Contemporary advancements in technology provide vast quantities of data with large
dimensions, leading to high computing burdens. These big data quantities suffer from …

This work presents an innovative deep-learning approach for multi-variate optimization,
focusing on the identification of Mg (OH) 2 precipitation kinetics parameters. The study …

Corn steep liquor is a waste product from the process of treating corn grain for starch
extraction. It is used as a substrate in anaerobic digestion with simultaneous hydrogen and …

Optimization algorithms are popular to solve different problems in many fields, and are
inspired by natural principles, animal living habits, plant pollinations, chemistry principles …

Extreme weather events pose significant risks to power systems, necessitating effective risk
forewarning and management strategies. A few existing researches have concerned the …

Feature selection plays a crucial role in establishing an effective speech emotion recognition
system. To improve recognition accuracy, people always extract as many features as …

Feature selection is the process of extracting an optimal subset feature from a primary
feature set to minimize data dimensionality. The hybrid metaheuristic is the most common …

Background COVID-19 is a global public health problem. Aim The main objective of this
research is to evaluate and compare the performance of the algorithms: Random Forest …

This Special Issue focuses on advancing research on algorithms, with a particular emphasis
on feature selection techniques. A key focus is the broad subject of scheduling, aiming to …

The need for renewable energy sources in addressing global energy demands is growing,
especially in Nigeria where electricity demand often exceeds supply. Solar photovoltaic (PV) …