Designing multimodal public transport networks using metaheuristics

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Machine learning in astronomy by Du Buisson, Lise

“…Using principal component analysis and linear discriminant analysis, we construct a grand total of 56 feature sets with which to train, optimise and test a Minimum Error Classifier (MEC), a naive Bayes classifier, a k-Nearest Neighbours (kNN) algorithm, a Support Vector Machine (SVM) and the SkyNet artificial neural network.…”
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Improving probabilistic record linkage with a single-layer neural network by Hamersma, Kris A.

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Autonomous racing on unseen tracks using reinforcement learning by Jefferies, Devin Wayne Patrick

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Using machine learning techniques in developing an autonomous network orchestration scheme in 5g networks by Mohamad, Anfar Mohamad Rimas

“…After that, application-based features were extracted by using heuristic logical filters to prepare a feature vector for the Machine Learning (ML) algorithm. A trained Multi-layer Perceptron (MLP) based Artificial Neural Network (ANN) was selected as the classifier after comparing results with Support Vector Machine (SVM), Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN). …”
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Predicting household poverty with machine learning methods: the case of Malawi by Chinyama, Francis

“…These supervised learning algorithms were trained using 10-fold cross-validation. …”
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Prospecting for enigmatic radio sources with autoencoders : a novel approach

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Predicting process performance in the manufacturing and agricultural sectors using machine learning techniques by Khoza, Sibusiso Comfort

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A novel framework for monitoring oil spill from moving vessels using synthetic aperture radar

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Markerless vision-based localisation for autonomous inspection drones. by Nel, Gert

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Human action recognition with 3D convolutional neural networks by Cronje, Frans

“…Three CNNs are built and trained to provide insight into design choices as well as allow the construction of an ensemble model. …”
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Analysis of a deep neural network for missing transverse momentum reconstruction in ATLAS by Leigh, Matthew

“…In this work, a deep neural network was trained using supervised learning to measure this imbalance. …”
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Investigating language preferences in improving multilingual Swahili information retrieval by Telemala, Joseph Philipo

“…We evaluated our proposed T-L-based algorithm using clickthrough logs from our prototype guided multilingual search engine. …”
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Determination of a robust metabolic barcoding model for chemotaxonomy in Aizoaceae species : expanding morphological and genetic understanding by Hilgart, Amelia

“…Once isolated, this subset of informative data was established as metabolic barcodes for the identification of the study species. A machine learning algorithm, Random Forest, was used to build a classification model based on the metabolic barcodes which was then trained on various trends from the factors monitored over the year. …”
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Exploring the application of Natural Language Processing to scientific medical cannabis publications by de Beer, James Charles

“…Analyzing the large quantities of available text data using natural language processing and machine learning algorithms could improve the speed and accuracy at which cannabis research is processed, as well as expose hitherto unknown connections between cannabis compounds and the treatment of healtth conditions. …”
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Rail surface anomaly detection : a deep learning . approach for computer vision

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AI/Machine learning approach to identifying potential statistical arbitrage opportunities with FX and Bitcoin Markets by Ntsaluba, Kuselo Ntsika

“…The forecasts made by the genetically trained ANN are compared to those made by a new variation of the simple moving average (MA) trading strategy, tailored to the methodology, as well as a random model. …”
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The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions by Olshewsky, Avron Bernard

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Towards high fidelity mapping of global inland water quality using earth observation data by Kravitz, Jeremy

“…Finally, the synthetic dataset was used to train and test four state-of-the-art machine learning architectures for multi-parameter retrieval and cross-sensor capability. …”
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Design and optimization of an embedded machine learning image processing system with a Linux SOC for large-scale livestock tallying by Le Roux, Morne

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