TY - GEN
T1 - Data Driven Fuzzy Modeling Using Level Sets
AU - Leite, Daniel
AU - Gomide, Fernando
AU - Yager, Ronald
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The paper looks at the structure of fuzzy rule-based models from the point of view of a function relating membership grades of inputs with rule outputs. This view in turn is generalized by an approach that produces the output functions of the fuzzy rules using input and output data. In this view, a formulation to compute the output of the model consists of estimating the parameters of the output functions. Essentially, the paper suggests an alternative method for fuzzy modeling based on output functions constructed from level sets and input and output data. The data driven method provides an easy and efficient way to develop and process fuzzy models. Examples of function estimation problems show that the data driven level set method is very effective when compared with alternative modeling techniques.
AB - The paper looks at the structure of fuzzy rule-based models from the point of view of a function relating membership grades of inputs with rule outputs. This view in turn is generalized by an approach that produces the output functions of the fuzzy rules using input and output data. In this view, a formulation to compute the output of the model consists of estimating the parameters of the output functions. Essentially, the paper suggests an alternative method for fuzzy modeling based on output functions constructed from level sets and input and output data. The data driven method provides an easy and efficient way to develop and process fuzzy models. Examples of function estimation problems show that the data driven level set method is very effective when compared with alternative modeling techniques.
KW - data driven modeling
KW - fuzzy modeling
UR - https://www.scopus.com/pages/publications/85135798068
U2 - 10.1109/FUZZ-IEEE55066.2022.9882555
DO - 10.1109/FUZZ-IEEE55066.2022.9882555
M3 - Conference contribution
AN - SCOPUS:85135798068
T3 - IEEE International Conference on Fuzzy Systems
BT - 2022 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2022 at the IEEE World Congress on Computational Intelligence, WCCI 2022
Y2 - 18 July 2022 through 23 July 2022
ER -