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ORCIDS. A. Dolenko
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Journal Articles
- 2023
[j1]Ismail M. Gadzhiev, Mikhail P. Knyshenko, Sergey Dolenko
, Alexei V. Samsonovich:
Inherent dimension of the affective space: Analysis using electromyography and machine learning. Cogn. Syst. Res. 78: 96-105 (2023)
Conference and Workshop Papers
- 2022
- [c27]Igor Isaev, Ivan Obornev, Eugeny Obornev, Eugeny Rodionov, Mikhail Shimelevich, Sergey Dolenko:
Multitasking learning in missing data recovery for the integration of geophysical methods in solving an inverse problem of exploration geophysics. BICA*AI 2022: 777-784 - 2019
- [c26]Irina Myagkova, Alexander Efitorov, Vladimir Shiroky, Sergey Dolenko:
Quality of Prediction of Daily Relativistic Electrons Flux at Geostationary Orbit by Machine Learning Methods. ICANN (4) 2019: 556-565 - 2018
- [c25]Tatiana A. Dolenko, Alexander Efitorov, Olga Sarmanova, Olga Kotova, Igor Isaev, Kirill Laptinskiy, Sergey Dolenko, Sergey Burikov:
Application of Wavelet Neural Networks for Monitoring of Extraction of Carbon Multi-Functional Medical Nano-Agents from the Body. BICA 2018: 177-183 - [c24]Alexander Efitorov, Vyacheslav A. Orlov, Vadim L. Ushakov, Vladimir Shiroky, Sergey Dolenko:
Comparison of nonlinear methods of motion correction in fMRI data. BICA 2018: 188-192 - [c23]Vladimir Shirokii, Roman Batusov, Arthur A. Chubarov, Sergey Dolenko, Alexei V. Samsonovich:
Patterns of Cognitive Activity in a Human vs Collaborative Robot Interactive Game. BICA 2018: 495-499 - [c22]Igor Isaev, Sergey Burikov, Tatiana A. Dolenko, Kirill Laptinskiy, Alexey Vervald, Sergey Dolenko:
Joint Application of Group Determination of Parameters and of Training with Noise Addition to Improve the Resilience of the Neural Network Solution of the Inverse Problem in Spectroscopy to Noise in Data. ICANN (1) 2018: 435-444 - [c21]Alexander Efitorov, Vladimir Shiroky, Sergey Dolenko:
A Neural Network of Multiresolution Wavelet Analysis. ICANN (2) 2018: 567-574 - 2017
- [c20]Roman Batusov, Sergey Dolenko, Irina Myagkova:
Neural Network Prediction of Daily Relativistic Electrons Fluence in the Outer Radiation Belt of the Earth: Selection of Delay Embedding Method. BICA 2017: 86-91 - [c19]Alexander Efitorov, Tatiana A. Dolenko, Sergey Burikov, Kirill Laptinskiy, Sergey Dolenko:
Study of Efficiency of Dividing the Problem Space as a Means to Improve Solution of Multi-parameter Inverse Problem by Adaptive Methods. BICA 2017: 122-127 - [c18]Igor Isaev, Sergey Dolenko:
Training with Noise Addition in Neural Network Solution of Inverse Problems: Procedures for Selection of the Optimal Network. BICA 2017: 171-176 - [c17]Igor Isaev, Ekaterina Vervald, Olga Sarmanova, Sergey Dolenko:
Neural Network Solution of an Inverse Problem in Raman Spectroscopy of Multi-Component Solutions of Inorganic Salts: Group Determination as a Method to Increase Noise Resilience of the Solution. BICA 2017: 177-182 - 2016
- [c16]Irina Myagkova, Vladimir Shiroky, Sergey Dolenko:
Effect of Simultaneous Time Series Prediction with Various Horizons on Prediction Quality at the Example of Electron Flux in the Outer Radiation Belt of the Earth. ICANN (2) 2016: 317-325 - [c15]Alexander Efitorov, Tatiana A. Dolenko, Sergey Burikov, Kirill Laptinskiy, Sergey Dolenko:
Solution of an Inverse Problem in Raman Spectroscopy of Multi-component Solutions of Inorganic Salts by Artificial Neural Networks. ICANN (2) 2016: 355-362 - [c14]Igor Isaev, Eugeny Obornev, Ivan Obornev, Mikhail Shimelevich, Sergey Dolenko:
Increase of the Resistance to Noise in Data for Neural Network Solution of the Inverse Problem of Magnetotellurics with Group Determination of Parameters. ICANN (1) 2016: 502-509 - 2015
- [c13]Irina Myagkova, Sergey Dolenko, Vladimir Shiroky, Natalia Sentemova, Igor Persiantsev:
Horizon of Neural Network Prediction of Relativistic Electrons Flux in the Outer Radiation Belt of the Earth. EANN Workshops 2015: 9:1-9:5 - [c12]Sergey Dolenko, Alexander Efitorov, Sergey Burikov, Tatiana A. Dolenko, Kirill Laptinskiy, Igor Persiantsev:
Neural Network Approaches to Solution of the Inverse Problem of Identification and Determination of the Ionic Composition of Multi-component Water Solutions. EANN 2015: 109-118 - 2014
- [c11]Sergey Dolenko, Sergey Burikov, Tatiana A. Dolenko, Alexander Efitorov, Kirill Gushchin, Igor Persiantsev:
Neural Network Approaches to Solution of the Inverse Problem of Identification and Determination of Partial Concentrations of Salts in Multi-сomponent Water Solutions. ICANN 2014: 805-812 - 2013
- [c10]Sergey Dolenko, Igor Isaev, Eugeny Obornev, Igor Persiantsev, Mikhail Shimelevich:
Study of Influence of Parameter Grouping on the Error of Neural Network Solution of the Inverse Problem of Electrical Prospecting. EANN (1) 2013: 81-90 - 2012
- [c9]Sergey Dolenko, Tatiana A. Dolenko, Sergey Burikov, Victor V. Fadeev, Alexey Sabirov, Igor Persiantsev:
Comparison of Input Data Compression Methods in Neural Network Solution of Inverse Problem in Laser Raman Spectroscopy of Natural Waters. ICANN (2) 2012: 443-450 - 2009
- [c8]Sergey Dolenko, Alexander Guzhva, Igor Persiantsev, Ju. S. Shugai:
Multi-stage Algorithm Based on Neural Network Committee for Prediction and Search for Precursors in Multi-dimensional Time Series. ICANN (2) 2009: 295-304 - [c7]Alexander Guzhva, Sergey Dolenko, Igor Persiantsev:
Multifold Acceleration of Neural Network Computations Using GPU. ICANN (1) 2009: 373-380 - [c6]Sergey Dolenko, Alexander Guzhva, Eugeny Obornev, Igor Persiantsev, Mikhail Shimelevich:
Comparison of Adaptive Algorithms for Significant Feature Selection in Neural Network Based Solution of the Inverse Problem of Electrical Prospecting. ICANN (2) 2009: 397-405 - 2005
- [c5]S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju. S. Shugai:
Neural Network Algorithm for Events Forecasting and Its Application to Space Physics Data. ICANN (2) 2005: 527-532 - 2001
- [c4]S. A. Dolenko, I. V. Boychuk, I. V. Churina, Tatiana A. Dolenko, Victor V. Fadeev, I. G. Persiantsev, Brian Carse:
Solution of Inverse Problems in Laser Spectroscopy of Water Media with the Help of Neural Networks. FLAIRS 2001: 470-474 - [c3]S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju. S. Shugai, Anthony G. Pipe:
Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers. FLAIRS 2001: 475-479 - [c2]S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju. S. Shugai, A. V. Dmitriev, A. V. Suvorova, I. S. Veselovsky:
Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers. Multiple Classifier Systems 2001: 289-298 - 1998
- [c1]S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju. S. Shugai:
Construction of Hierarchical Neural Classifers by Self-Organizing Error Back-Propagation. NC 1998: 113-116
Coauthor Index
aka: Igor Persiantsev
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