The determination of fuzzy information granules including the estimation of their
membership functions play a significant role in fuzzy system design as well as in the design …

In traditional fuzzy classification systems, learning is done from a stationary data distribution.
In online rule learning, however, data are non-stationary and change dynamically over time …

In this paper, an adaptive fuzzy classifier for online rule learning from real-time data streams
is proposed. These kinds of data have some limitations which make them different from …

Fuzzy Rule-Based Classification Systems (FRBCS) are highly investigated by researchers
due to their noise-stability and interpretability. Unfortunately, generating a rule-base which is …

Today, when it comes to selecting the most appropriate bridge type and defining its
respective component and properties, no systematic procedure exists when the bridge is still …

There are some well-known classifiers which in special conditions, not only have a similar
structure, but also show equal behavior in classifying any instance. This paper is aimed at …

Choosing the number of fuzzy rules and setting the membership functions constitutes the
difficult tasks in the process of designing fuzzy systems and fuzzy rule basedclassifiers. The …

The ability to learn new things is one of the main characteristics of intelligent behavior. It is
this that enables us humans to recognize patterns and to generalize following the structures …

Selecting a new bridge type at the conceptual design phase is subject to many weaknesses
in the processes conducted. Given that the engineers' decisions are based on their …