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1
A Multi-Objective Genetic Algorithm for Learning Linguistic Persistent Queries in Text Retrieval Environments
In: http://sci2s.ugr.es/publications/ficheros/2006-Chapter-Luque-GA_for_Text_Retrieval_Enviroments.pdf (2006)
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2
Genetic tuning of fuzzy rule deep structures preserving interpretability and its interactison with fuzzy set reduction
In: http://sci2s.ugr.es/publications/ficheros/01392997.pdf (2005)
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3
Interpretability improvements to find the balance interpretability-accuracy in fuzzy modeling: an overview
In: http://decsai.ugr.es/~casillas/downloads/papers/casillas-cl06-springer03b-ch1.pdf (2003)
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4
Genetic Tuning of Fuzzy Rule Deep Structures for Linguistic Modeling
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/tr-010102.ps.Z (2001)
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5
A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules
In: http://hera.ugr.es/doi/15016274.pdf (2000)
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6
Learning Fuzzy Rules Using Ant Colony Optimization Algorithms
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/con/LFR-ants00.ps.Z (2000)
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7
A proposal for improving the accuracy of linguistic modeling
In: http://hera.ugr.es/doi/1501535x.pdf (2000)
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8
Can Linguistic Modeling Be As Accurate As Fuzzy Modeling Without Losing Its Description To A High Degree?
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/tr-000120.ps.Z (2000)
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9
Linguistic modeling by hierarchical systems of linguistic rules
In: http://hera.ugr.es/doi/15006104.pdf (1999)
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10
ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/con/ida99.ps.Z (1999)
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11
Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods
In: http://sci2s.ugr.es/publications/ficheros/ijis-13(10-11)-1025-1053.pdf (1998)
Abstract: In this paper, we present a multistage genetic learning process for obtaining linguistic fuzzy rule-based classification systems that integrates fuzzy reasoning methods cooperating with the fuzzy rule base and learns the best set of linguistic hedges for the linguistic variable terms. We show the application of the genetic learning process to two well known sample bases, and compare the results with those obtained from different learning algorithms. The results show the good behavior of the proposed method, which maintains the linguistic description of the fuzzy rules. � 1998 John Wiley & Sons, Inc. 1.
URL: http://sci2s.ugr.es/publications/ficheros/ijis-13(10-11)-1025-1053.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.9569
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12
Identification of Linguistic Fuzzy Models by Means of Genetic Algorithms
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/hel.ps.Z (1997)
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13
A Three-Stage Evolutionary Process for Learning Descriptive and Approximative Fuzzy Logic Controller Knowledge Bases from Examples
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/ijar97.ps.Z (1997)
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14
Generating and Selecting Fuzzy Control Rules Using Evolution Strategies and Genetic Algorithms
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/con/gen-ipmu96.ps.Z (1996)
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15
Learning cooperative linguistic fuzzy rules using the best-worst ant system algorithm
In: http://sci2s.ugr.es/publications/ficheros/2005 - Casillas-Cordon-Viana-Herrera - Learning Cooperative Linguistic Fuzzy Rules Using ACO.pdf
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16
Different Proposals To Improve The Accuracy Of Fuzzy Linguistic Modeling
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/libro-kerre.ps.Z
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17
Genetic Feature Selection in a Fuzzy Rule-Based Classification System Learning Process
In: ftp://decsai.ugr.es/pub/arai/tech_rep/ga-fl/con/ipmu00-3.ps.Z
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18
Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base
In: http://sci2s.ugr.es/publications/ficheros/IEEE-TFS-9(4)-667-674.pdf
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19
Building Fuzzy Graphs: Features and Taxonomy of Learning for Non-Grid-Oriented Fuzzy Rule-Based Systems ∗
In: http://sci2s.ugr.es/publications/ficheros/IJIFS-2001-11-99-119.pdf
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20
Influence of Fuzzy Partition . . .
In: http://www.eusflat.org/publications/proceedings/EUSFLAT-ESTYLF_1999/papers/159-herrera.pdf
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