Improved search-tree algorithms for the cluster edit problem. (c2011) by Ghrayeb, Ali Kassem

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Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

Efficient methods and techniques for the open-shop scheduling problem. (c2006) by Bou Ghosn, Steve

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Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

“…<p>Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EEG analysis, and facilitate tailored therapeutic strategies, addressing the complexities of epilepsy management. …”

A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks by Yassine Himeur (14158821)

“…Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. …”

A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

“…Therefore, we proposed a Deep Reinforcement Learning (DRL) solution based on Deep Deterministic Policy Gradient (DDPG) algorithm to solve the highly complex SC problem by adjusting the BF weights and mirror orientations. …”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…However, AI tools, for instance, Machine Learning (ML) and Deep Learning (DL), offer precise and well-timed solutions for disease detection, classification, and eradication. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This approach uses other students’ grades to make a prediction. 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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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”

Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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Adaptive Time-Varying Brain Source Localization by Al-Momani, Sajedah A.

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Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…Conventional Building Energy Management methods suffer from a high dimensional and complex control environment. In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”

YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

“…It has recently become increasingly popular to apply deep learning algorithms to the identification of ships in SAR images. …”

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

“…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Discrepancies between the dynamic system models (DSM) and anomaly detection and deep learning (ADL) require in-depth localized off-line simulations. …”