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The effects of data balancing approaches: A case study
Published 2023“…<p dir="ltr">Imbalanced datasets affect the performance of machine learning algorithms adversely. To cope with this problem, several resampling methods have been developed recently. …”
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Software defect prediction. (c2019)
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masterThesis -
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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…However, the integration of quantum computing and machine learning poses several challenges. One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”
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Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Published 2021“…Machine learning (ML) algorithms are thus providing the necessary tools to augment the capabilities of SHM systems and provide intelligent solutions for the challenges of the past. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”
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Single channel speech denoising by DDPG reinforcement learning agent
Published 2025“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”
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76
Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
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doctoralThesis -
77
KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”
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78
The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
doctoralThesis -
79
Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”