Fuzzy Model of Defence of the Defensive Line by a Group of Dynamic Objects

Bayramov, Azad Agalar; Pashayev, Adalat; Sabziev, Elkhan

doi:10.1007/978-3-031-20153-0_30

Cited by 1 publication

(1 citation statement)

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“…The integration of fuzzy logic into decision-making models has emerged as a significant advancement in addressing complexity and uncertainty in various domains (Pamučar et al, 2012;Božanić et al, 2021;Narang et al, 2023;Sahoo & Goswami, 2023;Naseem et al, 2023;Tripathy, 2023), including security and defense (Bayramov et al, 2023;Güneri & Deveci, 2023;Kamalov et al, 2023). Fuzzy logic, a computational approach that accounts for vagueness and imprecision, has found application in diverse fields due to its ability to handle uncertain and incomplete information (Đuričić, 2023;Tešić et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Ranking challenges, risks and threats using Fuzzy Inference System

Božanić,

Tešić,

Puška

et al. 2023

Decis. Mak. Appl. Manag. Eng.

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This paper presents a Fuzzy Inference System (FIS) designed to comprehensively assess challenges, risks, and threats. In the realm of security and defense, defining these elements is inherently uncertain and complex. The paper addresses this challenge by integrating fuzzy logic into the model. As a pivotal instrument for decision-making, the model not only facilitates the precise identification of challenges, risks, and threats but also provides vital support for the strategic and doctrinal document development process. The methodology proves instrumental in reconciling divergent perspectives, aligning theoretical intricacies with practical applications. By effectively capturing the nuanced interplay between variables, the model offers a dynamic framework that enhances the accuracy and efficiency of security-related decision-making.

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