Tuning of a fuzzy logic power system stabilizer using geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal or near optimal settings of fuzzy logic power system stabilizer (FLPSS) parameters. …”
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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks by Al Hashimi, Rashid

“…Multi-agent reinforcement learning is a common method for optimizing agents' local decision in a distributed and scalable manner. …”
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ISSP by Zouein, P.P.

“…The underlying algorithms optimize positions of resources by minimizing handling and rehandling costs of these on site. …”
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Towards Multimedia Fragmentation by Saad, Samir

“…In this paper, we address multimedia database fragmentation by extending existing fragmentation algorithms to take into account key characteristics of multimedia objects. …”
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Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound by Abdel-Hafez, Mamoun

“…The proposed algorithms are first tested using a simulation environment. …”
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Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…Experimental results demonstrated that DL algorithms leveraging sampling methods perform significantly worse than the decision tree-based ensemble method. …”

A fine-grained XML structural comparison approach by Tekli, Joe

“…Our approach consists of two main algorithms for discovering the structural commonality between sub-trees and computing tree-based edit operations costs. …”
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On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity by Sweidan, Zahraa

“…We de ne the constraints of the problem, model it as a Markov Decision Process, and propose a reinforcement learning-based solution to optimize the UAV trajectory. Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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A Highly Efficient And Automated Approach To Identifying And Classifying Urban Traffic Images Using Self Organizing Maps and Artificial Intelligence. (c2006) by Bey, Hisham Mardam

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Dynamic multiple node failure recovery in distributed storage systems by Itani, May

“…We present a range of results for our proposed algorithms in several scenarios to assess the effectiveness of the solution approaches that are shown to generate results close to optimal.…”
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Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters by Farhan, Abid

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Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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SemIndex: Semantic-Aware Inverted Index by Chbeir, Richard

“…Preliminary results have demonstrated the effectiveness, scalability and optimality of our approach.…”
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Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…Five machine learning algorithms were evaluated: XGBoost, AdaBoost, random forest, decision tree, and multi-layer perceptron (MLP) classifier. …”

A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques by SALLOUM, SAID

“…The findings include that the main research area in phishing detection studies is feature extraction and selection, followed by methods for classifying and optimizing the detection of phishing emails. Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. …”
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Predicting Android Malware Using Evolution Networks by Chahine, Joy

“…We combine this model with genetic algorithms to optimize its parameters and return the best state transition probabilities, and we predict future malware accordingly. …”
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Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning by Moussa, Mostafa Mohamed

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Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter by Yahia, Mohamed

“…The recent advancement in synthetic aperture radar (SAR) technology has enabled high-resolution imaging capability that calls for efficient speckle filtering algorithms to preprocess radar imagery. Since the introduction of the Lee sigma filter in 1980, the various versions of the minimum mean square error (MMSE) filter were developed, focusing essentially on how to estimate the processed pixels. …”
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Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review by SHEHADEH, KHADIJA

“…Irrespective of the adopted processes for corrosion monitoring, it was concluded that none of these methods represent an optimum solution by itself, where employing a combination of multiple systems is one way of optimizing its results. New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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