The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Metaheuristic algorithms are widely used in various fields of optimization engineering.
These algorithms have become popular because of their ability to explore and exploit …

Abstract Chimp Optimization Algorithm (ChoA) is a recently developed meta-heuristic
approach which is inspired by the individual intelligence and sexual motivation of chimps. It …

Harris hawk optimization (HHO) is one of the recently proposed metaheuristic algorithms
that has proven to be work more effectively in several challenging optimization tasks …

Feature selection (FS), an important pre-processing step in the fields of machine learning
and data mining, has immense impact on the outcome of the corresponding learning …

Abstract The Proton Exchange Membrane Fuel Cell (PEMFC) is considered as one of the
most promising energy conversion technologies of the future due to its enormous …

Feature selection is a technique commonly used in Data Mining and Machine Learning.
Traditional feature selection methods, when applied to large datasets, generate a large …

Computations that mimic nature are known as nature-inspired computing. Nature presents a
wealthy source of thoughts and ideas for computing. The use of natural galvanized …

Feature selection is a real-world problem that finds a minimal feature subset from an original
feature set. A good feature selection method, in addition to selecting the most relevant …

There are various fields are affected by the growth of data dimensionality. The major
problems which are resulted from high dimensionality of data including high memory …