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Celal Cakiroglu
The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (...
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Sandi Baressi ?egota, Vedran Mrzljak, Nikola Andelic, Igor Poljak and Zlatan Car
Machine learning applications have demonstrated the potential to generate precise models in a wide variety of fields, including marine applications. Still, the main issue with ML-based methods is the need for large amounts of data, which may be impractic...
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Amirata Ghorbani, Dina Berenbaum, Maor Ivgi, Yuval Dafna and James Y. Zou
Interpretability is becoming an active research topic as machine learning (ML) models are more widely used to make critical decisions. Tabular data are one of the most commonly used modes of data in diverse applications such as healthcare and finance. Mu...
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Ana Me?trovic, Milan Petrovic and Slobodan Beliga
Retweet prediction is an important task in the context of various problems, such as information spreading analysis, automatic fake news detection, social media monitoring, etc. In this study, we explore retweet prediction based on heterogeneous data sour...
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Akram Mustafa and Mostafa Rahimi Azghadi
Machine learning (ML) has been slowly entering every aspect of our lives and its positive impact has been astonishing. To accelerate embedding ML in more applications and incorporating it in real-world scenarios, automated machine learning (AutoML) is em...
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