Email this article HIERARCHICAL MODEL OF DECISION-MAKING BASEDON FUZZY NEURALNETWORKS FOR INFORMATION PROCESSING
- Authors: Engel' E.A.1, Engel EA1
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- Issue: Vol 12, No 1 (2011)
- Pages: 83-86
- Section: Articles
- URL: https://journals.eco-vector.com/2712-8970/article/view/505729
- ID: 505729
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Abstract
Application of classical mathematical methods to solution of decision-making problems is difficult, intelligent systems
are more effective for this purpose, intelligent system is the synthesis of adaptive and conventional mathematical algorithms.
According to the vector approach, the problem of decision-making through the decomposition properties of alternatives
is a hierarchical system of criteria. Here there is a problem of inverse transition to assessment and comparison of
alternatives in general. This problem involves solution of problem composition of criteria for levels of hierarchy, which
is implemented by a neural network. The problem is solved by method of nested scalar convolutions. The developed
hierarchical fuzzy neural network is described.
are more effective for this purpose, intelligent system is the synthesis of adaptive and conventional mathematical algorithms.
According to the vector approach, the problem of decision-making through the decomposition properties of alternatives
is a hierarchical system of criteria. Here there is a problem of inverse transition to assessment and comparison of
alternatives in general. This problem involves solution of problem composition of criteria for levels of hierarchy, which
is implemented by a neural network. The problem is solved by method of nested scalar convolutions. The developed
hierarchical fuzzy neural network is described.
References
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- Энгель E. A.Модифицированная нейросеть для обработки информации с использованием селекции существенных связей : автореф. дис.канд. техн. наук. Красноярск, 2004.
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