Journal articles

Brester C., Ryzhikov I., Siponen S., Jayaprakash B., Ikonen J., Pitkänen T., Miettinen I.T., Torvinen E., Kolehmainen M. (2020) Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling. Sci Total Environ. 717:137249. doi: 10.1016/j.scitotenv.2020.137249. [link]

Brester C., Kauhanen J., Tuomainen T.-P., Voutilainen S., Rönkkö M., Ronkainen K., Semenkin E., Kolehmainen M. (2018) Evolutionary methods for variable selection in the epidemiological modeling of cardiovascular diseases. BioData Min. 11:18. doi: 10.1186/s13040-018-0180-x. [link]

Brester Ch., Ryzhikov I., Semenkina O. (2018) Generic scheme of a restart meta-heuristic operator for multi-objective genetic algorithms. International Journal on Information Technologies and Security. Vol. 10, no. 2, pp. 101-110. [pdf]

Brester C., Semenkin E., Sidorov M. (2016) Multi-objective heuristic feature selection for speech-based multilingual emotion recognition. Journal of Artificial Intelligence and Soft Computing Research. Vol. 6, no. 4, pp. 243-253. [pdf]

Conference papers

Brester C., Niska H., Ciszek R., Kolehmainen M. (2020) Weather-based fault prediction in electricity networks with artificial neural networks. IEEE World Congress on Computational Intelligence (IEEE WCCI). Accepted

Brester C., Ryzhikov I., Semenkin E., Kolehmainen M. (2019) On a restart metaheuristic for real-valued multi-objective evolutionary algorithms. Genetic and Evolutionary Computation Conference (GECCO) (Companion), pp. 197-198.

Brester C., Stanovov V., Voutilainen A., Tuomainen T.-P., Semenkin E., Kolehmainen M. (2019) Evolutionary fuzzy logic-based model design in predicting coronary heart disease and its progression. 11th International Joint Conference on Computational Intelligence (IJCCI), pp. 360-366.

Brester C., Ryzhikov I. (2019) Tuning parameters of differential evolution: self-adaptation, parallel Islands, or co-operation. 11th International Joint Conference on Computational Intelligence (IJCCI), pp. 259-264.

Brester C., Ryzhikov I., Tuomainen T.-P., Voutilainen A., Semenkin E., Kolehmainen M. (2018) Multi-objective approach for support vector machine parameter optimization and variable selection in cardiovascular predictive modeling. 5th International Conference on Informatics in Control, Automation and Robotics (ICINCO), vol. 1, pp. 209-215.

Brester C., Ryzhikov I., Semenkin E., Kolehmainen M. (2018) On island model performance for cooperative real-valued multi-objective genetic algorithms. 9th International Conference on Swarm Intelligence (ICSI), vol. 1, pp. 210-219.

Brester C., Ryzhikov I., Semenkin E. (2017) On performance improvement based on restart meta-heuristic implementation for solving multi-objective optimization problems. 8th International Conference on Swarm Intelligence (ICSI), vol. 2, pp. 23-30.

Brester C., Kauhanen J., Tuomainen T.P., Semenkin E., Kolehmainen M. (2016) Comparison of two-criterion evolutionary filtering techniques in cardiovascular predictive modelling. Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO’2016), Lisbon, Portugal. Vol. 1, pp. 140-145. [pdf]

Semenkina M., Akhmedova S., Brester C., Semenkin E. (2016) Choice of spacecraft control contour variant with self-configuring stochastic algorithms of multi-criteria optimization. Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO’2016), Lisbon, Portugal. Vol. 1, pp. 281-286. [pdf]

Sidorov M., Brester C., Ultes S., Schmitt A. (2016) Salient cross-lingual acoustic and prosodic features for English and German emotion recognition. Proceedings of the 7th International Workshop On Spoken Dialogue Systems (IWSDS), Lapland, Finland. [pdf]

Brester C., Semenkin E. (2015) Cooperative Multi-Objective Genetic Algorithm with Parallel Implementation. Advances in Swarm and Computational Intelligence. Part I, LNCS 9140, pp. 471–478. [pdf]

Sidorov M., Brester C., Schmitt A. (2015) Contemporary stochastic feature selection algorithms for speech-based emotion recognition. Proceedings of INTERSPEECH 2015, Dresden, Germany, pp. 2699-2703. [pdf]

Brester C., Semenkin E., Sidorov M., Semenkina O. (2015) Multicriteria neural network design in the speech-based emotion recognition problem. Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO’2015), Colmar, France. Vol. 1, pp. 621–628. [pdf]

Brester C., Semenkin E., Sidorov M., Kovalev I., Zelenkov P. (2015) Evolutionary feature selection for emotion recognition in multilingual speech analysis. Proceedings of IEEE Congress on Evolutionary Computation (CEC2015), Sendai, Japan, pp. 2406–2411. [pdf]

Brester C., Semenkin E., Sidorov M. (2014) Acoustic Emotion Recognition: Two Ways of Features Selection based on Self-Adaptive Multi-Objective Genetic Algorithm. Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO’2014), Vienna, Austria. Vol. 2, pp. 851–855. [pdf]

Sidorov M., Brester C., Minker W., Semenkin E. (2014) Speaker State Recognition with Neural Network-based Classification and Self-adaptive Heuristic Feature Selection. Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO’2014), Vienna, Austria. Vol. 1, pp. 699–703. [pdf]

Brester C., Semenkin E., Sidorov M. (2014) Speech-based emotion recognition: Application of collective decision making concepts. Proceedings of the International Conference on Computer Science and Artificial Intelligence (ICCSAI2014), Wuhan, China, pp. 216–220. [pdf]

Brester C., Semenkin E., Sidorov M., Minker W. (2014) Self-adaptive multi-objective genetic algorithms for feature selection. Proceedings of International Conference on Engineering and Applied Sciences Optimization, Kos Island, Greece, pp. 1838–1846. [pdf]

Sidorov M., Brester C., Minker W., Semenkin E. (2014) Speech-Based Emotion Recognition: Feature Selection by Self-Adapted Multi-Criteria Genetic Algorithm. Proceedings of the 9th edition of the Language Resources and Evaluation Conference (LREC), Reykjavik, Iceland, pp. 3481-3485. [pdf]