Application of neural fuzzy classification in decision support systems

\nThe 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.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-11-28
DOI
https://doi.org/10.1051/bioconf/202414504017/pdf
Primary Topic
Mathematical Control Systems and Analysis
Type
article
Field-Weighted Citation Impact
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article

Application of neural fuzzy classification in decision support systems

Springer Link (Chiba Institute of Technology)
Mathematical Control Systems and Analysis
article

Application of neural fuzzy classification in decision support systems

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Abstract

\nThe 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.\n

Springer Link (Chiba Institute of Technology)
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Mathematical Control Systems and Analysis
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Application of neural fuzzy classification in decision support systems · Springer Link (Chiba Institute of Technology) (2024) | TGRS Research Map | TGRS