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| 데مبر스터-셰퍼 증거 이론× | 퍼지 인지 지도 (Fuzzy Cognitive Maps, FCM)× | |
|---|---|---|
| 분야 | 소프트 컴퓨팅 | 소프트 컴퓨팅 |
| 계열≠ | Machine learning | Process / pipeline |
| 기원 연도≠ | 1976 | 1986 |
| 창시자≠ | Arthur P. Dempster & Glenn Shafer | Bart Kosko |
| 유형≠ | Uncertainty calculus for combining evidence | Fuzzy causal/feedback network for scenario analysis |
| 원전≠ | Dempster, A. P. (1967). Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38(2), 325–339. DOI ↗ | Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75. DOI ↗ |
| 별칭 | evidence theory, belief functions, evidential reasoning, Dempster-Shafer kanıt teorisi | FCM, Kosko cognitive map, causal cognitive map, bulanık bilişsel haritalar |
| 관련 | 4 | 4 |
| 요약≠ | Dempster-Shafer theory is a mathematical framework for reasoning under uncertainty that generalizes Bayesian probability by representing ignorance explicitly. Instead of forcing a single probability on each hypothesis, it assigns belief mass to sets of hypotheses and derives a belief-plausibility interval, and it provides Dempster's rule for fusing evidence from multiple independent sources. Developed from Arthur Dempster's 1967 work and Glenn Shafer's 1976 monograph, it underpins evidential reasoning and sensor/decision fusion. | A fuzzy cognitive map, introduced by Bart Kosko in 1986, represents a system as a network of concepts connected by signed, weighted causal links, and simulates how the concepts influence one another over time. By combining the intuitive structure of a cognitive map with fuzzy weights and iterative activation, FCMs let experts encode causal knowledge and then run what-if scenarios — making them popular for policy analysis, strategic decision-making, and modelling complex socio-technical systems. |
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