Clarkson University researchers have developed an artificial intelligence tool that can uncover the mathematical equations ...

Abstract: Physics-informed neural networks (PINNs) are not dependent on data-driven methods but are solely constrained by physical laws. This makes them more aligned with the ideal inverse design ...

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...

Index laws and the laws of logarithms are essential tools for simplifying and manipulating exponential and logarithmic functions. There is an inverse relationship between exponential and logarithmic ...

Differential equations often give rise to rank-structured matrices characterized by low-rank off-diagonal blocks. These matrices can be conveniently represented in a hierarchical format, enabling ...

The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the ...

This paper presents In-Context Operator Networks (ICON), a neural network approach that can learn new operators from prompted data during the inference stage without requiring any weight updates.

Abstract: Power systems consist of generators, transformers, loads, and distributed power sources interconnected through lines. The reliable operation of the system requires that voltage and current ...

1 College of Mathematics and Statistics, Sichuan University of Science & Engineering, Zigong, China. 2 Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering ...

This research work investigates the use of Artificial Neural Network (ANN) based on models for solving first and second order linear constant coefficient ordinary differential equations with initial ...