通过预测-校正方法在分数级水污染模型中对解决方案的稳定性和存在进行定性研究
Naveed Iqbal1, D K Archana2, Mohammad Nazrul Islam Khan3
1Department of Mathematics, College of Science, University of Ha'il, 2440, Ha'il, Saudi Arabia.
Scientific reports
|October 14, 2025
概括
分数顺序模型准确地模拟了水污染动态,包括记忆效应和异常扩散. 这项研究提出了一个新的计算框架来分析这些复杂的环境系统.
科学领域:
- 环境科学 环境科学
- 应用数学 应用数学 应用数学
- 水资源管理 水资源管理
背景情况:
- 水污染呈现复杂的动态,包括记忆效应和异常扩散,挑战传统的建模方法.
- 分数顺序模型为捕捉水生环境中的这些复杂行为提供了一个有希望的框架.
- 准确的计算分析对于了解污染物分散和微生物降解至关重要.
研究的目的:
- 引入一个分数顺序的水污染模型.
- 为分析模型提供一种高效的预测-校正数值方法.
- 调查模型的准确性,稳定性和适用于现实的环境场景.
主要方法:
- 为水污染开发一个分数次序微分方程模型.
- 预测-校正数值方法用于计算分析的应用.
- 稳定性分析以确定非对称行为和长期污染物分散.
- 固定点定理用于验证解决方案的存在和独特性.
主要成果:
- 预测-校正方法在模拟水污染动态方面表现出高准确性.
- 稳定性分析提供了对污染物的长期分散模式的见解.
- 数字模拟证实了在现实的环境条件下模型的可靠性.
- 验证解决方案的存在和独特性确保了数学严谨性.
结论:
- 分数顺序模型为研究复杂的水污染动态提供了强大的框架.
- 拟议的数值方法确保了准确和高效的计算分析.
- 这项研究为环境管理和可持续的水生生态系统健康提供了有价值的工具.
- 这项研究强调了先进的数学建模在应对环境挑战中的重要性.
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