GUAJE FUZZY Files

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//
//   GUAJE: Generating Understandable and Accurate Fuzzy Models in a Java Environment
//
//   Contact: guajefuzzy@gmail.com
//
//   Copyright (C) 2007 - 2015  Jose Maria Alonso Moral
//
//    This program is free software: you can redistribute it and/or modify
//    it under the terms of the GNU General Public License as published by
//    the Free Software Foundation, either version 3 of the License, or
//    (at your option) any later version.
//
//    This program is distributed in the hope that it will be useful,
//    but WITHOUT ANY WARRANTY; without even the implied warranty of
//    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
//    GNU General Public License for more details.
//
//    You should have received a copy of the GNU General Public License
//    along with this program. If not, see <http://www.gnu.org/licenses/>.
//
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GUAJE stands for "Generating Understandable and Accurate Fuzzy Models in a Java Environment".

GUAJE is a dynamic user friendly tool whose main goal is the generation or refinement of fuzzy knowledge bases related to specific problems. The whole process of using GUAJE is structured in different (not necessarily sequential) steps with the aim of generating a knowledge base related to a specific problem, carefully integrating both expert and induced knowledge.

GUAJE implements the fuzzy modeling methodology named as HILK. The interested reader is referred to the following publications for further details:

+ D. P. Pancho, J. M. Alonso, and L. Magdalena, Quest for interpretability-accuracy trade-off supported by Fingrams into the fuzzy modeling tool GUAJE, International Journal of Computational Intelligence Systems, 6(1):46-60, 2013.
+ J. M. Alonso and L. Magdalena, Generating understandable and accurate fuzzy rule-based systems in a java environment, Lecture Notes in Artificial Intelligence - 9th International Workshop on Fuzzy Logic and Applications, LNAI6857, 212–219, 2011.
+ J. M. Alonso and L. Magdalena, HILK++: an interpretability-guided fuzzy modeling methodology for learning readable and comprehensible fuzzy rule-based classifiers, Soft Computing, 15(10):1959–1980, 2011.
+ J. M. Alonso, L. Magdalena and S. Guillaume, HILK: a new methodology for designing highly interpretable linguistic knowledge bases using the fuzzy logic formalism, International Journal of Intelligent Systems, 23(7):761–794, 2008.
+ J. M. Alonso, Interpretable fuzzy systems modeling with cooperation between expert and induced knowledge, PhD thesis, Technical University of Madrid (UPM), 2007.

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//                                CITATION POLICY
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In case you want to make reference to GUAJE in your own publications, please cite the following papers:

+ D. P. Pancho, J. M. Alonso, and L. Magdalena, Quest for interpretability-accuracy trade-off supported by Fingrams into the fuzzy modeling tool GUAJE, International Journal of Computational Intelligence Systems, 6(1):46-60, 2013.
+ J. M. Alonso and L. Magdalena, Generating understandable and accurate fuzzy rule-based systems in a java environment, Lecture Notes in Artificial Intelligence - 9th International Workshop on Fuzzy Logic and Applications, LNAI6857, 212–219, 2011.
+ J. M. Alonso and L. Magdalena, HILK++: an interpretability-guided fuzzy modeling methodology for learning readable and comprehensible fuzzy rule-based classifiers, Soft Computing, 15(10):1959–1980, 2011.

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//                                NEW IN GUAJE-vb3.0
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The main changes in the new version are listed below:

1) Several minor bugs have been fixed.

2) GUAJE is now ready to be installed with both 32 and 64 bits JVMs.

3) GUAJE is adapted to the last version of FingramsGenerator. Thus, generation and visualization of fingrams is enriched.

4) GUAJE offers the new functionality of generating Java source code for the designed fuzzy systems.

5) The HTML user manual (as well as the quickstart tutorials) has been double checked, revised and enhanced with additional details.

6) The API is updated.