Many real world problems need to deal with uncertainty, therefore the management of such
uncertainty is usually a big challenge. Hence, different proposals to tackle and manage the …

The need for trading off interpretability and accuracy is intrinsic to the use of fuzzy systems.
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …

A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …

The world continues to generate quintillion bytes of data daily, leading to the pressing needs
for new efforts in dealing with the grand challenges brought by Big Data. Today, there is a …

Over the past few decades, fuzzy systems have been widely used in several application
fields, thanks to their ability to model complex systems. The design of fuzzy systems has …

Abstract Evolutionary Fuzzy Systems are a successful hybridization between fuzzy systems
and Evolutionary Algorithms. They integrate both the management of imprecision …

Fuzzy systems are universally acknowledged as valuable tools to model complex
phenomena while preserving a readable form of knowledge representation. The resort to …

Classification techniques are becoming essential in the financial world for reducing risks
and possible disasters. Managers are interested in not only high accuracy, but in …

Existing research mainly uses prior knowledge to set all fuzzy sets in a fuzzy system to the
same type. In data-driven fuzzy modeling, automatically determining the type of fuzzy set is …

Fuzzy rule-based systems (FRBSs) is a rule-based system which uses linguistic fuzzy
variables as antecedents and consequent to represent human-understandable knowledge …