Evolution-based design of neural fuzzy networks using self-adapting genetic parameters

IEEE Transactions on Fuzzy Systems

Volumn 10, Issue 2, 2002, Pages 211-221

  Alpaydin, Güner ^a   Dündar, Günhan ^b   Balkir, Sina ^c  

^a Istanbul Navy Ship Yard   (Turkey)

^b BOGAZICI UNIVERSITY   (Turkey)

^c UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Evolution strategies; Fuzzy logic systems (FLSs); Genetic algorithms; Neural fuzzy networks; Simulated annealing

Indexed keywords

GENETIC ALGORITHMS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; OPTIMIZATION; SIMULATED ANNEALING;

NEURAL FUZZY NETWORKS;

FUZZY SETS;

EID: 0036531527     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/91.995122     Document Type: Article

References (24)

1. ANFIS: Adaptive-network-based fuzzy inference system
2. Rule-based structure identification in an adaptive-network-based fuzzy inference system
3. Neural-network-based fuzzy logic control and decision making
4. Fuzzy inference neural network for fuzzy model tuning
5. An on-line self-constructing neural fuzzy inference network and its applications
6. Designing fuzzy logic systems
7. Fuzzy logic synthesis with genetic algorithms
8. Design of intelligent fuzzy logic controllers using genetic algorithms
9. Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms
10. Dynamic control of genetic algorithms using fuzzy logic techniques
11. Implementation of evolutionary fuzzy systems
12. Optimization of analog integrated circuits via simulated annealing and evolutionary strategies
13. Evolution strategies I: Variants and their computational implementation
14. Synthesis of high-performance analog circuits in ASTRX/OBLX
15. Equation of state calculations by fast computer machines
16. A theoretical framework for simulated annealing
17. Analog circuit design optimization based on symbolic simulation and simulated annealing
18. Evolution strategies II: Theoretical aspects
19. FuGeNeSys - A fuzzy genetic neural system for fuzzy modeling
20. Extended selection mechanisms in genetic algorithms
21. Circuit performance modeling by means of fuzzy logic
22. A Novel CMOS current conveyor realization with an electronically tunable current mode filter suitable for VLSI
23. A comparison of three methods for selecting initial values of input variables in the analysis of output from a computer code
24. Cascading classifiers