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Publikācija: ANGIE: Adaptive Network for Granular Information and Evidence Processing

Publication Type Full-text conference paper published in other conference proceedings
Funding for basic activity Unknown
Defending: ,
Publication language English (en)
Title in original language ANGIE: Adaptive Network for Granular Information and Evidence Processing
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Aleksandrs Vališevskis
Arkādijs Borisovs
Keywords adaptive network, information granularity, fuzzy evidences, decision support systems, sensitivity analysis.
Abstract In this paper the possibility of using adaptive networks in fuzzy-evidence-based decision support systems is considered. The architecture and learning algorithm underlying ANGIE (adaptive network for granular information processing) is presented. The proposed learning procedure helps in solving a task that can be related to sensitivity analysis in decision aid models. The proposed adaptive network can be used as a decision support system or as a tool for determining the significance and contribution of fuzzy features to the reaching of the desired value of the fuzzy criterion.
Hyperlink: http://alephfiles.rtu.lv/TUA01/000022343_e.pdf 
Reference Vališevskis, A., Borisovs, A. ANGIE: Adaptive Network for Granular Information and Evidence Processing. In: Proceedings of the 5th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS-2002), Italy, Milan, 17-18 September, 2002. Kaufering: b-Quadrat Verlag, 2002, pp.166-173.
ID 11127