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Self-organizing construction of hierarchical structure of multi-layer perceptronsстатья
Информация о цитировании статьи получена из
Web of Science
Дата последнего поиска статьи во внешних источниках: 29 мая 2015 г.
- Авторы: Dolenko S.A., Eremin E.K., Orlov Yu V., Persiantsev I.G., Shugai Ju S.
- Сборник: Proceedings of the 5th International Conference on Artificial Neural Networks
- Серия: IEE Conference Publication
- Том: 440
- Год издания: 1997
- Место издания: University of Cambridge Institute of Electrical and Electronics Engineers Cambridge, UK
- Первая страница: 285
- Последняя страница: 290
- Аннотация: A novel algorithm for creation of a hierarchical structure of neural network classifiers for classification of large databases is suggested. Each node of the hierarchical tree is a multilayer perceptron trained by the algorithm combining self-organization with supervised learning. Thus, the problems of clustering and classification for a given node are solved in concord. Also, it allows the a priori information on similarity of grouped patterns to be naturally taken into account. The algorithm performance has been tested on model data and on real-world problems.
- Добавил в систему: Шугай Юлия Сергеевна