标题： 基于熵的正则化方法对随机Shigesada-Kawasaki-Teramoto系统的涨落校正与整体解 显示英文标题

标题： Fluctuation Correction and Global Solutions for the Stochastic Shigesada-Kawasaki-Teramoto System via Entropy-Based Regularization

摘要： 我们引入一个噪声项以考虑基于n-物种Shigesada-Kawasaki-Teramoto (SKT) 系统粒子系统近似的涨落校正。对于由此产生的随机偏微分方程 (SPDE) 系统，我们建立了非负全局弱鞅解的存在性。我们的方法利用了基于系统熵结构的正则化技术。 显示英文摘要

摘要： We derive a noise term to account for fluctuation corrections based on the particle system approximation for the n-species Shigesada-Kawasaki-Teramoto (SKT) system. For the resulting system of stochastic partial differential equations (SPDEs), we establish the existence of nonnegative, global, weak martingale solutions. Our approach utilizes the regularization technique, which is grounded in the entropy structure of the system.