Abstract AutoML (Automated Machine Learning) is an emerging field that aims to automate
the process of building machine learning models. AutoML emerged to increase productivity …

Artificial neural networks (ANN), machine learning (ML), deep learning (DL), and ensemble
learning (EL) are four outstanding approaches that enable algorithms to extract information …

Accurate forecasting of carbon dioxide (CO 2) emissions is crucial for achieving carbon
neutrality early, as CO 2 is the primary component of greenhouse gases. The time series of …

The Zero-touch network and Service Management (ZSM) framework represents an
emerging paradigm in the management of the fifth-generation (5G) and Beyond (5G+) …

The data generated exponentially by a massive number of devices in the Internet of Things
(IoT) are extremely high-dimensional, large-scale, non-labeled, which poses great …

Abstract A Cluster-Based Wireless Sensor Network (CBWSN) is a system designed to
remotely control and monitor specific events or phenomena in areas such as smart grids …

Over the last few years, substantial research has been conducted towards develo**
efficient abnormal detection techniques while considering efficiency, accuracy, high …

In this paper, we built an automated machine learning (AutoML) pipeline for structure-based
learning and hyperparameter optimization purposes. The pipeline consists of three main …

The ever-increasing complexity of the Internet of Things (IoT) environment demands robust
and adaptable intrusion detection frameworks, as existing approaches struggle with real …

The integration of the Internet of Things (IoT) and artificial intelligence (AI) in urban
infrastructure, powered by advanced information communication technologies (ICT), has …