Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks by S. N. V. Bramareswara Rao (21768302)

“…Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. …”

A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

Soft Sensor for NOx Emission using Dynamical Neural Network by Shakil, M.

“…Lag space for the model is found by using genetic algorithm to find the best time delayed model. Lag space obtained from the linear model is then used for constriction of the dynamical neural network. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm by Ahmed, Khidir Galal Eldin Khidir

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Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…When comparing the actual and anticipated ground loss, the SVR performed best (R² = 0.79–0.93) as compared to the other two algorithms i.e., LR (R² = 0.73 to 0.92), and RF (R² = 0.53 to 0.89) for the three fields. …”

Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem by Al-Mulhem, M.

“…This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). …”
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Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

Improved Jaya Synergistic Swarm Optimization Algorithm to Optimize Task Scheduling Problems in Cloud Computing by Abualigah, Laith

“…The Jaya algorithm's ability to exploit the current best solutions is complemented by the SSO's collaborative search strategy, resulting in a synergistic optimization framework. …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…Extracted vegetation indices were evaluated on three ML algorithms, namely, random forest (RF), k-nearest neighbour (K-NN), and k dimensional-tree (KD-Tree). …”

A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”