Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights von Emelyanov, A V, Nikiruy, K E, Serenko, A V, Sitnikov, A V, Presnyakov, M Yu, Rybka, R B, Sboev, A G, Rylkov, V V, Kashkarov, P K, Kovalchuk, M V, Demin, V A

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Neural network data driven model of the process of analyzing control commands for a mobile robot in natural russian language von Sboev, A. G., Rybka, R. B., Davydov, Y.A., Moloshnikov, I. A.

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Baseline accuracy of forecasting COVID-19 cases in Moscow region on a year in retrospect using basic statistical and machine learning methods von Sboev, A G, Kudryshov, N A, Moloshnikov, I A, Serenko, A V, Naumov, A V, Rybka, R B

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A neural network algorithm for extracting pharmacological information from russian-language internet reviews on drugs von Sboev, A G, Sboeva, S G, Gryaznov, A V, Evteeva, A V, Rybka, R B, Silin, M S

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Baseline Accuracies of Forecasting COVID-19 Cases in Russian Regions on a Year in Retrospect Using Basic Statistical and Machine Learning Methods von Naumov, A.V., Moloshnikov, I.A., Serenko, A.V., Sboev, A.G., Rybka, R.B.

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Effective calculations on neuromorphic hardware based on spiking neural network approaches von Sboev, A. G., Serenko, A. V., Vlasov, D. S.

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A probabilistic-entropy approach of finding thematically similar documents with creating context-semantic graph for investigating evolution of society opinion von Moloshnikov, I.A., Sboev, A.G., Rybka, R.B., Gydovskikh, D.V.

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Application of Machine Learning to Construct Solitons of Generalized Nonlinear Schrödinger Equation von Sboev, A. G., Kudryashov, N. A., Moloshnikov, I. A., Nifontov, D. R., Zavertyaev, S. V., Rybka, R. B.

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A probabilistically entropic mechanism of topical clusterisation along with thematic annotation for evolution analysis of meaningful social information of internet sources von Gydovskikh, D. V., Moloshnikov, I. A., Naumov, A. V., Rybka, R. B., Sboev, A. G., Selivanov, A. A.

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COMPARATIVE ANALYSIS OF THE CALCULATION MODELS FOR ISCHEMIC HEART DISEASE OVERALL RISK IN RAILROAD WORKERS von Gorokhova, S. G., Muraseeva, E. V., Pfaff, V. F., Sboev, A. G., Moloshnikov, I. A., Atkov, O. Yu

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On the accuracy of Covid-19 forecasting methods in Russia for two years von Moloshnikov, I.A., Sboev, A.G., Naumov, A.V., Zavertyaev, S.V., Rybka, R.B.

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Spiking neural network with local plasticity and sparse connectivity for audio classification von Rybka, Roman, Vlasov, Danila, Manzhurov, Alexander, Serenko, Alexey, Sboev, Alexander

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Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions von Chernikov, Alexander D., Eremin, Nikolay A., Stolyarov, Vladimir E., Sboev, Alexander G., Semenova-Chashchina, Olga K., Fitsner, Leonid K.

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On increasing the productive time of drilling oil and gas wells using machine learning methods von Dmitrievsky, Anatoliy N., Sboev, Alexander G., Eremin, Nikolai A., Chernikov, Alexander D., Naumov, Aleksandr V., Gryaznov, Artem V., Moloshnikov, Ivan A., Borozdin, Sergei O., Safarova, Elizaveta A.

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Syntactic Analysis of the Sentences of the Russian Language Based on Neural Networks von Sboev, A.G., Rybka, R., Moloshnikov, I., Gudovskih, D.

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An Algorithm of Finding Thematically Similar Documents with Creating Context-semantic Graph Based on Probabilistic-entropy Approach von Moloshnikov, I.A., Sboev, A.G., Rybka, R.B., Gydovskikh, D.V.

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Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters von Atkov, Oleg Yu., MD, PhD, Gorokhova, Svetlana G., MD, PhD, Sboev, Alexandr G., PhD, Generozov, Eduard V., PhD, Muraseyeva, Elena V., MD, PhD, Moroshkina, Svetlana Y, Cherniy, Nadezhda N

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Analytical properties of the perturbed FitzHugh–Nagumo model von Kudryashov, Nikolay A., Rybka, Roman B., Sboev, Aleksander G.

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Experimental investigation of free jet pulsations in the wind tunnel with an open test section von Baranov, S. A., Batura, N. I., Gadzhimagomedov, G. G., Sboev, D. S.

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A Quantitative Method of Text Emotiveness Evaluation on Base of the Psycholinguistic Markers Founded on Morphological Features von Sboev, A., Gudovskikh, D., Rybka, R., Moloshnikov, I.

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