This paper aims at providing an in-depth overview of designing interpretable fuzzy inference
models from data within a unified framework. The objective of complex system modelling is …

Information granules are complex entities that arise in the process of abstraction of data and
derivation of knowledge. The automatic generation of information granules from data is an …

Fuzzy modeling of high-dimensional systems is a challenging topic. This paper proposes an
effective approach to data-based fuzzy modeling of high-dimensional systems. An initial …

Abstract Fuzzy model identification is an effective tool for the approx-imation of uncertain
nonlinear systems on the basis of measured data. The identification of a fuzzy model using …

Abstract System modeling with fuzzy rule-based systems (FRBSs), ie fuzzy modeling (FM),
usually comes with two contradictory requirements in the obtained model: the interpretability …

This paper proposes a novel approach for building transparent knowledge-based systems
by generating accurate and interpretable fuzzy rules. The learning mechanism reported here …

Radial basis function networks and fuzzy rule systems are functionally equivalent under
some mild conditions. Therefore, the learning algorithms developed in the field of artificial …

Develo** Takagi–Sugeno fuzzy models by evolutionary algorithms mainly requires three
factors: an encoding scheme, an evaluation method, and appropriate evolutionary …

This chapter deals with low-level transparency of fuzzy systems that is necessary to ensure
reliable interpretation of linguistic information provided by fuzzy systems. It is shown that for …

Fuzzy systems are commonly considered suitable tools to express knowledge in a human
comprehensible fashion. This kind of characterization makes them eligible for being applied …