Imbalanced classification is a well-known challenge faced by many real-world applications.
This issue occurs when the distribution of the target variable is skewed, leading to a …

There are a plethora of invented classifiers in Machine learning literature, however, there is
no optimal classifier in terms of accuracy and time taken to build the trained model …

Big data is a large set of data that is analyzed with the calculation to manifest myriad
sources. Big data is capable of handling various challenges to processing huge amounts of …

The capacity to interact with environments, understand them, and make judgments on time
defines smartness, the foundation of smart cities, and civilizations. The main motivation of …

Big data mining has emerged as an active field of interest, and traditional data mining
approaches frequently fail to handle the complexities associated with massive datasets. One …

Predicting electrical power consumption is essential in many industries. This paper presents
a method to predict total electrical power consumption in a certain period of Hot Rolling Mill …

Edge-cloud applications are rapidly prevailing in recent years and pose the challenge of
using both resource-strenuous edge devices and elastic cloud resources under dynamic …

Big data refers to vast volumes of structured and unstructured data that are too large or
complex for traditional data-processing methods to handle efficiently. The importance of big …

As a main type of colorectal cancer, rectal cancer has a high risk and mortality rate so it is
very important to accurately predict the survivability of patients to make better decisions on …

This paper proposes an optimized convolutional neural network-based tapered nine-core
optical fiber (CNN-TNOF) structure for the measurement of temperature and refractive index …