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Salama A. Mostafa
Researcher at Universiti Tun Hussein Onn Malaysia
Publications - 177
Citations - 3344
Salama A. Mostafa is an academic researcher from Universiti Tun Hussein Onn Malaysia. The author has contributed to research in topics: Computer science & Autonomous agent. The author has an hindex of 25, co-authored 142 publications receiving 1751 citations. Previous affiliations of Salama A. Mostafa include Universiti Tenaga Nasional & College of Information Technology.
Papers
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Journal ArticleDOI
Solving vehicle routing problem by using improved genetic algorithm for optimal solution
Mazin Abed Mohammed,Mazin Abed Mohammed,Mohd Khanapi Abd Ghani,Raed I. Hamed,Salama A. Mostafa,Mohd Sharifuddin Ahmad,Dheyaa Ahmed Ibrahim +6 more
TL;DR: A genetic algorithm is used to solve the Capacitated Vehicle Routing Problem (CVRP) model for optimizing UNITEN’s shuttle bus services and shows that the proportion of reduction the distance is relatively short, but the savings in the distance becomes greater when calculating the total distances traveled by all buses daily or monthly.
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Benchmarking Methodology for Selection of Optimal COVID-19 Diagnostic Model Based on Entropy and TOPSIS Methods
Mazin Abed Mohammed,Karrar Hameed Abdulkareem,Alaa S. Al-Waisy,Salama A. Mostafa,Shumoos Al-Fahdawi,Ahmed M. Dinar,Wajdi Alhakami,Abdullah Baz,Mohammed Nasser Al-Mhiqani,Hosam Alhakami,Nureize Arbaiy,Mashael S. Maashi,Ammar Awad Mutlag,Begona Garcia-Zapirain,Isabel de la Torre Díez +14 more
TL;DR: The study results revealed that the benchmarking and selection problems associated with COVID19 diagnosis models can be effectively solved using the integration of Entropy and TOPSIS.
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Benchmarking of Machine Learning for Anomaly Based Intrusion Detection Systems in the CICIDS2017 Dataset
Ziadoon Kamil Maseer,Robiah Yusof,Nazrulazhar Bahaman,Salama A. Mostafa,Cik Feresa Mohd Foozy +4 more
TL;DR: 10 popular supervised and unsupervised ML algorithms for identifying effective and efficient ML–AIDS of networks and computers are applied and the true positive and negative rates, accuracy, precision, recall, and F-Score of 31 ML-AIDS models are evaluated.
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Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson’s disease
Salama A. Mostafa,Aida Mustapha,Mazin Abed Mohammed,Raed I. Hamed,N. Arunkumar,Mohd Khanapi Abd Ghani,Mustafa Musa Jaber,Shihab Hamad Khaleefah +7 more
TL;DR: Results show that the MFEA of the multi-agent system finds the best set of features and improves the performance of the classifiers’ diagnosis results.
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Neural network and multi-fractal dimension features for breast cancer classification from ultrasound images
Mazin Abed Mohammed,Mazin Abed Mohammed,Belal Al-Khateeb,Ahmed Noori Rashid,Dheyaa Ahmed Ibrahim,Mohd Khanapi Abd Ghani,Salama A. Mostafa +6 more
TL;DR: An effort to automate characterization of breast cancer from ultrasound images using multi-fractal dimensions and backpropagation neural networks is presented.