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141
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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142
Using machine learning for disease detection. (c2013)
Published 2016“…Classification consists of predicting group membership for new data instances by learning from pre-classified data instances. …”
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masterThesis -
143
A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Optimization algorithms are one of the most popular methods for solving NP-hard problems. …”
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146
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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147
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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148
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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149
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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151
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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152
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
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doctoralThesis -
153
Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…This chapter offers the sea salmon-associated polyp (SALP) swarm algorithm (SSA) and multipurpose SSA (MSSA) as new optimization algorithms for solving optimization problems with single and multiple objectives. …”
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154
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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155
Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…<p>Data is present in abundance, but the problem of imbalanced dataset crops up time and again, vexing classifiers and reducing accuracy. …”
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