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Applied Mathematics and Machine Learning
Qun Li (editor) and Aihua Wood (editor)
2024
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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; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications. We publish papers from all areas of mathematics and engineering, and especially those that showcase novel machine learning techniques that leverage subject matter expertise. We aim to foster the communication of the latest research results in the areas of applied and computational mathematics.
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Keywords
- anomaly detection
- autoencoders
- bibliometric analysis
- Casetti’s model
- Cauchy matrix
- climate variables
- coarse grid
- compressive strength
- convolutional neural networks (CNNs)
- Data envelopment analysis
- Dbar-dressing method
- deep learning
- deep neural network
- Digital twin
- dynamical systems
- Efficiency
- electron microscope
- Entropy
- false information detection
- financial ratio
- fuzzy
- Gallium Arsenide (GaAs)
- gradient boosting machine
- graph neural network
- Industry 4.0
- Korteweg–de Vries equation
- latent representation
- Lax pair
- Machine learning
- manifold learning
- multi-criteria decision making
- neural networks
- operational risk
- potential improvement
- prediction
- principal component analysis (PCA)
- Ranking
- residual structure
- RShiny
- SAR-X
- self-compacting concrete
- soliton solutions
- subject area
- supply chain
- 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
- TOPSIS
Links
DOI: 10.3390/books978-3-7258-1282-0Editions