Time series clustering based on complex network with synchronous matching states
H Li, Z Liu, X Wan - Expert Systems with Applications, 2023 - Elsevier
Due to the extensive existence of time series in various fields, more and more research on
time series data mining, especially time series clustering, has been done in recent years …
time series data mining, especially time series clustering, has been done in recent years …
No two users are alike: Generating audiences with neural clustering for temporal point processes
V Zhuzhel, V Grabar, N Kaploukhaya… - Doklady …, 2023 - Springer
Identifying the right user to target is a common problem for different Internet platforms.
Although numerous systems address this task, they are heavily tailored for specific …
Although numerous systems address this task, they are heavily tailored for specific …
Anomaly Detection in the Automotive Stamping Process: An Unsupervised Machine Learning Approach
In metal forming, such as stamping of automotive parts, unsupervised machine learning
models offer a transformative approach to real-time quality control, especially when labelled …
models offer a transformative approach to real-time quality control, especially when labelled …
Supervised Machine Learning for Input Modelling of an Agent-Based Simulation Model for Autonomous On-Demand Shuttle Services
M Wartenberg, MA der Landwehr, LHM Nguyen… - EUROSIM …, 2023 - Springer
The quality of simulation-based experimentation is directly related to the estimation of its key
input parameters. Yet, especially when it comes to innovative transportation concepts that …
input parameters. Yet, especially when it comes to innovative transportation concepts that …
Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation …
Deep learning has changed the approach of urban environmental risk assessment and
management. These methods enable solid models for large data sets, enabling early …
management. These methods enable solid models for large data sets, enabling early …