This page contains the table of contents of the journal special issues about GFSs, referenced from the paper Website
Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects

Specifically, we have included the following special issues:

• F. Herrera. Special Issue on Genetic Fuzzy Systems for Control and Robotics. International Journal of Approximate Reasoning, Volume 17, Number 4, November 1997. Table of contents
• F. Herrera and L. Magdalena. Special Issue on Genetic Fuzzy Systems. International Journal of Intelligent Systems, Volume 13, Numbers 10-11, Oct.-Nov. 1998. Table of contents
• O. Cordón, F. Herrera, F. Hoffmann and L. Magdalena. Special Issue on Recent Advances in Genetic Fuzzy System. Information Sciences, Volume 136, Numbers 1-4 , August 2001. Table of contents
• O. Cordón, F. Gomide, F. Herrera, F. Hoffmann, L. Magdalena. Special Issue on Genetic Fuzzy Systems. Fuzzy Sets and Systems, Volume 141, Number 1, January 2004. Table of contents
• J. Casillas, M.J. del Jesus, F. Herrera, R. Pérez, P. Villar. Special Issue on Genetic Fuzzy Systems and the Interpretability-Accuracy Trade-off. International Journal of Approximate Reasoning. Volume 44, Number 1, February 2007. Table of contents
• O. Cordón, R. Alcalá, J. Alcalá-Fdez, I. Rojas. Genetic Fuzzy Systems. Special Issue on Genetic Fuzzy Systems: What's Next?. IEEE Transactions on Fuzzy Systems. Volume 15, Number 4, August 2007. Table of contents
• B. Carse, A.G. Pipe. Special Issue on Genetic Fuzzy Systems. International Journal of Intelligent Systems. Volume 22, Number 9, September 2007. Table of contents
• J. Casillas, B. Carse. Special Issue on Genetic Fuzzy Systems: Recent Developments and Future Directions. Soft-Computing. Volume 13, Number 5, March 2009. Table of contents
• R. Alcalá, Y. Nojima. Special Issue on Genetic Fuzzy Systems: New Advances. Evolutionary Intelligence. Volume 2, October 2009. Table of contents
• Y. Nojima, R. Alcalá, H. Ishibuchi and F. Herrera. Special Issue on Evolutionary Fuzzy Systems. Soft-Computing. Volume 15, Number 12, December 2011. Table of contents
• R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera. Special Issue on Evolutionary Fuzzy Systems. International Journal of Computational Intelligence Systems. Volume 5, Number 2, July 2012. Table of contents
• R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera. Special Issue on Evolutionary Fuzzy Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. Volume 20, Number 2, October 2012. Table of contents

International Journal of Approximate Reasoning Volume 17, Issue 4, November 1997
Special Issue on Genetic Fuzzy Systems for Control and Robotics

F. Herrera (Ed.)

Special Issue on Genetic Fuzzy Systems for Control and Robotics - Preface
Herrera, F.
p. 325-326, doi: 10.1016/S0888-613X(97)00023-6

Adapting the Gain of an FLC With Genetic Algorithms
Luis Magdalena
p. 327-349, doi: 10.1016/S0888-613X(97)00001-7

A Cascaded Genetic Algorithm for Improving Fuzzy-System Design
Henning Heider and Thorsten Drabe
p. 351-368, doi: 10.1016/S0888-613X(97)00003-0

A Three-Stage Evolutionary Process for Learning Descriptive and Approximate Fuzzy-Logic-Controller Knowledge Bases From Examples
O. Cordón and F. Herrera
p. 369-407, doi: 10.1016/S0888-613X(96)00133-8

Learning to Compose Fuzzy Behaviors for Autonomous Agents
Andrea Bonarini and Filippo Basso
p. 409-432, doi: 10.1016/S0888-613X(97)00002-9

Coordination Between Autonomous Robots
Pierre-Yves Glorennec
p. 433-446, doi: 10.1016/S0888-613X(97)00004-2

Evolutionary Design of a Fuzzy Knowledge Base for a Mobile Robot
Frank Hoffmann and Gerd Pfister
p. 447-469, doi: 10.1016/S0888-613X(97)00005-4

International Journal of Intelligent Systems Volume 13, Numbers 10-11, October-November 1998
Special Issue on Genetic Fuzzy Systems

F. Herrera, L. Magdalena (Eds.)

Introduction: Genetic fuzzy systems
Francisco Herrera, Luis Magdalena
p. 887-890, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<887::AID-INT1>3.0.CO;2-V

Genetic-based on-line learning for fuzzy process control
Juan R. Velasco
p. 891-903, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<891::AID-INT2>3.0.CO;2-U

Artificial evolution of fuzzy rule bases which represent time: A temporal fuzzy classifier system
Brian Carse, Terence C. Fogarty, Alistair Munro
p. 905-927, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<905::AID-INT3>3.0.CO;2-2

Context adaptation in fuzzy processing and genetic algorithms
Ricardo Gudwin, Fernando Gomide, Witold Pedrycz
p. 929-948, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<929::AID-INT4>3.0.CO;2-0

Learning fuzzy control by evolutionary and advantage reinforcements
Munir-ul M. Chowdhury, Yun Li
p. 949-974, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<949::AID-INT5>3.0.CO;2-Z

Fuzzy clustering with evolutionary algorithms
Frank Klawonn, Annette Keller
p. 975-991, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<975::AID-INT6>3.0.CO;2-W

Crossing unordered sets of rules in evolutionary fuzzy controllers
Luis Magdalena
p. 993-1010, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<993::AID-INT7>3.0.CO;2-U

Multistage control of a stochastic system in a fuzzy environment using a genetic algorithm
Janusz Kacprzyk
p. 1011-1023, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<1011::AID-INT8>3.0.CO;2-O

Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods
Oscar Cordón, María José del Jesus, Francisco Herrera
p. 1025-1053, doi: 10.1002/(SICI)1098-111X(199810/11)13:10/11<1025::AID-INT9>3.0.CO;2-N

Information Sciences Volume 136, Issue 1-4, August 2001
Special Issue on Recent Advances in Genetic Fuzzy Systems

O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena (Eds.)

Recent advances in genetic fuzzy systems
O. Cordón, F. Herrera, F. Hoffmann and L. Magdalena
1-5, doi: 10.1016/S0020-0255(01)00138-4

Genetic programming for model selection of TSK-fuzzy systems
Frank Hoffmann and Oliver Nelles
7-28, doi: 10.1016/S0020-0255(01)00139-6

Hierarchical genetic fuzzy systems
Myriam Regattieri Delgado, Fernando Von Zuben and Fernando Gomide
29-52, doi: 10.1016/S0020-0255(01)00140-2

Fuzzy modeling using genetic algorithms with fuzzy entropy as conciseness measure
T. Suzuki, T. Kodama, T. Furuhashi and H. Tsutsui
53-67, doi: 10.1016/S0020-0255(01)00141-4

Optimizing lattice-based associative memory networks by evolutionary algorithms
Ingo Renners and Adolf Grauel
69-84, doi: 10.1016/S0020-0255(01)00142-6

A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base
O. Cordón, F. Herrera, L. Magdalena and P. Villar
85-107, doi: 10.1016/S0020-0255(01)00143-8

Three-objective genetics-based machine learning for linguistic rule extraction
Hisao Ishibuchi, Tomoharu Nakashima and Tadahiko Murata
109-133, doi: 10.1016/S0020-0255(01)00144-X

Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems
J. Casillas, O. Cordón, M.J. Del Jesus and F. Herrera
135-157, doi: 10.1016/S0020-0255(01)00147-5

An experimental study about the search mechanism in the SLAVE learning algorithm: Hill-climbing methods versus genetic algorithms
Antonio González and Raúl Pérez
159-174, doi: 10.1016/S0020-0255(01)00145-1

Combining GP operators with SA search to evolve fuzzy rule based classifiers
Luciano Sánchez, Inés Couso and J.A. Corrales
175-191, doi: 10.1016/S0020-0255(01)00146-3

Approximative fuzzy rules approaches for classification with hybrid-GA techniques
Antonio F. Gómez-Skarmeta, Mercedes Valdés, Fernando Jiménez and Javier G. Marín-Blázquez
193-214, doi: 10.1016/S0020-0255(01)00148-7

Learning fuzzy classifier systems for multi-agent coordination
Andrea Bonarini and Vito Trianni
215-239, doi: 10.1016/S0020-0255(01)00149-9

Fuzzy Sets and Systems Volume 141, Number 1, 2004
Special Issue on Genetic Fuzzy Systems: New Developments

O. Cordón, F. Gomide, F. Herrera, F. Hoffmann and L. Magdalena (Eds.)

Genetic fuzzy systems. New developments.
Oscar Cordón, Fernando A. C. Gomide, Francisco Herrera, Frank Hoffmann, Luis Magdalena
p. 1-3, doi: 10.1016/S0165-0114(03)00110-6

Ten years of genetic fuzzy systems: current framework and new trends.
Oscar Cordón, Fernando A. C. Gomide, Francisco Herrera, Frank Hoffmann, Luis Magdalena
p. 5-31, doi: 10.1016/S0165-0114(03)00111-8

A fast genetic method for inducting descriptive fuzzy models.
Luciano Sánchez, José Otero
p. 33-46, doi: 10.1016/S0165-0114(03)00112-X

Combining boosting and evolutionary algorithms for learning of fuzzy classification rules.
Frank Hoffmann
p. 47-58, doi: 10.1016/S0165-0114(03)00113-1

Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining.
Hisao Ishibuchi, Takashi Yamamoto
p. 59-88, doi: 10.1016/S0165-0114(03)00114-3

Coevolutionary genetic fuzzy systems: a hierarchical collaborative approach.
Myriam Regattieri Delgado, Fernando J. Von Zuben, Fernando A. C. Gomide
p. 89-106, doi: 10.1016/S0165-0114(03)00115-5

Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy-Genetic system.
Hani Hagras, Victor Callaghan, Martin Colley
p. 107-160, doi: 10.1016/S0165-0114(03)00116-7

Book Review: "Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases" by Oscar Cordon, Francisco Herrera, Frank Hoffmann and Luis Magdalena; World Scientific, Singapore, New Jersey, London, Hong Kong, 2001, 462pp., ISBN 981-02-4016-3.
Hisao Ishibuchi
p. 161-162, doi: 10.1016/S0165-0114(03)00262-8

Corrigendum to "Computational complexity of optimization and crude range testing: a new approach motivated by fuzzy optimization": [Fuzzy Sets and Systems 135 (2003) 179-208]
G. William Walster, Vladik Kreinovich
p. 163, doi: 10.1016/S0165-0114(03)00130-1

International Journal of Approximate Reasoning Volume 44, Issue 1, 2007
Special Issue on Genetic Fuzzy Systems and the Interpretability-Accuracy Trade-off

J. Casillas, F. Herrera, R. Pérez, M.J. del Jesus, P. Villar (Eds.)

Special Issue on Genetic Fuzzy Systems and the Interpretability-Accuracy Trade-off - Editorial
Jorge Casillas, Francisco Herrera, Raúl Pérez, María José del Jesus and Pedro Villar
p. 1-3, doi: 10.1016/j.ijar.2006.06.002

Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning
Hisao Ishibuchi and Yusuke Nojima
p. 4-31, doi: 10.1016/j.ijar.2006.01.004

Improving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms
Jesús González, Ignacio Rojas, Héctor Pomares, Luis J. Herrera, Alberto Guillén, José M. Palomares and Fernando Rojas
p. 32-44, doi: 10.1016/j.ijar.2006.02.006

Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation
Rafael Alcalá, Jesús Alcalá-Fdez, Francisco Herrera and José Otero
p. 45-64, doi: 10.1016/j.ijar.2006.02.007

Interpretability-preserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study
Ester Van Broekhoven, Veronique Adriaenssens and Bernard De Baets
p. 65-90, doi: 10.1016/j.ijar.2006.03.003

IEEE Transactions on Fuzzy Systems Volume 15, Issue 4, 2007
Special Issue on Genetic Fuzzy Systems: What’s Next?

O. Cordón, R. Alcalá, J. Alcalá-Fdez., I. Rojas (Eds.)

Genetic Fuzzy Systems: What’s Next? - Editorial
O. Cordón, R. Alcalá, J. Alcalá-Fdez., I. Rojas
p. 533-535, doi: 10.1109/TFUZZ.2007.900902

Fuzzy-XCS: A Michigan Genetic Fuzzy System
J. Casillas, B. Carse and L. Bull
p. 536-550, doi: 10.1109/TFUZZ.2007.900904

Advocating the Use of Imprecisely Observed Data in Genetic Fuzzy Systems
L. Sánchez and I. Couso
p. 551-562, doi: 10.1109/TFUZZ.2007.895942

Incremental Evolutionary Design of TSK Fuzzy Controllers
F. Hoffmann, D. Schauten and S. Hölemann
p. 563-577, doi: 10.1109/TFUZZ.2007.900905

Evolutionary Fuzzy Rule Induction Process for Subgroup Discovery: A Case Study in Marketing
M. J. del Jesus, P. G. González, F. Herrera and M. Mesonero
p. 578-592, doi: 10.1109/TFUZZ.2006.890662

International Journal of Intelligent Systems Volume 22, Issue 9, September 2007.
Special Issue on Genetic Fuzzy Systems.

B. Carse, A.G. Pipe. (Eds)

Introduction: Genetic fuzzy systems
Brian Carse, A.G. Pipe
p. 905-907, doi: 10.1002/int.20231

Local identification of prototypes for genetic learning of accurate TSK fuzzy rule-based systems
Rafael Alcalá, Jesús Alcalá-Fdez, Jorge Casillas, Oscar Cordón, Francisco Herrera
p. 909-941, doi: 10.1002/int.20232

Improving interpretability in approximative fuzzy models via multiobjective evolutionary algorithms
A.F. Gómez-Skarmeta, F. Jiménez, G. Sánchez
p. 943-969, doi: 10.1002/int.20233

Genetic fuzzy systems to evolve interaction strategies in multiagent systems
Igor Walter, Fernando Gomide
p. 971-991, doi: 10.1002/int.20234

Fuzzy classifier system architectures for mobile robotics: An experimental comparison
A.G. Pipe, Brian Carse p. 993-1019, doi: 10.1002/int.20235

Boosting fuzzy rules in classification problems under single-winner inference
Luciano Sánchez, José Otero
p. 1021-1034, doi: 10.1002/int.20236

Increasing fuzzy rules cooperation based on evolutionary adaptive inference systems
Jesús Alcalá-Fdez, Francisco Herrera, Francisco Márquez, Antonio Peregrín
p. 1035-1064, doi: 10.1002/int.20237

Soft Computing Volume 13, Issue 3, March 2009
Special Issue on Genetic Fuzzy Systems: Recent Developments and Future Directions.

J. Casillas, B. Carse (Eds)

Preface: Genetic Fuzzy Systems: Recent Developments and Future Directions
Jorge Casillas, Brian Carse
p. 417-418 doi: 10.1007/s00500-008-0358-0

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems
María José Gacto, Rafael Alcalá, Francisco Herrera
p. 419-436 doi: 10.1007/s00500-008-0359-z

Context Adaptation of Fuzzy Systems Through a Multi-objective Evolutionary Approach Based on a Novel Interpretability Index
Alessio Botta, Beatrice Lazzerini, Francesco Marcelloni, Dan Stefanescu
p. 437-449 doi: 10.1007/s00500-008-0360-6

Learning consistent, complete and compact fuzzy rules sets in conjunctive normal form for system identification
Jorge Casillas, Pedro Martínez, Alicia D. Benítez
p. 451-465 doi: 10.1007/s00500-008-0361-5

Obtaining Linguistic Fuzzy Rule-based Regression Models from Imprecise Data with Multiobjective Genetic Algorithms
Luciano Sanchez, Jose Otero and Ines Couso
p. 467-479 doi: 10.1007/s00500-008-0362-4

A neuro-coevolutionary GFS to build soft sensors
Myriam Regattieri Delgado, Elaine Yassue Nagai, Lúcia Valéria Ramos de Arruda
p. 481-495 doi: 10.1007/s00500-008-0363-3

Processing time estimations by variable structure TSK rules learned through genetic programming.
Manuel Mucientes, Juan C. Vidal, Alberto Bugarín and Manuel Lama
p. 497-509 doi: 10.1007/s00500-008-0364-2

Parallel distributed genetic fuzzy rule selection
Yusuke Nojima, Hisao Ishibuchi, Isao Kuwajima
p. 511-519 doi: 10.1007/s00500-008-0365-1

A genetic-fuzzy mining approach for items with multiple minimum supports
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng, Chang-Shing Lee
p. 521-533 doi: 10.1007/s00500-008-0366-0

Evolutionary Intelligence, Volume 2, Issue 1-2, November 2009
Special Issue on Genetic Fuzzy Systems: New Advances.

R. Alcalá, Y. Nojima (Eds)

Guest Editorial: Special issue on genetic fuzzy systems: new advances
Rafael Alcalá, Yusuke Nojima
p. 1-3 doi: 10.1007/s12065-009-0027-y

Evolutionary parallel and gradually distributed lateral tuning of fuzzy rule-based systems
Ignacio Robles, Rafael Alcalá, José Manuel Benítez, Francisco Herrera
p. 5-19 doi: 10.1007/s12065-009-0025-0

Multi-objective evolutionary learning of granularity, membership function parameters and rules of Mamdani fuzzy systems
Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni
p. 21-37 doi: 10.1007/s12065-009-0022-3

Rule base and adaptive fuzzy operators cooperative learning of Mamdani fuzzy systems with multi-objective genetic algorithms
Antonio A. Márquez, Francisco A. Márquez, Antonio Peregrín
p. 39-51 doi: 10.1007/s12065-009-0026-z

Multiagent coevolutionary genetic fuzzy system to develop bidding strategies in electricity markets: computational economics to assess mechanism design
Igor Walter, Fernando Gomide
p. 53-71 doi: 10.1007/s12065-009-0023-2

Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets
Ana M. Palacios, Luciano Sánchez, Inés Couso
p. 73-84 doi: 10.1007/s12065-009-0024-1

Soft Computing (2011), Volume 15, Issue 12, December 2011
Special Issue on Evolutionary Fuzzy Systems.

Y. Nojima, R. Alcalá, H. Ishibuchi and F. Herrera (Eds)

Guest editorial: Special issue on evolutionary fuzzy systems
Y. Nojima, R. Alcalá, H. Ishibuchi and F. Herrera
p. 2299-2301, doi: 10.1007/s00500-010-0663-2

Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions
R. Alcalá, Y. Nojima, F. Herrera and H. Ishibuchi
p. 2303-2318, doi: 10.1007/s00500-010-0671-2

Genetic-fuzzy mining with multiple minimum supports based on fuzzy clustering
C. Chen, T. Hong and V. S. Tseng
p. 2319-2333, doi: 10.1007/s00500-010-0664-1

Learning knowledge bases of multi-objective evolutionary fuzzy systems by simultaneously optimizing accuracy, complexity and partition integrity
M. Antonelli, P. Ducange, B. Lazzerini and F. Marcelloni
p. 2335-2354, doi: 10.1007/s00500-010-0665-0

A multistage genetic fuzzy classifier for land cover classification from satellite imagery
D. G. Stavrakoudis, J. B. Theocharis and G. C. Zalidis
p. 2355-2374, doi: 10.1007/s00500-010-0666-z

Connecting Community-Grids by supporting job negotiation with coevolutionary Fuzzy-Systems
A. Fölling, C. Grimme, J. Lepping and A. Papaspyrou
p. 2375-2387, doi: 10.1007/s00500-010-0667-y

Fuzzy knowledge representation study for incremental learning in data streams and classification problems
A. Orriols-Puig and J. Casillas
p. 2389-2414, doi: 10.1007/s00500-010-0668-x

Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning
H. Ishibuchi, Y. Nakashima and Y. Nojima
p. 2415-2434, doi: 10.1007/s00500-010-0669-9

Evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department
C. J. Carmona, P. González, M. J. del Jesus, M. Navío-Acosta and L. Jiménez-Trevino
p. 2435-2448, doi: 10.1007/s00500-010-0670-3

International Journal of Computational Intelligence Systems (2012), Volume 5, Issue 2, July 2012
Special Issue on Evolutionary Fuzzy Systems.

R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera (Eds)

Guest editorial: Special issue on evolutionary fuzzy systems
R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera
p. 209-211, doi: 10.1080/18756891.2012.685261

An efficient inductive genetic learning algorithm for fuzzy relational rules
A. González, R. Pérez, Y. Caises and E. Leyva
p. 212-230, doi: 10.1080/18756891.2012.685265

A study on the use of multiobjective genetic algorithms for classifier selection in FURIA-based fuzzy multiclassifiers
Krzysztof Trawinski, Oscar Cordón and Arnaud Quirin
p. 231-253, doi: 10.1080/18756891.2012.685272

Reducing the complexity of genetic fuzzy classifiers in highly-dimensional classification problems
D. G. Stavrakoudis, G. N. Galidaki, I. Z. Gitas and J. B. Theocharis
p. 254-275, doi: 10.1080/18756891.2012.685290

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers
A. M. Palacios, L. Sánchez and I. Couso
p. 276-296, doi: 10.1080/18756891.2012.685292

A mechanism to improve the interpretability of linguistic fuzzy systems with adaptive defuzzification based on the use of a multi-objective evolutionary algorithm
A. A. Márquez, F. A. Márquez and A. Peregrín
p. 297-321, doi: 10.1080/18756891.2012.685309

Improving transparency in approximate fuzzy modeling using multi-objective immune-inspired optimisation
Jun Chen and Mahdi Mahfouf
p. 322-342, doi: 10.1080/18756891.2012.685311

Finding pareto-front membership functions in fuzzy data mining
Chun-Hao Chen, Tzung-Pei Hong and Vincent S. Tseng
p. 343-354, doi: 10.1080/18756891.2012.685314

Genetic lateral tuning for subgroup discovery with fuzzy rules using the algorithm NMEEF-SD
C. J. Carmona, P. González, M. J. Gacto and M. J. del Jesus
p. 355-367, doi: 10.1080/18756891.2012.685323

Automatic laser pointer detection algorithm for environment control device systems based on template matching and genetic tuning of fuzzy rule-based systems
F. Chávez, F. Fernández, M. J. Gacto, R. Alcalá
p. 368-386, doi: 10.1080/18756891.2012.685327

Genetic learning of fuzzy parameters in predictive and decision support modelling
Àngela Nebot, Francisco Mugica, Félix Castro and Jesús Acosta
p. 387-402, doi: 10.1080/18756891.2012.685328

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (2012), Volume 20, Issue 2, October 2012
Special Issue on Evolutionary Fuzzy Systems.

R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera (Eds)

Guest Editors' Introduction
R. Alcalá, Y. Nojima, H. Ishibuchi and F. Herrera
p. --, doi: 10.1142/S0218488512020023

IIVFDT: Ignorance Functions Based Interval-valued Fuzzy Decision Tree With Genetic Tuning
J. Sanz, H. Bustince, A. Fernández and F. Herrera
p. 1-30, doi: 10.1142/S0218488512400132

A Filter Proposal For Including Feature Construction In A Genetic Learning Algorithm
David Garcia, Antonio Gonzalez and Raul Perez
p. 31-49, doi: 10.1142/S0218488512400144

Combining Adaboost With Preprocessing Algorithms For Extracting Fuzzy Rules From Low Quality Data In Possibly Imbalanced Problems
Ana Palacios, Luciano Sanchez and Ines Couso
p. 51-71, doi: 10.1142/S0218488512400156

Handling Highly-dimensional Classification Tasks With Hierarchical Genetic Fuzzy Rule-based Classifiers
Dimitris G. Stavrakoudis And John B. Theocharis
p. 73-104, doi: 10.1142/S0218488512400168

Hierarchical-interpolative Fuzzy System Construction By Genetic And Bacterial Memetic Programming Approaches
Krisztián Balázs And László T. Kóczy
p. 105-131, doi: 10.1142/S021848851240017x

Inducing Fuzzy Regression Tree Forests Using Artificial Immune Systems
Fathi Gasir, Keeley Crockett and Zuhair Bandar
p. 133-157, doi: 10.1142/S0218488512400181

Checking Orthogonal Transformations And Genetic Algorithms For Selection Of Fuzzy Rules Based On Interpretability-accuracy Concepts
M. Isabel Rey, Marta Galende, M. J. Fuente and Gregorio I. Sainz-Palmero
p. 159-186, doi: 10.1142/S0218488512400193

Genetic-fuzzy Mining With Taxonomy
Chun-hao Chen, Tzung-pei Hong and Yeong-chyi Lee
p. 187-205, doi: 10.1142/S021848851240020x

Universal Image Noise Removal Filter Based On Type-2 Fuzzy Logic System And Qpso
Daoyuan Zhai, Minshen Hao and Jerry Mendel
p. 207-232, doi: 10.1142/S0218488512400211

Do Absence Data Matter When Modelling Fish Habitat Preference Using A Genetic Takagi-sugeno Fuzzy Model?
Shinji Fukuda And Bernard De Baets
p. 233-245, doi: 10.1142/S0218488512400223

A Novel Genetic Fuzzy Markup Language And Its Application To Healthy Diet Assessment
Chang-shing Lee, Mei-hui Wang, Hani Hagras, Zhi-wei Chen, Shun-teng Lan, Chin-yuan Hsu, Su-e Kuo, Hui-ching Kuo and Hui-hua Cheng
p. 247-278, doi: 10.1142/S0218488512400235