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A new fusion of grey wolf optimizer algorithm with a two-phase mutation for feature selection
Faculty
Computer Science
Year:
2019
Type of Publication:
ZU Hosted
Pages:
Authors:
Ibrahiem Mahmoud Mohamed Elhenawy
Staff Zu Site
Abstract In Staff Site
Journal:
Expert Systems with Applications Elsevier
Volume:
Keywords :
, , fusion , grey wolf optimizer algorithm with
Abstract:
Because of their high dimensionality, dealing with large datasets can hinder the data mining process. Thus, the feature selection is a pre-process mandatory phase for reducing the dimensionality of datasets through using the most informativ
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Ibrahiem Mahmoud Mohamed Elhenawy, "A Review on the Applications of Neutrosophic Sets", Source: Journal of Computational and Theoretical Nanoscience, Volume 13, Number 1, January 2016, pp. 936-944(9), 2016
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Ibrahiem Mahmoud Mohamed Elhenawy, "Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization", Springer, 2017
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Department Related Publications
Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019
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Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014
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Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015
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Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013
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Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014
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