一种新的自适应多尺度波段加勒金方法,用于解决模糊混合微分方程
V Murugesh1, M Priyadharshini2, Yogesh Kumar Sharma1
1Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, AP, India.
一种新的数值方法,即自适应式多层盖勒金 (AMWG) 方法,准确地解决了复杂的模糊混合微分方程. 它有效地处理不确定性和急剧过渡,在准确性和速度方面超过传统技术.
科学领域:
- 数字分析 数字分析
- 应用数学 应用数学 应用数学
- 计算科学是一种计算科学.
背景情况:
- 模糊混合微分方程 (FHDEs) 模型具有不确定性和混合行为的复杂系统.
- 传统的数值方法由于非线性,不连续性和模糊参数而与FHDEs作斗争.
- 准确和高效的FHDE解决方案在控制工程,生物学和经济学中至关重要.
研究的目的:
- 引入一种新的数值方案,即适应式多层盖勒金 (AMWG) 方法,用于解决FHDEs.
- 解决FHDEs中处理不确定性和急剧过渡的现有方法的局限性.
- 在复杂的动态系统中展示AMWG方法的准确性,效率和可扩展性.
主要方法:
- 结合基于波纹的多分辨率分析与加勒金投影技术.
- 采用本地错误估计,用于解决方案域的自适应性改进.
- 应用选择性精炼:在的坡度/不连续性方面很好,其他地方粗.
主要成果:
- 在AMWG方法显著降低计算成本,而不会牺牲准确性.
- 与传统方法相比,实现更高的准确性,更低的内存要求和更快的计算速度.
- 在基准FHDEs中有效处理模糊的不确定性和急剧的过渡.
结论:
- AMWG方法是FHDEs的强大,灵活和可扩展的数值工具.
- 为具有非线性和离散切换的复杂动态系统提供卓越的性能.
- 具有大规模科学和工程应用的巨大潜力.
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