Abstract Time Series Classification (TSC) is an important and challenging problem in data
mining. With the increase of time series data availability, hundreds of TSC algorithms have …

Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

With the rapid increase of data availability, time series classification (TSC) has arisen in a
wide range of fields and drawn great attention of researchers. Recently, hundreds of TSC …

Classification of multivariate time series (MTS) has been tackled with a large variety of
methodologies and applied to a wide range of scenarios. Reservoir computing (RC) …

Uncovering flow dynamic behavior of different flow patterns is an important foundation of
multiphase flow research. But the traditional classifier is still adopted in the flow pattern …

Intra-driver and inter-driver heterogeneity has been confirmed to exist in human driving
behaviors by many studies. This research proposes a driver identification method by …

Reservoir computing is a machine learning method that is closely linked to dynamical
systems theory. This connection is highlighted in a brief introduction to the general concept …

Aeroengine, served by gas turbine, is a highly sophisticated system. It is a hard task to
analyze the location and cause of gas‐path faults by computational‐fluid‐dynamics software …

The information technology revolution, especially with the adoption of the Internet of Things,
longitudinal data in many domains become more available and accessible for secondary …

Objective. Understanding the cognitive load of drivers is crucial for road safety. Brain
sensing has the potential to provide an objective measure of driver cognitive load. We aim to …