Hybrid approaches to optimization and machine learning methods: a systematic literature review
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
Evolutionary inspired approach for mental stress detection using EEG signal
Stress is a pensive issue in our competitive world and it has a huge impact on physical and
mental health. Severe health issues may arise due to long exposure of stress. Hence, its …
mental health. Severe health issues may arise due to long exposure of stress. Hence, its …
An evolutionary fake news detection method for covid-19 pandemic information
As the COVID-19 pandemic rapidly spreads across the world, regrettably, misinformation
and fake news related to COVID-19 have also spread remarkably. Such misinformation has …
and fake news related to COVID-19 have also spread remarkably. Such misinformation has …
Memory-based Harris hawk optimization with learning agents: a feature selection approach
Feature selection is a vital pre-processing phase for most machine learning and data mining
courses. This article proposes new variants of the Harris hawk optimization called memory …
courses. This article proposes new variants of the Harris hawk optimization called memory …
A hierarchical multi-leadership sine cosine algorithm to dissolving global optimization and data classification: The COVID-19 case study
M Zhong, J Wen, J Ma, H Cui, Q Zhang… - Computers in Biology and …, 2023 - Elsevier
Abstract The Sine Cosine Algorithm (SCA) is an outstanding optimizer that is appreciably
used to dissolve complicated real-world problems. Nevertheless, this algorithm lacks …
used to dissolve complicated real-world problems. Nevertheless, this algorithm lacks …
A multi-layer classification approach for intrusion detection in iot networks based on deep learning
The security of IoT networks is an important concern to researchers and business owners,
which is taken into careful consideration due to its direct impact on the availability of the …
which is taken into careful consideration due to its direct impact on the availability of the …
[HTML][HTML] Support Vector Machine with feature selection: A multiobjective approach
Abstract Support Vector Machines are models widely used in supervised classification. The
classical model minimizes a compromise between the structural risk and the empirical risk …
classical model minimizes a compromise between the structural risk and the empirical risk …
Competitive Swarm Optimizer: A decade survey
Since its inception in 2014, the Competitive Swarm Optimizer (CSO) has emerged as a
significant advancement in the field of swarm intelligence, particularly in addressing large …
significant advancement in the field of swarm intelligence, particularly in addressing large …
An evolutionary-based sentiment analysis approach for enhancing government decisions during COVID-19 pandemic: The case of jordan
The world has witnessed recently a global outbreak of coronavirus disease (COVID-19).
This pandemic has affected many countries and has resulted in worldwide health concerns …
This pandemic has affected many countries and has resulted in worldwide health concerns …
Evolutionary support vector regression for monitoring Poisson profiles
Many researchers have shown interest in profile monitoring; however, most of the
applications in this field of research are developed under the assumption of normal …
applications in this field of research are developed under the assumption of normal …