Batool Bushra, Abosuliman Shougi Suliman, Abdullah Saleem, Ashraf Shahzaib
Department of Mathematics, University of Sargodha, Sargodha, Pakistan.
Department of Transportation and Port Management, Faculty of Maritime Studies, King Abdulaziz University, Jeddah, 21588 Saudi Arabia.
J Ambient Intell Humaniz Comput. 2022;13(12):5491-5504. doi: 10.1007/s12652-021-03181-1. Epub 2021 Apr 12.
The significance of emergency decision-making (EmDM) has been experienced recently due to the continuous occurrence of various emergency situations that have caused significant social and monetary misfortunes. EmDM assumes a manageable role when it is important to moderate property and live misfortunes and to reduce the negative effects on the social and natural turn of events. Genuine world EmDM issues are usually described as complex, time-consuming, lack of data, and the effect of mental practices that make it a challenging task for decision-makers. This article shows the need to manage the various types of vulnerabilities and to monitor practices to resolve these concerns. In clinical analysis, how to select an ideal drug from certain drugs with efficacy values for coronavirus disease has become a common problem these days. To address this issue, we are establishing a multi-attribute decision-making approach (MADMap) based on the EDAS method under Pythagorean probabilistic hesitant fuzzy information. In addition, an algorithm is developed to address the uncertainty in the selection of drugs in EmDM issues with regards to clinical analysis. The actual contextual analysis of the selection of the appropriate drug to treat coronavirus ailment is utilized to show the practicality of our proposed technique. Finally, with the help of a comparative analysis of the TOPSIS technique, we demonstrate the efficiency and applicability of the established methodology.
由于各种紧急情况不断发生，造成了重大的社会和经济损失，紧急决策（EmDM）的重要性最近得到了体现。当需要减轻财产和生命损失，并减少对社会和自然发展的负面影响时，紧急决策发挥着可控作用。现实世界中的紧急决策问题通常被描述为复杂、耗时、缺乏数据，以及心理因素的影响，这使得决策者面临一项具有挑战性的任务。本文表明有必要应对各种类型的不确定性，并监测相关做法以解决这些问题。在临床分析中，如何从某些对冠状病毒病具有疗效值的药物中选择理想药物，如今已成为一个常见问题。为解决这一问题，我们正在基于毕达哥拉斯概率犹豫模糊信息下的EDAS方法建立一种多属性决策方法（MADMap）。此外，还开发了一种算法来解决紧急决策问题中临床分析药物选择方面的不确定性。通过选择治疗冠状病毒病的合适药物的实际案例分析，来展示我们所提出技术的实用性。最后，借助与TOPSIS技术的对比分析，我们证明了所建立方法的有效性和适用性。
