Rough Sets and Artificial Neural Networks
Marcin S. Szczuka · Studies in fuzziness and soft computing · 1998
This work is an attempt to summarize several approaches aimed at connecting Rough Set Theory with Artificial Neural Networks. Both methodologies have their place among intelligent classification and decision support methods. Artificial Neural Networks belong to most commonly used techniques in applications of Artificial Intelligence. During the last twenty years of its development numerous theoretical and applied works have been done in that field. Rough Set Theory which emerged about fifteen years ago is nowadays rapidly developing branch of AI and Soft Computing. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.