This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

Phishing email is one of the major problems of today's Internet, resulting in financial losses
for organizations and annoying individual users. Numerous approaches have been …

Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …

This paper proposes a new method in construction fuzzy neural network to forecast travel
speed for multi-step ahead based on 2-min travel speed data collected from three remote …

This paper introduces a new type of fuzzy inference systems, denoted as dynamic evolving
neural-fuzzy inference system (DENFIS), for adaptive online and offline learning, and their …

An approach to the online learning of Takagi-Sugeno (TS) type models is proposed in the
paper. It is based on a novel learning algorithm that recursively updates TS model structure …

This research develops a weighted evolving fuzzy neural network for PCB sales forecasting
and it includes four major steps: first of all, collecting 15 factors among macroeconomic data …

This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …

This second edition of the must-read work in the field presents generic computational
models and techniques that can be used for the development of evolving, adaptive modeling …

The integration of neural networks and fuzzy inference systems could be formulated into
three main categories: cooperative, concurrent and integrated neuro-fuzzy models. We …