Numerical Methods of Synthesis of a Correct Algorithm for Solving Recognition Problems

We mainly study the voting model. The article considers recognition problems with disjoint classes. These problems are, in a particular case, a discrete analogue of the problem of finding optimal solutions. Not only the problems of synthesizing the best solutions, but also other important classes of applied problems are reduced to recognition problems. In real calculations, there is no need to remember all the parameters 𝑃𝑟 𝑣 · 𝜀𝑟 𝑣 that determine the proximity function for the recognizable object and the sets 𝐾𝑗 . It is enough to limit ourselves to only a small part. The values of the parameters 𝜀𝑖𝑘𝑃𝑖𝑘 in problems with disjoint classes are determined independently for each class.

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Publication Details

Journal
Advances in Artificial Intelligence and Machine Learning
Published
2025-01-01
DOI
https://doi.org/10.54364/aaiml.2025.51202
Citations
1
Primary Topic
Advanced Computational Techniques in Science and Engineering
Type
article
Field-Weighted Citation Impact
3.25
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article

Numerical Methods of Synthesis of a Correct Algorithm for Solving Recognition Problems

Nodirbek Urinov, Islambek Saymanov, Alimdzhan Babadzhanov, Akmal Varisov et al.
1 citations
Advances in Artificial Intelligence and Machine Learning
Advanced Computational Techniques in Science and Engineering
3.25
article

Numerical Methods of Synthesis of a Correct Algorithm for Solving Recognition Problems

Nodirbek Urinov, Islambek Saymanov, Alimdzhan Babadzhanov, Akmal Varisov, Anvarxon Madjidov
article en
1 citations

Abstract

We mainly study the voting model. The article considers recognition problems with disjoint classes. These problems are, in a particular case, a discrete analogue of the problem of finding optimal solutions. Not only the problems of synthesizing the best solutions, but also other important classes of applied problems are reduced to recognition problems. In real calculations, there is no need to remember all the parameters 𝑃𝑟 𝑣 · 𝜀𝑟 𝑣 that determine the proximity function for the recognizable object and the sets 𝐾𝑗 . It is enough to limit ourselves to only a small part. The values of the parameters 𝜀𝑖𝑘𝑃𝑖𝑘 in problems with disjoint classes are determined independently for each class.

Advances in Artificial Intelligence and Machine LearningVol. 05(01)
Openalex Percentile: Top 10%
Advanced Computational Techniques in Science and Engineering
3.25
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