Multivariate time series classification tasks play a crucial role in the field of data mining and find wide applications in areas such as audio, healthcare, and transportation. The core challenge in ...

To address the challenges of traditional marine meteorological prediction methods, which struggle to effectively capture intervariable correlations in multivariate time series data and suffer from ...

Given the limitations of the existing model, it is necessary to develop a new model that more comprehensively describes and predicts the viscoelastic mechanical parameters of the mixture. According to ...

The model calibration methodology described in the journal Landslides uses a probabilistic approach — Bayesian statistics — to maximize the information produced in site investigation data. This ...

The Monster Inside ChatGPT We discovered how easily a model’s safety training falls off, and below that mask is a lot of darkness.

This study introduces a Q-learning-based nonlinear model predictive control (QL-NMPC) framework for temperature control in batch reactors. A reinforcement learning agent is trained in simulation to ...