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  1. 2024

  2. Modeling of the thermal softening of metals under impact loads and their temperature–time correspondence

    Zhao, S., Petrov, Y. V., Zhang, Y., Volkov, G. A., Xu, Z. & Huang, F., 1 Jan 2024, In: International Journal of Engineering Science. 194, 103969.

    Research output: Contribution to journal › Article › peer-review

  3. 2023

  4. Long-Term Forecasting of Air Pollution Particulate Matter (PM2. 5) and Analysis of Influencing Factors

    Zhang, Y., Sun, Q., Liu, J. & Petrosian, O., 19 Dec 2023, In: Sustainability. 16, 1, 19.

    Research output: Contribution to journal › Article › peer-review

  5. Microgrid control for renewable energy sources based on deep reinforcement learning and numerical optimization approaches*

    Zhadan, A. U., Wu, H., Kudin, P. S., Zhang, Y. & Petrosian, O. L., 1 Nov 2023, In: Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya. 19, 3, p. 391-402 12 p.

    Research output: Contribution to journal › Article › peer-review

  6. Resource Allocation in Heterogeneous Network with Supervised GNNs

    Sun, Q., Zhang, Y., Wu, H. & Petrosian, O., 8 Jul 2023, In: Lecture Notes in Computer Science. 13969, p. 350-361 12 p.

    Research output: Contribution to journal › Article › peer-review

  7. ShapTime: A General XAI Approach for Explainable Time Series Forecasting

    Zhang, Y., Sun, Q., Qi, D., Liu, J., Ma, R. & Petrosian, O., 2023, (Accepted/In press) In: Lecture Notes in Networks and Systems. 15 p.

    Research output: Contribution to journal › Article › peer-review

  8. 2022

  9. Prediction of Next App in OS

    Ma, R., Zhang, Y., Liu, J., Petrosian, O. & Krinkin, K., 16 Jun 2022, Proceedings of 2022 3rd International Conference on Neural Networks and Neurotechnologies, NeuroNT 2022. Shaposhnikov, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 28-31 4 p. (Proceedings of 2022 3rd International Conference on Neural Networks and Neurotechnologies, NeuroNT 2022).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  10. FI-SHAP: Explanation of Time Series Forecasting and Improvement of Feature Engineering Based on Boosting Algorithm

    Zhang, Y., Petrosian, O., Liu, J., Ma, R. & Krinkin, K. V., 2022, Intelligent Systems and Applications: Proceedings of the 2022 Intelligent Systems Conference (IntelliSys). Springer Nature, Vol. 3. p. 745–758 (Lecture Notes in Networks and Systems; no. 544).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

  11. Forecasting and XAI for Applications Usage in OS

    Ma, R., Zhang, Y., Liu, J., Li, Y., Petrosian, O. & Krinkin, K. V., 2022, Machine Learning and Artificial Intelligence. IOS Press, p. 17-27 (Frontiers in Artificial Intelligence and Applications; no. 360).

    Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research › peer-review

  12. NEXT RUNNING APPLICATION PREDICTION IN OS USING TIME-SERIES FORECASTING AND XAI

    Ma, R., Zhang, Y., Liu, J. & Petrosian, O., 2022, In: ПРОЦЕССЫ УПРАВЛЕНИЯ И УСТОЙЧИВОСТЬ. 9, 1, p. 329-338

    Research output: Contribution to journal › Conference article › peer-review

  13. 2021

  14. Comparison and explanation of forecasting algorithms for energy time series

    Zhang, Y., Ma, R., Liu, J., Liu, X., Petrosian, O. & Krinkin, K., 1 Nov 2021, In: Mathematics. 9, 21, 2794.

    Research output: Contribution to journal › Article › peer-review

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