Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

“…<p>This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). …”

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks by Bekir Sait Ciftler (17541801)

“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”

Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Get full text

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

Subjects: “…Data clustering…”

Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”

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

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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

Subjects: “…orthogonal learning (OL)…”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…This article provides an in-depth survey of the strategies used to analyze sensor data and determine occupancy. The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…The framework is basically a merger of a deep learning (DL) agent deployed at the network edge with a quantum memory module (QMM). …”

Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

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Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

“…Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…However, they might not perform as expected, take much time in training, or not have enough input data to generalize well. To that end, deep transfer learning (DTL) and deep domain adaptation (DDA) have recently been proposed as promising solutions to alleviate these issues. …”