A fuzzy inference system consists of a machine learning concept that combines accuracy
and interpretability. They are divided into two main groups: Mamdani and Takagi–Sugeno …

This paper extends our recent work about dropout for the design of Takagi–Sugeno–Kang
(TSK) fuzzy classifiers, ie, fuzzy-knowledge-out, to the generalized concept, ie, fuzzy rule …

This study made the digital system to perform screening (early prediction) of Hypoxemia
using MAX30102 sensor with the fuzzy value from SpO2 level and heart rate. This research …

Takagi-Sugeno (TS) fuzzy model offers a general and systematic framework to represent a
nonlinear plant and provides an effective platform to facilitate stability analysis and control …

In the regression analysis, Takagi-Sugeno fuzzy model gives a way of exploiting fuzzy logic
to tackle nonlinear issues. However, the general Takagi-Sugeno fuzzy model encounters …

The multi-view fuzzy learning method, due to its ability to comprehensively explore feature
information and possess good interpretability, has been widely used in the field of disease …

This research paper presents the design and simulation of the proportional integral
derivative (PID) controller whose gains are controlled by an adaptive fuzzy tuning …

Admittedly, it is of paramount guiding significance to construct a scientific comprehensive
evaluation system for university teachers' teaching performance to promote the overall …

This study focuses on discussing how fuzzy logic can be used in temperature control
systems. To avoid unsuitable and excessive performance as a result of the growing number …

The structure of any Bangla numerical character is more complex compared to English
numerical character. Two pairs of numerical character in Bangla resembles to be closed and …