A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation حسب Kfouri, Ronald

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Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review حسب Ruba, Sulaiman

"…Most of the included studies focused on mortality prediction, utilizing datasets of varying sizes and diverse ML algorithms. The most employed ML algorithms were random forest, logistics regression, and gradient boosting. …"
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Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review حسب Ruba Sulaiman (17734065)

"…</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Medical Informatics<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmedinf.2025.105840" target="_blank">https://dx.doi.org/10.1016/j.ijmedinf.2025.105840</a></p>…"

Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning حسب Mohamed Massaoudi (16888710)

"…Additionally, it assists stakeholders in selecting the most appropriate clustering algorithms for PGP applications.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Open Access Journal of Power and Energy<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/oajpe.2025.3535709" target="_blank">https://dx.doi.org/10.1109/oajpe.2025.3535709</a></p>…"

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

"…The learning environment is based on a nonlinear double-track vehicle model, incorporating tire-road interactions. …"

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

"…It investigates the gain in training time and the performance in terms of accuracy when clustering-based deep learning modeling is employed for STLF. A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …"

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices حسب Neder Karmous (19743430)

"…We employed an ML method based on Random Forest (RF), Logistic Regression (LR), k-Nearest Neighbors (kNN), and Naive Bayes (NB) with a One-versus-Rest (OvR) strategy and then compared our work to other related works. …"

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…"

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model حسب Ramesh Sundar (19326046)

"…<p>This work aims to provide an effective hybrid beam forming method with Dual-Deep-Network to overcome overhead for mm-wave massive MIMO systems. …"

A Simulated Annealing Algorithm For Fuzzy Unit Commitment Problem حسب Mantawy, A. H.

"…This paper presents a new algorithm based on integrating simulated annealing and fuzzy logic methods to solve the unit commitment problem. …"
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A simulated annealing algorithm for fuzzy unit commitment problem حسب Mantawy, A.H.

"…This paper presents a new algorithm based on integrating simulated annealing and fuzzy logic methods to solve the unit commitment problem. …"
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Economic load dispatch using memetic sine cosine algorithm حسب Abu Zitar, Raed

"…SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. …"
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A Survey of cuckoo search algorithm: optimizer and new applications حسب Abualigah, Laith

"…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …"
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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms حسب Emara-Shabaik, Husam

"…Numerical simulations are presented to illustrate the effectiveness of the proposed algorithm based on different input signals, and different noise-to-signal ratios of the output. …"
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An efficient method for the open-shop scheduling problem using simulated annealing حسب Harmanani, Haidar M.

"…The method is based on a simulated annealing algorithm that efficiently explores the solution space. …"
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Animal migration optimization algorithm: novel optimizer, analysis, and applications حسب Abualigah, Laith

"…A new heuristic optimization algorithm was proposed in 2013 called the animal migration optimization (AMO) algorithm. …"
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Using genetic algorithms to optimize software quality estimation models حسب Azar, Danielle

"…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …"
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A new minimum curvator multi-step method for unconstrained optimization حسب Obeid, Samir

"…Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …"
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An incremental approach for test scheduling and synthesis using genetic algorithms حسب Harmanani, H.

"…The method is based on a genetic algorithm that efficiently explores the testable design space. …"
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms حسب Harmanani, H. M.

"…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …"
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