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Wilson Tsakane Mongwe, Rendani Mbuvha and Tshilidzi Marwala
Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis?Hastings (MH) algorithm. The MH algorithm suffers fro...
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Sungkun Hwang, Recep M. Gorguluarslan, Hae-Jin Choi and Seung-Kyum Choi
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the nar...
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Eslam A. Hussein, Christopher Thron, Mehrdad Ghaziasgar, Antoine Bagula and Mattia Vaccari
Predicting groundwater availability is important to water sustainability and drought mitigation. Machine-learning tools have the potential to improve groundwater prediction, thus enabling resource planners to: (1) anticipate water quality in unsampled ar...
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Christina M. Botai, Joel O. Botai, Abiodun M. Adeola, Jaco P. de Wit, Katlego P. Ncongwane and Nosipho N. Zwane
This research study was carried out to investigate the characteristics of drought based on the joint distribution of two dependent variables, the duration and severity, in the Eastern Cape Province, South Africa. The drought variables were computed from ...
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Mohammad Wedyan, Alessandro Crippa and Adel Al-Jumaily
Deep neural networks are successful learning tools for building nonlinear models. However, a robust deep learning-based classification model needs a large dataset. Indeed, these models are often unstable when they use small datasets. To solve this issue,...
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