Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

Meta heuristics is an optimization approach that works as an intelligent technique to solve
optimization problems. Evolutionary algorithms, human-based algorithms, physics-based …

Abstract Emperor Penguin Optimizer (EPO) is a metaheuristic algorithm which is recently
developed and illustrates the emperor penguin's huddling behaviour. However, the original …

Feature selection is one of the important techniques of dimensionality reduction in data
preprocessing because datasets generally have redundant and irrelevant features that …

Deep learning (DL) driven cardiac image processing methods manage and monitor the
massive medical data collected by the internet of things (IoT) based on wearable devices. A …

Text obtained in natural scenes contains various information; therefore, it is extensively used
in various applications to understand the image scenarios and also to retrieve the visual …

Today due to the important environmental effects of the building sector, the utilization of
sustainable energy sources should be taken into account by designers. For the optimization …

Prediction of the energy consumed by household appliances is a challenging research topic
owing to a transition toward the Internet of Everything. Although classical machine learning …

The search for powerful optimizers has led to the development of a multitude of
metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom …

This study introduces the extension of currently developed Emperor Penguin Optimizer
(EPO) in terms of multi-objective problems solving capability, which is entitled as Multi …