In this paper, a novel fuzzy neural network termed as dynamic parsimonious fuzzy neural network (DPFNN) is proposed. DPFNN is a four layers network, which features coalescence …
E Lughofer - Handbook on Computer Learning and Intelligence …, 2022 - World Scientific
This chapter provides an all-round picture of the development and advances in the fields of evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …
SW Tung, C Quek, C Guan - Information Sciences, 2013 - Elsevier
There are two main approaches to design a neural fuzzy system; namely, through expert knowledge, and through numerical data. While the computational structure of a system is …
As one of the three pillars in computational intelligence, fuzzy systems are a powerful mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
Most of the dynamics in real-world systems are compiled by shifts and drifts, which are uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in …
MNM Salleh, N Talpur, K Hussain - Data Mining and Big Data: Second …, 2017 - Springer
Adaptive neuro-fuzzy inference system (ANFIS) is efficient estimation model not only among neuro-fuzzy systems but also various other machine learning techniques. Despite …
JS Wang, CSG Lee - IEEE Transactions on Fuzzy systems, 2002 - ieeexplore.ieee.org
This paper presents a self-adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base …
E Lughofer - Handbook on computational intelligence: volume 1 …, 2016 - World Scientific
This chapter provides a round picture of the development and advances in the field of evolving fuzzy systems (EFS) made during the last decade since their first appearance in …
Fuzzy and neural-fuzzy systems have successfully and extensively applied to solve problems in many research areas such as those associated with industrial, medical and …