Majdi Mafarja
Majdi Mafarja
Associate Professor of Computer Science, Birzeit University
Verified email at birzeit.edu - Homepage
Title
Cited by
Cited by
Year
Harris hawks optimization: Algorithm and applications
AA Heidari, S Mirjalili, H Faris, I Aljarah, M Mafarja, H Chen
Future generation computer systems 97, 849-872, 2019
9842019
Hybrid whale optimization algorithm with simulated annealing for feature selection
MM Mafarja, S Mirjalili
Neurocomputing 260, 302-312, 2017
6152017
Whale Optimization Approaches for Wrapper Feature Selection
M Mafarja, S Mirjalili
Applied Soft Computing 62, 441 - 453, 2017
3502017
An efficient binary salp swarm algorithm with crossover scheme for feature selection problems
H Faris, MM Mafarja, AA Heidari, I Aljarah, AZ Ala’M, S Mirjalili, H Fujita
Knowledge-Based Systems 154, 43-67, 2018
3242018
Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems
M Mafarja, I Aljarah, AA Heidari, AI Hammouri, H Faris, AZ Ala’M, ...
Knowledge-Based Systems 145, 25-45, 2018
2682018
Binary dragonfly optimization for feature selection using time-varying transfer functions
M Mafarja, I Aljarah, AA Heidari, H Faris, P Fournier-Viger, X Li, S Mirjalili
Knowledge-Based Systems 161, 185-204, 2018
2032018
Binary grasshopper optimisation algorithm approaches for feature selection problems
M Mafarja, I Aljarah, H Faris, AI Hammouri, AZ Ala’M, S Mirjalili
Expert Systems with Applications 117, 267-286, 2019
1972019
An intelligent system for spam detection and identification of the most relevant features based on evolutionary random weight networks
H Faris, AZ Ala’M, AA Heidari, I Aljarah, M Mafarja, MA Hassonah, ...
Information Fusion 48, 67-83, 2019
1542019
Asynchronous accelerating multi-leader salp chains for feature selection
I Aljarah, M Mafarja, AA Heidari, H Faris, Y Zhang, S Mirjalili
Applied Soft Computing 71, 964-979, 2018
1262018
An evolutionary gravitational search-based feature selection
M Taradeh, M Mafarja, AA Heidari, H Faris, I Aljarah, S Mirjalili, H Fujita
Information Sciences 497, 219-239, 2019
1072019
Binary dragonfly algorithm for feature selection
MM Mafarja, D Eleyan, I Jaber, A Hammouri, S Mirjalili
2017 International conference on new trends in computing sciences (ICTCS), 12-17, 2017
1042017
Hybrid Binary Ant Lion Optimizer with Rough Set and Approximate Entropy Reducts for Feature Selection
M Mafarja, S Mirjalili
Soft Computing, 2018
862018
S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem
M Mafarja, D Eleyan, S Abdullah, S Mirjalili
Proceedings of the international conference on future networks and …, 2017
592017
Boosting salp swarm algorithm by sine cosine algorithm and disrupt operator for feature selection
N Neggaz, AA Ewees, M Abd Elaziz, M Mafarja
Expert Systems with Applications 145, 113103, 2020
582020
Ant Lion Optimizer: Theory, Literature Review, and Application in Multi-layer Perceptron Neural Networks
AA Heidari, H Faris, S Mirjalili, I Aljarah, M Mafarja
Nature-Inspired Optimizers, 23-46, 2019
582019
Clustering analysis using a novel locality-informed grey wolf-inspired clustering approach
I Aljarah, M Mafarja, AA Heidari, H Faris, S Mirjalili
Knowledge and Information Systems 62 (2), 507-539, 2020
562020
Salp Swarm Algorithm: Theory, Literature Review, and Application in Extreme Learning Machines
H Faris, S Mirjalili, I Aljarah, M Mafarja, AA Heidari
Nature-Inspired Optimizers, 185-199, 2019
542019
Feature selection using salp swarm algorithm with chaos
S Ahmed, M Mafarja, H Faris, I Aljarah
2nd International Conference on Intelligent Systems, Metaheuristics & Swarm …, 2018
542018
Dragonfly Algorithm: Theory, Literature Review, and Application in Feature Selection
M Mafarja, AA Heidari, H Faris, S Mirjalili, I Aljarah
Nature-Inspired Optimizers, 47-67, 2019
502019
Time-varying hierarchical chains of salps with random weight networks for feature selection
H Faris, AA Heidari, AZ Ala’M, M Mafarja, I Aljarah, M Eshtay, S Mirjalili
Expert Systems with Applications 140, 112898, 2020
492020
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