APPLICATION OF NEURAL FUZZY CLASSIFICATION IN DECISION SUPPORT SYSTEMS
Section: SECTION 2. DESIGN AUTOMATION SYSTEMS
Authors:
1.
Tambov State Technical University
Russian Federation
Russian Federation
Type:
Сonference article
Published:
14.04.2025
Subject area:
004.8
Language:
Russian
Keywords:
dynamics, fuzzy logic, neuro-fuzzy networks, classification
Abstract (English):
The article proposes a classification of fuzzy information about the terrain for solving problems in the fields of agriculture and forestry. This classification allows for a more accurate description and understanding of the characteristics of fuzzy information, which can be useful for decision-making under uncertainty. Special attention is given to the area of forest fire modeling using geographic information systems. A hybrid fuzzy network is proposed for classifying the parameters of the fire source and the environment to select the optimal analytical model.
The article proposes a classification of fuzzy information about the terrain for solving problems in the fields of agriculture and forestry. This classification allows for a more accurate description and understanding of the characteristics of fuzzy information, which can be useful for decision-making under uncertainty. Special attention is given to the area of forest fire modeling using geographic information systems. A hybrid fuzzy network is proposed for classifying the parameters of the fire source and the environment to select the optimal analytical model.
Keywords:
dynamics, fuzzy logic, neuro-fuzzy networks, classification
dynamics, fuzzy logic, neuro-fuzzy networks, classification
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