Deterioration is the significant degradation of the physical state prior to death. Detecting the
deterioration of patients could provide an early warning to their families in instances of …

Directly mining high-dimensional time series presents several challenges, such as time and
space costs. This study proposes a new approach for representing time series data and …

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing
downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large …

Efficient anomaly detection is at the forefront of ensuring optimized operations and system
safety, especially in the field of engineering. It is deemed indispensable for the …

Approximate dynamic programming (ADP) is the standard tool for the solution of multistage
dynamic optimization problems under general conditions, such as nonlinear state equation …

Time series anomaly detection aims to find specific patterns in time series that do not
conform to general rules, which is one of the important research directions in machine …

With the widespread adoption of drones in daily life, next-generation smart cities need to
establish highways, ie, trajectories where drones can fly and operate safely. However, due …

In addressing the complexities of time series analysis, two primary challenges emerge: high
dimensionality and inherent non-linearity, which often obstruct effective data processing and …

Under space-based observation conditions, targets are subject to a large number of stars,
clutter, false alarms, and other interferences, which can significantly impact the traditional …

Variable-length anomalous subsequence detection in time series has many important
applications in the real world, yet the methods presented in existing studies are …