The present study examines the role of feature selection methods in optimizing machine
learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with …

Selection of a suitable general circulation model (GCM) ensemble is crucial for effective
water resource management and reliable climate studies in developing countries with …

In this study, we present a transfer learning method for gesture classification via an inductive
and supervised transductive approach with an electromyographic dataset gathered via the …

The forecasting of electricity load is an important task for the proper functioning of power
system utilities. In the modern era, the dimension of the dataset becomes the barrier for …

Climate change and awareness of the need to care for the environment have resulted in a
global increase in the interest in renewable energy sources. The European Union (EU) is …

Rooftop solar photovoltaic (PV) systems, commonly referred to as distributed generation
(DG) solar systems, are deemed important contenders in future sustainable cities. Because …

Frequent geopolitical events have reduced the stability of natural gas supply and caused
drastic price fluctuations, which poses a new challenge to the natural gas consumer market …

This study aims at designing Map Reduce and federated learning-based asthma prediction
model for adolescent to provide answers to the problems associated with the existing …

Customer research is one of the important aspects of understanding customer behavior
patterns with business enterprises and predicate how consumer satisfaction is achieved …

Fog computing is a type of distributed computing that makes data storage and computation
closer to the network edge. While fog computing o® ers numerous advantages, it also …