Moth–flame optimization algorithm: variants and applications
This paper thoroughly presents a comprehensive review of the so-called moth–flame
optimization (MFO) and analyzes its main characteristics. MFO is considered one of the …
optimization (MFO) and analyzes its main characteristics. MFO is considered one of the …
A comprehensive review of moth-flame optimisation: variants, hybrids, and applications
ABSTRACT Moth-flame Optimisation Algorithm (MFO) is a new metaheuristics optimisation
algorithm presented by Mirjalili in 2015 which inspired by the navigation method of moths in …
algorithm presented by Mirjalili in 2015 which inspired by the navigation method of moths in …
An efficient binary salp swarm algorithm with crossover scheme for feature selection problems
Searching for the (near) optimal subset of features is a challenging problem in the process of
feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior …
feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior …
Binary dragonfly optimization for feature selection using time-varying transfer functions
Abstract The Dragonfly Algorithm (DA) is a recently proposed heuristic search algorithm that
was shown to have excellent performance for numerous optimization problems. In this …
was shown to have excellent performance for numerous optimization problems. In this …
Feature selection via a novel chaotic crow search algorithm
Crow search algorithm (CSA) is a new natural inspired algorithm proposed by Askarzadeh
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …
An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
Abstract Detection of Denial of Service (DoS) attack is one of the most critical issues in cloud
computing. The attack detection framework is very complex due to the nonlinear thought of …
computing. The attack detection framework is very complex due to the nonlinear thought of …
Orthogonal Nelder-Mead moth flame method for parameters identification of photovoltaic modules
Defining the optimal parameters of the photovoltaic system (PV) models according to the
actual real voltage and current data is a crucial process during designing, emulating …
actual real voltage and current data is a crucial process during designing, emulating …
Binary dragonfly algorithm for feature selection
Wrapper feature selection methods aim to reduce the number of features from the original
feature set to and improve the classification accuracy simultaneously. In this paper, a …
feature set to and improve the classification accuracy simultaneously. In this paper, a …
Improved Slime Mould Algorithm based on Firefly Algorithm for feature selection: A case study on QSAR model
Feature selection (FS) methods are necessary to develop intelligent analysis tools that
require data preprocessing and enhancing the performance of the machine learning …
require data preprocessing and enhancing the performance of the machine learning …
An optimized framework for breast cancer classification using machine learning
Breast cancer, if diagnosed and treated early, has a better chance of surviving. Many studies
have shown that a larger number of ultrasound images are generated every day, and the …
have shown that a larger number of ultrasound images are generated every day, and the …