模糊广义线性方法
Fuzzy general linear methods
AI总结：
本文提出模糊广义线性方法（FGLM）以求解模糊微分方程，该方法在强 generalized 可微性下扩展了Adams方案，分析了稳定性、一致性和收敛性，并通过数值结果展示其效率和精度。
摘要：
本文致力于开发最一般的方案，即所谓的模糊广义线性方法（FGLM），用于求解模糊微分方程。广义线性方法（GLM）对于常微分方程是单步欧拉方法的两种极端扩展（线性多步法和龙格-库塔方法）之间的中间状态。在本文中，我们开发了用于在强 generalized 可微性下求解模糊微分方程的Adams方案的FGLM框架。将讨论稳定性、一致性和收敛性结果。数值结果和精度阶将被示出，以展示新方案的效率和精度。
英文摘要：
This paper concerns with the developing the most general schemes so-called Fuzzy General Linear Methods (FGLM) for solving fuzzy differential equations. The general linear methods (GLM) for ordinary differential equations are the middle state of two extreme extensions (linear multistep and Runge-Kutta methods) of the one step Euler method. In this paper we develop the FGLM framework of the Adams schemes for solving fuzzy differential equations under the strongly generalized differentiability. The stability, consistency and convergent results will be addressed. The numerical results and the order of accuracy is illustrated to show the efficiency and accuracy of the novel scheme.
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