“I was curious to establish a baseline for when LLMs are effectively able to solve open math problems compared to where they ...

Abstract: This article investigates a class of systems of nonlinear equations (SNEs). Three distributed neurodynamic models (DNMs), namely a two-layer model (DNM-I) and two single-layer models (DNM-II ...

Abstract: Analytically solving complex or large-scale differential equations is often difficult or even impossible, making numerical integration methods indispensable. However, as all numerical ...

1 Institute of Data Science and Engineering, Xuzhou University of Technology, Xuzhou, China 2 School of Mathematics and Statistics, Huaibei Normal University, Huaibei, China This study introduces a ...

Breakthroughs, discoveries, and DIY tips sent six days a week. Terms of Service and Privacy Policy. Most people’s experiences with polynomial equations don’t ...

A UNSW Sydney mathematician has discovered a new method to tackle algebra's oldest challenge—solving higher polynomial equations. Polynomials are equations involving a variable raised to powers, such ...

This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...

Neural networks have been widely used to solve partial differential equations (PDEs) in different fields, such as biology, physics, and materials science. Although current research focuses on PDEs ...