… machine learning algorithms for prediction of maximum event water fractions at the event
scale… two widely used machine learning algorithms, namely ANN and SVM, to predict maximum …

… where self-healing using machine learning can be applied to … to communities and preserve
critical services after power outages or … that use machine learning for cyber–physical systems. …

… tools to identify the timing and locations of events in disasters is critical. Over the past …
presents a hybrid machine learning pipeline that enables mapping events across various locations …

… PTW using three steps namely, critical event detection system, accident detection system,
and severity assessment system. The critical event detection system reads the accelerometer …

… injury are the foundation of neurocritical care management in severe traumatic … events and
36 (IQR 13.5–45.75) normal events identified per patient. The random forest machine learning …

… Risk assessment has a primary role in safety-critical industries. However, it faces a series of
… of machine learning on Known/Unknown events (Fig. 12). While machine learning may be …

… analyzed and in case of an identified critical trend or event, adequate action, such as an …
combination of Cluster Analysis and Supervised Machine Learning on product state data along …

… the complex interactions that lead to a critical event. As artificial intelligence and machine-learning
models offer improved ability to predict these events, they offer the potential to elevate …

… critical events. The intrinsic energy contribution measured using the GPR model is the most
numerically stable, whereas the SVR model gives the largest deviation among the testing …