Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …

Intelligent algorithms can empower the development of smart manufacturing, since they can
provide optimal solutions for detection, analysis, prediction and optimization. In recent ten …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

The study proposes a novel model for DNA sequence classification that combines machine
learning methods and a pattern-matching algorithm. This model aims to effectively …

Explainability is essential for users to effectively understand, trust, and manage powerful
artificial intelligence solutions. Decision trees are one of the pioneer explanaible artificial …

This study focuses on using EEG signal-based behavioral biometric data to classify and
identify persons. A person identification system based on a nonlinear model with excellent …

We introduce two new search strategies to further improve the performance of vegetation
evolution (VEGE) for solving continuous optimization problems. Specifically, the first …

Epilepsy stands as one of the prevalent and significant neurological disorders, representing
a critical healthcare challenge. Recently, machine learning techniques have emerged as …

Decision trees (DTs) are a type of machine learning technique used for classification and
regression problems. They are considered to be a part of explainable artificial intelligence …

Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated
with high mortality rates. Approximately 80% of cases occur in cirrhotic livers, posing a …