Manuscript Topics

The escalating complexity of real-world problems, as well as further breakthroughs in established computational theories, demand a spectrum of innovative approaches for numerical simulations and unveiling the underlying mathematical essence. This special issue aims to present recent developments at the intersection of classical numerical methods, scientific machine learning, and other numerical approaches. It serves as a platform for disseminating innovations in computational theories, numerical techniques, and applied studies that address problems in science and engineering through the lens of partial differential equations (PDEs) and data.

The main topics include, but are not limited to:
Numerical Methods for PDEs, ODEs and Integral Equations
Numerical Analysis
Scientific Machine Learning
Data-driven Approaches
Optimization and Control

Instructions for authors
https://www.aimspress.com/era/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/