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Application of optimal set partitioning theory to solving problems of artificial intelligence and pattern recognition

Application of optimal set partitioning theory to solving problems of artificial intelligence and pattern recognition

Abstract

The paper substantiates the possibility of applying the mathematical theory of continuous problems of optimal partitioning of sets of n-dimensional Euclidean space, which belong to the non-classical problems of infinite-dimensional mathematical programming, to the solution of problems of artificial intelligence and pattern recognition. The problems of pattern recognition both in conditions of certainty and in conditions of uncertainty are formulated. A particular attention is paid to the application of methods of the theory of optimal partitioning for the construction of fuzzy Voronoi diagrams. Examples of constructing fuzzy Voronoi diagrams with the optimal placement of generating points are given.

Обґрунтовано можливість застосування математичної теорії неперервних задач оптимального розбиття множин n-вимірного евклідового простору, які належать до некласичних задач нескінченновимірного математичного програмування, до розв’язання задач штучного інтелекту та розпізнавання образів. Наведено постановки задач розпізнавання образів як в умовах визначеності, так і в умовах невизначеності, підходи до їх розв’язання із застосуванням теорії оптимального розбиття множин. Особливу увагу приділено застосуванню методів теорії оптимального розбиття для побудови нечітких діаграм Вороного. Наведено приклади побудови нечітких діаграм Вороного з оптимальним розміщенням точок-генераторів.

Обоснована возможность применения математической теории непрерывных задач оптимального разбиения множеств n-мерного эвклидова пространства, которые относятся к неклассическим задачам бесконечномерного математического программирования, к решению задач искусственного интеллекта и распознавания образов. Приведены постановки задач распознавания образов как в условия определенности, так и в условиях неопределенности. Особое внимание уделено применению методов теории оптимального разбиения для построения нечетких диаграмм Вороного. Приведены примеры построения нечетких диаграмм Вороного с оптимальным размещением точек-генераторов.

Keywords

искусственный интеллект, оптимальне розбиття множин, точки-генератори, нескінченновимірне математичне програмування, fuzzy Voronoi diagram, point generators, оптимальное разбиение множеств, штучний інтелект, pattern recognition, распознавание образов, нечеткая диаграмма Вороного, artificial intelligence, optimal set partitioning, бесконечномерное математическое программирование, infinite-dimensional mathematical programming, розпізнавання образів, точки-генераторы, нечітка діаграма Вороного

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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