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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Печать: 1064-2315
ISSN Онлайн: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v31.i7-9.90
pages 51-58

Application of Self-Organizing Neural Networks with Active Neurons for Prediction of Bioactivity of Chemical Compounds by the Analogues Search Algorithm

Alexey G. Ivakhnenko
International Research and Training Center of Information Technlogies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kyiv
V. V. Kovalishyn
Igor V. Tetko
Institute of Physiology of Lausanne University, Switzerland
A. I. Luik
Grigoriy A. Ivakhnenko
"Information Recourses Inc." company, London, Great Britain
N. A. Ivakhnenko

Краткое описание

In the developed artificial neural network the analogues complexing algorithm is used as active neurons. Proposed procedure of structure self-organization and parameters choice is used for testing of two experimental subsamples of data. Two variants of sorting procedures of variables sets are considered. Analogues are found by distance calculation between the given output point and its closest neighbours. Received results show that self-organizing neural networks with active neurons, can be successfully applied in structure-activity relationship studies.

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