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Publication search results
found 23 matches
- 2021
- Bor-Sen Chen, Min-Yen Lee, Wei-Yu Chen, Weihai Zhang:
Reverse-Order Multi-Objective Evolution Algorithm for Multi-Objective Observer-Based Fault-Tolerant Control of T-S Fuzzy Systems. IEEE Access 9: 1556-1574 (2021) - Amiram Moshaiov, Adham Salih:
Multi-Objective Structure and Parameter Evolution of Neuro-Fuzzy Systems. SSCI 2021: 1-7 - 2019
- Salma Elhag, Alberto Fernández, Abdulrahman H. Altalhi, Saleh Alshomrani, Francisco Herrera:
A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems. Soft Comput. 23(4): 1321-1336 (2019) - 2016
- Marian B. Gorzalczany, Filip Rudzinski:
An improved multi-objective evolutionary optimization of data-mining-based fuzzy decision support systems. FUZZ-IEEE 2016: 2227-2234 - 2014
- Michela Fazzolari, Rafael Alcalá, Francisco Herrera:
A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems: D-MOFARC algorithm. Appl. Soft Comput. 24: 470-481 (2014) - 2012
- María José Gacto, Rafael Alcalá, Francisco Herrera:
A multi-objective evolutionary algorithm for an effective tuning of fuzzy logic controllers in heating, ventilating and air conditioning systems. Appl. Intell. 36(2): 330-347 (2012) - Antonio A. Márquez, Francisco Alfredo Márquez, Antonio Peregrín:
A Mechanism to Improve the Interpretability of Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm. Int. J. Comput. Intell. Syst. 5(2): 297-321 (2012) - 2011
- Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
Learning knowledge bases of multi-objective evolutionary fuzzy systems by simultaneously optimizing accuracy, complexity and partition integrity. Soft Comput. 15(12): 2335-2354 (2011) - Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
Multi-objective evolutionary generation of Mamdani fuzzy rule-based systems based on rule and condition selection. GEFS 2011: 47-53 - 2010
- María José Gacto, Rafael Alcalá, Francisco Herrera:
Analysis of the Performance of a Semantic Interpretability-Based Tuning and Rule Selection of Fuzzy Rule-Based Systems by Means of a Multi-Objective Evolutionary Algorithm. IEA/AIE (2) 2010: 228-238 - 2009
- Pietro Ducange:
Multi-Objective Evolutionary Learning of Mamdani Fuzzy Rule-Based Systems. University of Pisa, Italy, 2009 - Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
Multi-objective evolutionary learning of granularity, membership function parameters and rules of Mamdani fuzzy systems. Evol. Intell. 2(1-2): 21-37 (2009) - Antonio Gabriel López-Herrera, Enrique Herrera-Viedma, Francisco Herrera:
Applying multi-objective evolutionary algorithms to the automatic learning of extended Boolean queries in fuzzy ordinal linguistic information retrieval systems. Fuzzy Sets Syst. 160(15): 2192-2205 (2009) - Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework. Int. J. Approx. Reason. 50(7): 1066-1080 (2009) - Alessio Botta, Beatrice Lazzerini, Francesco Marcelloni, Dan C. Stefanescu:
Context adaptation of fuzzy systems through a multi-objective evolutionary approach based on a novel interpretability index. Soft Comput. 13(5): 437-449 (2009) - María José Gacto, Rafael Alcalá, Francisco Herrera:
Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems. Soft Comput. 13(5): 419-436 (2009) - Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
Exploiting a New Interpretability Index in the Multi-Objective Evolutionary Learning of Mamdani Fuzzy Rule-Based Systems. ISDA 2009: 115-120 - 2008
- Marco Cococcioni, Giovanni Corsini, Beatrice Lazzerini, Francesco Marcelloni:
Solving the ocean color inverse problem by using evolutionary multi-objective optimization of neuro-fuzzy systems. Int. J. Knowl. Based Intell. Eng. Syst. 12(5-6): 339-355 (2008) - Pietro Ducange, Rafael Alcalá, Francisco Herrera, Beatrice Lazzerini, Francesco Marcelloni:
Knowledge Base Learning of Linguistic Fuzzy Rule-Based Systems in a Multi-objective Evolutionary Framework. HAIS 2008: 747-754 - 2007
- Marco Cococcioni, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni:
A Pareto-based multi-objective evolutionary approach to the identification of Mamdani fuzzy systems. Soft Comput. 11(11): 1013-1031 (2007) - 2006
- Jesús González, Ignacio Rojas, Héctor Pomares, Fernando Rojas, José M. Palomares:
Multi-objective evolution of fuzzy systems. Soft Comput. 10(9): 735-748 (2006) - 2004
- Paul J. Stewart, D. A. Stone, Peter J. Fleming:
Design of robust fuzzy-logic control systems by multi-objective evolutionary methods with hardware in the loop. Eng. Appl. Artif. Intell. 17(3): 275-284 (2004) - Hisao Ishibuchi, Takashi Yamamoto:
Multi-objective evolutionary design of fuzzy rule-based systems. SMC (3) 2004: 2362-2367
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