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 …

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 …

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 …

Among various biometric systems, an offline signature verification system has been widely
used in all fields such as in banks, educational institutes, legal procedures and, criminal …

Feature selection (FS) is a crucial area of cognitive computation that demands further
studies. It has recently received a lot of attention from researchers working in machine …

This study attempts to maintain the terminal voltage level of an automatic voltage regulator
(AVR) and control the speed of a direct current (DC) motor using a fractional order …