TY  - JOUR 
AU  - Gacto, María José
AU  - Galende Hernández, Marta
AU  - Alcalá, Rafael
AU  - Herrera, Francisco
PY  - 2014
SN  - 0020-0255
UR  - https://uvadoc.uva.es/handle/10324/74373
AB  - In this contribution, we propose a two-stage method for Accurate Fuzzy Modeling in High-Dimensional Regression Problems using Approximate Takagi–Sugeno–Kang Fuzzy Rule-Based Systems. In the first stage, an evolutionary data base learning is performed...
LA  - eng
PB  - Elsevier
KW  - Accurate fuzzy modeling
KW  - Takagi–Sugeno–Kang rules
KW  - Multi-objective genetic algorithms
KW  - Embedded genetic data base learning
KW  - Regression
KW  - High-dimensional and large-scale problems
TI  - METSK-HDe: A multiobjective evolutionary algorithm to learn accurate TSK-fuzzy systems in high-dimensional and large-scale regression problems
DO  - 10.1016/J.INS.2014.02.047
ER  -