… prediction (machine learning algorithm) is a widely used data mining technique in many
areas of research and applications. Classification uses a supervised learning method where the …

… ), rule-based analysis (Lee et al., 2013) and hybrid methods (Lee et al., 2014). In response
to the limited availability of CFL learner data for machine learning and linguistic analysis, the …

… set used for super-resolution reconstruction technology, the performances of … method
and typical super-resolution reconstruction method based on deep learning are analyzed and …

… applications in decision-making and machine learning, then introduces basic operations
and … their typical applications in controls and machine learning. Finally, it points out several …

… More speculatively, use of the cyber range could itself generate more training data to feed
machine learning (ML) models and aid in their development.The progress and value of such …

… has proposed an “Artificial Intelligence 2.0 Plan,” which focused on big data, intelligent
sensing, cognitive computing, machine learning, and swarm intelligence.The Ministry of Science …

… In this research, we focus on the validity of artificial intelligence method … a machine learning
technology widely applied in multilayer feed forward network. Steepest error descent method …

… Methods This small-scale exploratory study adopted a mixed-methods approach, using
content and statistical analyses on the quantitative data in an inductive process (Patton 1990). …

… Our enemies are innovative and resourceful, and so are we. They never stop thinking about
… Our enemies are innovative and resourceful, and so are we. They never stop thinking about …