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The role of Reinforcement Learning in software testing
Published 2023“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”
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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach
Published 2025“…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. …”
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Identification of phantom movements with an ensemble learning approach
Published 2022“…The ensemble learning-based approaches outperformed the SVM, Decision tree, and kNN methods. …”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …”
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Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
Published 2002“…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …”
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170
Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
Published 2013“…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …”
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171
Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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172
A machine learning approach for localization in cellular environments
Published 2018“…A machine learning approach is developed for localization based on received signal strength (RSS) from cellular towers. …”
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LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”
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Using machine learning to support students’ academic decisions
Published 2019“…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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177
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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