Fast Fuzzy Inference in Octave

DOI

10.1080/18756891.2013.769765How to use a DOI?

Keywords

GNU Octave, fuzzy relations, fuzzy composition, fuzzy inference

Abstract

Fuzzy relations are simple mathematical structures that enable a very general representation of fuzzy knowledge, and fuzzy relational calculus offers a powerful machinery for approximate reasoning. However, one of the most relevant limitations of approximate reasoning is the efficiency bottleneck. In this paper, we present two implementations for fast fuzzy inference through relational composition, with the twofold objective of being general and efficient. The two implementations are capable of working on full and sparse representations respectively. Further, a wrapper procedure is capable of automatically selecting the best implementation on the basis of the input features. We implemented the code in GNU Octave because it is a high-level language targeted to numerical computations. Experimental results show the impressive performance gain when the proposed implementation is used.

Copyright

© 2017, 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  - JOUR
AU  - Piero Molino
AU  - Gianvito Pio
AU  - Corrado Mencar
PY  - 2013
DA  - 2013/03/01
TI  - Fast Fuzzy Inference in Octave
JO  - International Journal of Computational Intelligence Systems
SP  - 307
EP  - 317
VL  - 6
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.769765
DO  - 10.1080/18756891.2013.769765
ID  - Molino2013
ER  -