Input selection in data-driven fuzzy modeling

IEEE International Conference on Fuzzy Systems

Volumn 3, Issue , 2001, Pages 1251-1254

  Gaweda, Adam E ^a   Zurada, Jacek M ^a   Setiono, Rudy ^b  

^a UNIVERSITY OF LOUISVILLE   (United States)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BACKWARD SELECTION METHOD; FUZZY MODEL EXTRACTION; INPUT VARIABLE SELECTION; TAKAGI-SUGENO MODEL;

COMPUTATIONAL COMPLEXITY; CORRELATION METHODS; HEURISTIC METHODS; IDENTIFICATION (CONTROL SYSTEMS); ITERATIVE METHODS; LEARNING ALGORITHMS; LINEAR EQUATIONS; MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; NONLINEAR SYSTEMS; SENSITIVITY ANALYSIS; VECTORS;

FUZZY SETS;

EID: 0036346429     PISSN: None     EISSN: None     Source Type: Journal    
DOI: 10.1109/FUZZ.2001.1008885     Document Type: Article

References (10)

1. A fuzzy-logic-based approach to qualitative modeling
2. Input selection for ANFIS learning
3. Modeling and control of carbon monoxide concentration using a neuro-fuzzy technique
4. Selecting input variables for fuzzy models
5. Input variable identification - Fuzzy curves and fuzzy surfaces
6. Input selection and partition validation for fuzzy modelling using neural network
7. Fuzzy identification of systems and its application to modeling and control
8. Data-driven design of fuzzy system with relational input partition