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Prioritization of hospital resilience indicators for disaster preparedness: a fuzzy Delphi-AHP approach in Iranian public hospitals. [PDF]
BMC Health Serv ResNakhaeipour M +4 more
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A neutrosophic explainable AI framework for modeling uncertainty in immersive stereotactic neurosurgical simulation. [PDF]
Front NeurolHechavarria-Hernandez JR.
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The extended TODIM method under q-rung orthopair fuzzy environment and its application to multi-path parallel transmission in mobile networks. [PDF]
Sci RepQiu S, Deng X, Jin Z, Chen Y.
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Fuzzy connectionist expert systems
Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 2002Hybrid architectures for intelligent systems is a new field of artificial intelligence research concerned with the development of the next generation of intelligent systems. Current research interests in this field focus on integrating the computational paradigm of expert systems with new emergent paradigms such as neural networks, fuzzy logic, and ...
R.J. Machado, A. Freitas da Rocha
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Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94, 2002
For developing fuzzy control systems and fuzzy expert systems, we have several shells. We describe two shells for expert systems, FPS (Fuzzy Production System) developed by the authors and FINEST (Fuzzy Inference Environment Software with Tuning) being developed in LIFE (Laboratory for International Fuzzy Engineering Research).
M. Umano, I. Hatono, H. Tamura
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For developing fuzzy control systems and fuzzy expert systems, we have several shells. We describe two shells for expert systems, FPS (Fuzzy Production System) developed by the authors and FINEST (Fuzzy Inference Environment Software with Tuning) being developed in LIFE (Laboratory for International Fuzzy Engineering Research).
M. Umano, I. Hatono, H. Tamura
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Fuzzy Sets and Systems, 1986
We describe a fuzzy rule based expert production system. The system accepts as input a fuzzy vector all of whose components are fuzzy sets, and produces as output a fuzzy set of conclusions. Non-fuzzy data are stored as fuzzy data with grade of membership one; internally, all data are considered fuzzy.
J.J. Buckley, W. Siler, Douglas Tucker
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We describe a fuzzy rule based expert production system. The system accepts as input a fuzzy vector all of whose components are fuzzy sets, and produces as output a fuzzy set of conclusions. Non-fuzzy data are stored as fuzzy data with grade of membership one; internally, all data are considered fuzzy.
J.J. Buckley, W. Siler, Douglas Tucker
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Fuzzy connectionist expert systems
International Joint Conference on Neural Networks, 1989Summary form only given, as follows. A fuzzy connectionist expert system with learning capabilities is described. The system uses a recruitment-of-cells learning algorithm for knowledge acquisition, and also allows the translation of rules into an equivalent connectionist network.
null Romaniuk, null Hall
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TrAC Trends in Analytical Chemistry, 1990
Abstract Application of the theory of fuzzy sets for building expert systems in analytical chemistry is explored. Fuzzy data, linguistic variables and quantifiers, approximate and default reasoning as well as fuzzy neural networks are considered. A reasoning scheme according to Yager [Artificial Intelligence, 31 (1987) 99] is used to demonstrate ...
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Abstract Application of the theory of fuzzy sets for building expert systems in analytical chemistry is explored. Fuzzy data, linguistic variables and quantifiers, approximate and default reasoning as well as fuzzy neural networks are considered. A reasoning scheme according to Yager [Artificial Intelligence, 31 (1987) 99] is used to demonstrate ...
openaire +1 more source