Neural Network Committees Optimized with Evolutionary Methods for Steel Temperature Control

Abstract

This paper presents regression models based on an ensemble of neural networks trained on different data that negotiate the final decision using an optimization approach based on an evolutionary approach. The model is designed for big and complex datasets. First, the data is clustered in a hierarchical way and then using different level of cluster and random… (More)
DOI: 10.1007/978-3-642-23935-9_4

Topics

3 Figures and Tables

Cite this paper

@inproceedings{Kordos2011NeuralNC, title={Neural Network Committees Optimized with Evolutionary Methods for Steel Temperature Control}, author={Miroslaw Kordos and Marcin Blachnik and Tadeusz Wieczorek and Slawomir Golak}, booktitle={ICCCI}, year={2011} }