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

“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

“…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

“…Second, the standard convolutional operations are replaced with Deformable Convolutional Networksv2 (DCNv2) in the neck section to improve robustness in identifying multi-scale defects. …”

Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”

Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach by S. Punitha (17945654)

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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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NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES by Al-Garni, Ahmed Z.

“…., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. Second, weight compression is applied to streamline the deep neural network (DNN) parameters, boosting the storage efficiency and accelerating inference. …”

Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting by AlSayegh, Hadeel Yacoub

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

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…It is worth noting that the injection moulding process does not incorporate a type-2 fuzzy neural network (T2FNN). However, in this particular investigation, T2FNN was employed to replicate the mechanical stress model associated with dashboard injection moulding. …”

A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

“…Although, there are dedicated audio processing DNNs, yet, many recent models of AE have utilized U-Net: a DNN based on Convolutional Neural Network (CNN), fundamentally developed for image segmentation. …”