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| Belief Rule Base (BRB)× | 퍼지 인지 지도 (Fuzzy Cognitive Maps, FCM)× | |
|---|---|---|
| 분야 | 소프트 컴퓨팅 | 소프트 컴퓨팅 |
| 계열≠ | Machine learning | Process / pipeline |
| 기원 연도≠ | 2006 | 1986 |
| 창시자≠ | Jian-Bo Yang et al. | Bart Kosko |
| 유형≠ | Expert-system inference with belief distributions | Fuzzy causal/feedback network for scenario analysis |
| 원전≠ | Yang, J.-B., Liu, J., Wang, J., Sii, H.-S., & Wang, H.-W. (2006). Belief rule-base inference methodology using the evidential reasoning approach—RIMER. IEEE Transactions on Systems, Man, and Cybernetics—Part A, 36(2), 266–285. DOI ↗ | Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75. DOI ↗ |
| 별칭 | RIMER, Belief Rule-Based System, BRB System, İnanç Kural Tabanlı Çıkarım | FCM, Kosko cognitive map, causal cognitive map, bulanık bilişsel haritalar |
| 관련≠ | 3 | 4 |
| 요약≠ | Belief Rule Base (BRB), introduced by Yang et al. in 2006 under the RIMER framework, is an expert-system inference methodology that extends classical if-then rules by attaching belief degree distributions to rule consequents. It combines rule-based reasoning with the Evidential Reasoning (ER) approach, enabling the representation and propagation of uncertainty, incompleteness, and vagueness in complex decision problems across engineering, risk assessment, and management domains. | 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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