基于局部广义闭集的冠状病毒决策

IF 2 4区 计算机科学 Q2 Computer Science
M. A. El Safty, S. A. Alblowi, Y. Almalki, M. E. El Sayed
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引用次数: 0

摘要

现实世界的应用程序现在处理大量的数据,而关于世界的信息是不准确的、不完整的或不确定的。因此,我们在本文中提出了一个解决问题的建议模型。该模型基于一类局部广义闭集,即局部简单* α广义闭*集和局部简单* α广义闭**集(简称L S-M* α GC*-集和L S-M* α GC**-集),基于简单* α开集。我们还介绍了它们性质的各种概念以及它们与其他类型的关系,我们正在研究它们的一些性质。最后,我们应用简单* alpha开放集的概念来说明我们的方法在关于人类冠状病毒感染的信息系统决策中的重要性。事实上,我们能够确定冠状病毒感染的影响因素。并利用MATLAB程序对实验结果进行了编程。因此,建议在未来的决策中使用我们提出的概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coronavirus Decision-Making Based on a Locally -Generalized Closed Set
Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, L S-M*alpha GC*-sets and L S-M*alpha GC**-sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open set to illustrate the importance of our method in decision-making for information systems about the infections of Coronavirus in humans. In fact, we were able to decide the impact factors of Coronavirus infection. The results were also programmed using the MATLAB program. Therefore, it is recommended that our proposed concept be used in future decision-making.
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来源期刊
Intelligent Automation and Soft Computing
Intelligent Automation and Soft Computing 工程技术-计算机:人工智能
CiteScore
3.50
自引率
10.00%
发文量
429
审稿时长
10.8 months
期刊介绍: An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.
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