Machine learning methods for large deviations by Cloete, Daniël Willem Hendrik

Subjects: “…Stochastic processes -- Mathematical models…”
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Prediction of Distresses in Pavement Networks: A Machine Learning Approach by Kotb, Mahmoud

Subjects: “…pavement management prediction modeling machine learning…”
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Factors to consider in the transition from a teacher-centred model to a learner-centred model in a computer-rich learning environment

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Wildfire path spread prediction system using machine learning: use of ANN, convolutional autoencoder, and ConvLSTM ML model by Makhaba, Limpho Mapulane

“…This research performs a comprehensive investigation into the use of supervised classification Machine Learning(ML) models, specifically, Artificial Neural Networks(ANN), Convolutional Autoencoder, and Convolution Long Short-Term Memory(convLSTM), in predicting wildfire spread. …”
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Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data

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Cluster graph representations of low-density parity-check codes including non-stationary channel noise estimation by Du Toit, Jaco

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Seismic resistance of unreinforced load-bearing masonry buildings, retrofitted with a strain-hardening cement-based composite by Kotze, Mariska

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The implications of Ned Herrmann’s whole-brain model for violin teaching : a case study by Campbell, Velma-Jean

Subjects: “…Learning style models…”
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Optimizing Load Balancing in Cloud-Based Healthcare Systems: Leveraging Linear Programming, Metaheuristics, and Queuing Models to Minimize Latency and Maximize Throughput

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Optimizing Load Balancing in Cloud-Based Healthcare Systems: Leveraging Linear Programming, Metaheuristics, and Queuing Models to Minimize Latency and Maximize Throughput

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Building a Model for stock exchange growth in Africa: Learnings from the BRICS exchanges

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Modelling highly imbalanced credit card fraud detection data using statistical learning by Moodley, Revesa

“…The best supervised learning models are RF and XGBoost. The tree models were generally well suited to the imbalanced dataset, whilst LR performed the worst, even when applying regularisation. …”
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Enhancement of digital elevation models using tree-based ensemble machine learning algorithms by Okolie, Chukwuma

“…Thus, global digital elevation models (DEMs) have gained worldwide prominence due to their free availability; a prime advantage when compared to prohibitively expensive airborne topographic surveys. …”
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Towards an interactive mobile lecturing model a higher-level engagement for enhancing learning by Boyinbode, Olutayo Kehinde

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An interactive R shiny application for learning multivariate data analysis and time series modelling

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A machine learning-remote sensing framework for modelling water stress in Shiraz vineyards by Loggenberg, Kyle Devronne

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