The extended belief rule-based (EBRB) system is shown to have the potential to handle both
quantitative and qualitative information under uncertainty, and it has been used as an …

We propose a new evolving fuzzy classifier approach termed as EFC-RNG (Evolving Fuzzy
Classifier based on Robust Neural Gas) acting in a fully single-pass, sample-wise …

This paper extends the recently conceived learning mechanism called EVeP (Extreme Value
evolving Predictor), an evolving fuzzy-rule-based predictor characterized by innovative …

Nowadays, biometric systems have emerged as a powerful tool for personal identification.
Advanced research with significant results has been provided. Despite the important …

In the era of big data, huge amounts of data are generated and updated every day, and their
processing and analysis is an important challenge today. In order to tackle this challenge, it …

This paper introduces an evolving hybrid fuzzy neural network-based modeling approach
using neurons based on uninorms and sigmoidal activation functions in a feed forward …

This paper presents the design and experimental validation of a new model-free data-driven
iterative reference input tuning (IRIT) algorithm that solves a reference trajectory tracking …

Machine learning has arisen with advanced data analytics. Many factors influence crop
yield, such as soil, amount of water, climate, and genotype. Determining factors that …

This paper introduces an innovative adaptive hybrid Particle Swarm Optimization (PSO)-
Gravitational Search Algorithm (GSA) dedicated to the optimal tuning of Takagi-Sugeno …

Time series forecasting is widely used to predict future values in several applications, such
as climate, industries demand, stock markets and business strategies. Fuzzy set based time …