Machine learning-based accuracy and reliability prediction for significant wave heights in the North Pacific Ocean: a hybrid deep learning framework

Well-Posedness and Long-Time Dynamics of a Manifold-Constrained Modified Swift–Hohenberg Equation

High-spatial resolution analyses of compressible turbulent boundary layers at Ma =\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin

Forecasting the Term Structure of Crude Oil Futures Prices Under Mean-Reverting Dynamics and Deep Learning Models

The research indicates that combining mean-reversion theory with scientific machine learning (SciML) yields a robust, theoretically sound methodology for forecasting commodity prices.

Deep Learning-Informed Symbolic Regression for Solution Gas–Oil Ratio Estimation

Exact Order of Multiplicative Approximation in Beta Dynamical Systems

Measurement-Driven Low-Label Adaptation for Signal-Based Areal Surface Roughness Prediction After Tool Replacement in Ti–6Al–4V Milling

In precision milling, areal surface roughness (Sa\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_{\textrm{a}}$$\end{document}) is common...