用于土木工程的人工智能工具的分类在复杂的模糊粗的弗兰克聚合运算符的概念下
Walid Emam1, Jabbar Ahmmad2,3, Tahir Mahmood4
1Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia.
Scientific reports
|May 24, 2024
概括
研究人员开发了一个复杂的模糊粗略集在笛卡尔形式来最大限度地减少数据损失,解决模糊和粗略集理论的局限性. 这种新的框架可以处理上/下近似和二维来改进信息处理.
科学领域:
- 信息理论是信息理论.
- 模糊的集合理论 模糊的集合理论
- 粗略的集合理论就是粗略的集合理论.
背景情况:
- 传统的模糊和粗略集在处理近似和多维数据方面存在局限性,导致潜在的信息丢失.
- 现有的复杂模糊集合无法充分处理上下近似,因此需要增强结构.
研究的目的:
- 介绍复杂模糊关系理论和复杂模糊粗略集在笛卡尔形式.
- 开发复杂模糊粗略数的基本定律,使用弗兰克的t-规范和t-规范.
- 为复杂的模糊粗略集定义新的聚合运算符.
主要方法:
- 发展复杂的模糊关系和复杂的模糊粗略集合理论在笛卡尔形式.
- 基于弗兰克t-规范和t-规范的复杂模糊粗数基本定律的初始化.
- 复杂的模糊粗略弗兰克平均和几何聚合运算符的定义.
主要成果:
- 建立了复杂模糊粗略集的理论,以笛卡尔形式,能够处理第二维和近似.
- 引入了新的聚合运算符 (弗兰克平均和几何运算符) 用于复杂的模糊粗略数字.
- 开发了一种算法,并证明了它在对土木工程人工智能工具的分类中的应用.
结论:
- 复杂的模糊粗略设置在笛卡儿形式有效地解决了以前理论的局限性,最大限度地减少数据损失.
- 开发的聚合运算符和算法为复杂的数据分析提供了强大的框架.
- 该方法显示了对现有概念的进步,通过在土木工程人工智能工具分类中的实际应用来验证.
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