Applied Mathematics and Machine Learning

The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; o...

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Format:	Online
Idioma:	anglès
Publicat:	MDPI - Multidisciplinary Digital Publishing Institute 2024
Matèries:	self-compacting concrete compressive strength deep neural network gradient boosting machine machine learning Dbar-dressing method Cauchy matrix Lax pair soliton solutions entropy fuzzy TOPSIS multi-criteria decision making financial ratio ranking data envelopment analysis efficiency operational risk potential improvement Korteweg–de Vries equation coarse grid digital twin Industry 4.0 supply chain bibliometric analysis subject area false information detection residual structure graph neural network electron microscope convolutional neural networks (CNNs) anomaly detection principal component analysis (PCA) deep learning neural networks Gallium Arsenide (GaAs) SAR-X Casetti’s model climate variables prediction RShiny dynamical systems autoencoders latent representation manifold learning thema EDItEUR::P Mathematics and Science thema EDItEUR::P Mathematics and Science::PB Mathematics thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics
Accés en línia:	ONIX_20240704_9783725812813_123
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Applied Mathematics and Machine Learning

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