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dc.contributor.authorGolovko, Vladimir Adamovich
dc.contributor.authorSavitsky, Yuri Viktorovich
dc.contributor.authorGladyschuk, Vitaly B.
dc.coverage.spatialTimişoararu_RU
dc.date.accessioned2023-11-14T14:05:22Z
dc.date.available2023-11-14T14:05:22Z
dc.date.issued1996
dc.identifier.citationGolovko, V. A. A neural net for prediction prodlems / V. A. Golovko, J. V. Savitsky, V. B. Gladishchuk // Computer science and engineering : proceeding the international conference of technical informatics, Timişoara, November 14–16, 1996 / Politehnica university of Timişoara, Faculty of automation and computer science and engineering. – Timişoara, 1996. – P. 49–52. – Vol. 2. – Bibliogr.: p. 52 ( 3 titles).ru_RU
dc.identifier.urihttps://rep.bstu.by/handle/data/37083
dc.descriptionГоловко Владимир Адамович, Савицкий Юрий Викторович, Гладыщук Виталий Б. Нейронная сеть для решения задач прогнозированияru_RU
dc.description.abstractIn this paper are presents and investigates the various modifications of gradient descent method for Back-Propagation algorithm. Opportunity on reduction of neural network training time and increasing of training algorithm stability are considered The particular expressions for choosing of optimum steps of training neurons with sigmoid and linear functions of output activity are received. Results of experiments on predicting of various mathematical series and functions by using neural networks are presented The analysis of speed training neural network for offered training algorithm demonstrates its advantage before classical Back-Propagation algorithm.ru_RU
dc.language.isoenru_RU
dc.publisherPolitehnica university of Timişoararu_RU
dc.subjectneural netru_RU
dc.subjectback Propagationru_RU
dc.subjectобратное распространениеru_RU
dc.subjecttraining speedru_RU
dc.subjectскорость обученияru_RU
dc.subjectpredictionru_RU
dc.subjectпрогнозированиеru_RU
dc.titleA neural net for prediction prodlemsru_RU
dc.title.alternativeНейронная сеть для решения задач прогнозированияru_RU
dc.typeНаучный доклад (Working Paper)ru_RU


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