Advertisement
Published in:
2009 | OriginalPaper | Chapter
Thresholded Neural Networks for Sensitive Industrial Classification Tasks
Authors : Marco Vannucci, Valentina Colla, Mirko Sgarbi, Orlando Toscanelli
Published in: Bio-Inspired Systems: Computational and Ambient Intelligence
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this paper a novel classification method for real world classification tasks is proposed. The method was designed to overcome the difficulties encountered by traditional methods when coping with those real world problems where the key issue is the detection of particular situations - such as for instance machine faults or anomalies - which in some frameworks are hard to be recognized due to some interacting factors that are analyzed within the paper. The method is described and tested on two industrial problems, which show the goodness of the proposed approach and encourage its use in the industrial environments.