In order to determine the parameters of belief-rule-base (BRB) accurately, several
optimization methods have been proposed for training BRB, on the basis of a generic rule …

In the cases of designing fuzzy control systems, tuning and optimizing fuzzy controllers are
challenging problems. This work proposes an optimal fuzzy system to control the operations …

A belief rule base inference methodology using the evidential reasoning (RIMER) approach
has been developed recently. A belief rule base (BRB), which can be treated as a more …

An efficient approach is presented to improve the local and global approximation and
modelling capability of Takagi–Sugeno (T–S) fuzzy model. The main aim is obtaining high …

In engineering practice, a system's behavior constantly changes over time. To predict the
behavior of a complex engineering system, a model can be built and trained using historical …

Heterogeneous feature transfer (HeFT) learning can leverage the semantically related
source domain from a different feature space for modeling the target domain with insufficient …

Different from the dominant view of treating fuzzy reasoning as generalization of classical
logical inference, in this paper fuzzy reasoning is treated as a control problem. A new fuzzy …

To predict the behavior of a complex engineering system, a model can be built and trained
using historical data. However, it may be difficult to obtain a complete and accurate set of …

Two new and efficient approaches are presented to improve the local and global estimation
of the Takagi‐Sugeno (T‐S) fuzzy model. The main aim is to obtain high function …

This paper presents an evolutionary optimal fuzzy system with information fusion of
heterogeneous distributed computing and polar-space dynamic model for online motion …