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Boosting Atomic Orbit Search Using Dynamic-Based Learning for Feature Selection
Faculty
Science
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Rehab Aly Ibrahim Muhammed
Staff Zu Site
Abstract In Staff Site
Journal:
Mathematics MDPI
Volume:
Keywords :
Boosting Atomic Orbit Search Using Dynamic-Based
Abstract:
Feature selection (FS) is a well-known preprocess step in soft computing and machine learning algorithms. It plays a critical role in different real-world applications since it aims to determine the relevant features and remove other ones. This process (i.e., FS) reduces the time and space complexity of the learning technique used to handle the collected data. The feature selection methods based on metaheuristic (MH) techniques established their performance over all the conventional FS methods. So, in this paper, we presented a modified version of new MH techniques named Atomic Orbital Search (AOS) as FS technique. This is performed using the advances of dynamic opposite-based learning (DOL) strategy that is used to enhance the ability of AOS to explore the search domain. This is performed by increasing the diversity of the solutions during the searching process and updating the search domain. A set of eighteen datasets has been used to evaluate the efficiency of the developed FS approach, named AOSD, and the results of AOSD are compared with other MH methods. From the results, AOSD can reduce the number of features by preserving or increasing the classification accuracy better than other MH techniques.
Author Related Publications
Rehab Aly Ibrahim Muhammed, "Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary", International Journal of Computer Applications, 2012
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Rehab Aly Ibrahim Muhammed, "Cooperative Meta-heuristic Algorithms for Global Optimization Problems", Elseveir, 2021
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Rehab Aly Ibrahim Muhammed, "Efficient artificial intelligence forecasting models for COVID-19outbreak in Russia and Brazil", Elseveir, 2021
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Rehab Aly Ibrahim Muhammed, "Automatic clustering method to segment COVID-19 CT images", ٍٍSpringer, 2021
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Rehab Aly Ibrahim Muhammed, "Fractional Calculus-Based Slime Mould Algorithm for Feature Selection Using Rough Set", IEEE, 2021
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Department Related Publications
Rodyna Ahmed Mahmoud, "Proximity structures and grill", ijser, 2013
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Heba Ibrahim Mustafa, "On rough approximations via ideal", Elsevier, 2013
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Heba Ibrahim Mustafa, "Soft Generalized Closed Sets with Respect to an Ideal in Soft Topological Spaces", Natural science publishing USA, 2014
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Heba Ibrahim Mustafa, "Hybridizing Rough Sets and Double Sets (An approach for increasing decision accuracy)", Acta Zhengzhou University Overseas, 2013
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Alaa Hassan Attia Hassan, "On subordination results for certain new classes of analytic functions defined by using Salagean operator", Universiteti i Prishtines, Prishtine, Kosove, 2012
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