편재관 김도영 강정화 박상철 2024-06 2508-4003 https://aurora.ajou.ac.kr/handle/2018.oak/37854 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART003085535 Modern battlefield environments are filled with complexity and uncertainty, necessitating accu- rate assessment of threats posed by targets, armaments, and protective assets. In these complex settings, objective threat assessment is crucial for strategic decision-making and efficient resource allocation. This study proposes a new methodology for threat assessment, integrating fuzzy logic with genetic algorithms. Utilizing real-world data on weaponry and equipment, this methodology derives optimal membership function values using genetic algorithms. These val- ues are then used to extract threat weights for each piece of equipment. Additionally, proximity calculations are employed to determine the final threat level. This approach offers a more objec- tive and precise evaluation compared to traditional methods, effectively reflecting the diverse characteristics of ground targets. Future research will focus on developing algorithms that con- sider a broader range of battlefield conditions and target characteristics, along with validating their applicability in real-world scenarios. Kor 한국CDE학회 퍼지 유전 알고리즘과 분석적 접근을 통한 대지 표적 위협도 평가 Threat Assessment of Ground Targets Through Fuzzy Genetic Algorithm and Analytical Approach Article 135 2 125 한국CDE학회 논문집 29 한국CDE학회 논문집, Vol.29 No.2, pp.125-135 10.7315/CDE.2024.125 Decision Making supporting Fuzzy expert system Genetic Algorithm Modeling and Simulation Optimization Risk Assessment Article