This work presents a design of interval type-2 fuzzy brain emotional learning control
(T2FBELC) combining with the self-evolving algorithm to help the network to automatically …

This paper introduces an optimized model of brain emotional learning (BEL) that merges the
Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) for …

This study proposes a new efficient predictor called a three-dimensional (3D) membership
function-based Type-2 Fuzzy Brain-Emotional Learning Predictor (T2FBELP) to model and …

In this article, the new cognitive model convolutional brain emotional learning (CBEL) is
introduced to recognize emotional speech on the Berlin dataset. This model is an improved …

This study presents a multidimensional classifier design using a fuzzy brain emotional
learning model, combined with a particle swarm optimization (PSO) algorithm that allows a …

Brain emotional learning (BEL) model has been used frequently for predicting a quantity or
modeling complex and nonlinear systems in recent years. In this research, two methods …

This paper studies the H∞ tracking control for uncertain nonlinear multivariable systems. We
propose a control strategy, which combines the adaptive wavelet-type Takagi-Sugeno-Kang …

Microgrids (MGs) are building blocks of smart power systems formed by integrating local
power generation resources, energy storage systems, and power-consuming units. While …

A novel interval type‐2 intuition fuzzy brain emotional learning network model (IT2IFBELC)
which depends only on the input and output data is proposed for the rehabilitation robot …

Speech emotion signals are the quickest and most neutral method in individuals'
relationships, leading researchers to develop speech emotion signal as a quick and efficient …