booktitle = "2015 IEEE Congress on Evolutionary Computation (CEC)",
title = "Evolutionary multi-objective optimization for evolving
hierarchical fuzzy system",
year = "2015",
pages = "3163--3170",
isbn13 = "978-1-4799-7491-7",
abstract = "In this paper, a Multi-Objective Extended Genetic
Programming (MOEGP) algorithm is developed to evolve
the structure of the Hierarchical Flexible Beta Fuzzy
System (HFBFS). The proposed algorithm allows finding
the best representation of the hierarchical fuzzy
system while trying to attain the desired balance of
accuracy/interpretability. Furthermore, the free
parameters (Beta membership functions and the
consequent parts of rules) encoded in the best
structure are tuned by applying the hybrid Bacterial
Foraging Optimisation Algorithm (the hybrid BFOA). The
proposed methodology interleaves both MOEGP and the
hybrid BFOA for the structure and the parameter
optimisation respectively until a satisfactory HFBFS is
found. The performance of the approach is evaluated
using several classification datasets with low and high
input dimensions. Results prove the superiority of our
method as compared with other existing works.",