Manuscript Topics

The rapid growing demands of increasingly complex real-world challenges, coupled with advancements in computational power and techniques, drive the developments of novel approaches for numerical simulations and the exploration of the mathematical principles underlying these problems. This special issue highlights recent advancements at the intersection of classical numerical methods, scientific machine learning, and data science. It aims to disseminate developments in numerical and data-driven methodologies, as well as mathematical modeling, for addressing complex problems in science and engineering.

The main topics include, but are not limited to:  
1). Numerical Methods for Differential and Integral Equations  
2). Numerical Analysis  
3). Inverse Problem  
4). Statistical Modeling  
5). Scientific Machine Learning  
6). Data-driven Approaches  
7). Optimization and Control

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