Machine learning for alloys
Alloy modelling has a history of machine-learning-like approaches, preceding the tide of
data-science-inspired work. The dawn of computational databases has made the integration …
data-science-inspired work. The dawn of computational databases has made the integration …
Machine learning in additive manufacturing: State-of-the-art and perspectives
Additive manufacturing (AM) has emerged as a disruptive digital manufacturing technology.
However, its broad adoption in industry is still hindered by high entry barriers of design for …
However, its broad adoption in industry is still hindered by high entry barriers of design for …
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
The spread of Covid-19 has resulted in worldwide health concerns. Social media is
increasingly used to share news and opinions about it. A realistic assessment of the …
increasingly used to share news and opinions about it. A realistic assessment of the …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Deep learning in chemistry
Machine learning enables computers to address problems by learning from data. Deep
learning is a type of machine learning that uses a hierarchical recombination of features to …
learning is a type of machine learning that uses a hierarchical recombination of features to …
[HTML][HTML] Deep learning for topology optimization of 2D metamaterials
Data-driven models are rising as an auspicious method for the geometrical design of
materials and structural systems. Nevertheless, existing data-driven models customarily …
materials and structural systems. Nevertheless, existing data-driven models customarily …
CatBoost model and artificial intelligence techniques for corporate failure prediction
Financial distress prediction provides an effective warning system for banks and investors to
correctly guide decisions on granting credit. Ensemble methods have demonstrated their …
correctly guide decisions on granting credit. Ensemble methods have demonstrated their …
On the class overlap problem in imbalanced data classification
Class imbalance is an active research area in the machine learning community. However,
existing and recent literature showed that class overlap had a higher negative impact on the …
existing and recent literature showed that class overlap had a higher negative impact on the …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Machine learning meets with metal organic frameworks for gas storage and separation
The acceleration in design of new metal organic frameworks (MOFs) has led scientists to
focus on high-throughput computational screening (HTCS) methods to quickly assess the …
focus on high-throughput computational screening (HTCS) methods to quickly assess the …