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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

Выпуски:
Том 52, 2020 Том 51, 2019 Том 50, 2018 Том 49, 2017 Том 48, 2016 Том 47, 2015 Том 46, 2014 Том 45, 2013 Том 44, 2012 Том 43, 2011 Том 42, 2010 Том 41, 2009 Том 40, 2008 Том 39, 2007 Том 38, 2006 Том 37, 2005 Том 36, 2004 Том 35, 2003 Том 34, 2002 Том 33, 2001 Том 32, 2000 Том 31, 1999 Том 30, 1998 Том 29, 1997 Том 28, 1996

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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