler to learn, more stable and practical.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fuqiang Xu
AU  - Youtian Tao
PY  - 2014/05
DA  - 2014/05
TI  - Variables Screening Method Based on the Algorithm of Combining Fruit Fly Optimization Algorithm and RBF Neural Network
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1521
EP  - 1525
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.377
DO  - 10.2991/iccia.2012.377
ID  - Xu2014/05
ER  -