Genetic Programming Bibliography entries for Mikhail A Maslyaev

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GP coauthors/coeditors: Alexander A Hvatov, Anna V Kalyuzhnaya, Nikolay O Nikitin, Mikhail Yachmenkov, Alexander Boukhanovsky,

Genetic Programming Articles by Mikhail A Maslyaev

• Mikhail A. Maslyaev and Alexander A. Hvatov. Multiobjective evolutionary discovery of equation-based analytical models for dynamical systems. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 23(1):97-104, 2023. details

• Anna V. Kalyuzhnaya and Nikolay O. Nikitin and Alexander Hvatov and Mikhail Maslyaev and Mikhail Yachmenkov and Alexander Boukhanovsky. Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning. Entropy, 23(1) 2021. details

• Mikhail Maslyaev and Alexander Hvatov and Anna V. Kalyuzhnaya. Partial differential equations discovery with EPDE framework: application for real and synthetic data. Journal of Computational Science, 53:101345, 2021. details

Genetic Programming conference papers by Mikhail A Maslyaev

1. Mikhail Maslyaev and Alexander Hvatov. Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pages 603-606, Lisbon, Portugal, 2023. Association for Computing Machinery. details

2. Mikhail Maslyaev and Alexander Hvatov. Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equation. In 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, 2022. details

3. Mikhail Maslyaev and Alexander Hvatov. Multi-Objective Discovery of PDE Systems Using Evolutionary Approach. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 596-603, Krakow, Poland, 2021. details

4. Alexander Hvatov and Mikhail Maslyaev. The Data-Driven Physical-Based Equations Discovery Using Evolutionary Approach. In Richard Allmendinger and Hugo Terashima Marin and Efren Mezura Montes and Thomas Bartz-Beielstein and Bogdan Filipic and Ke Tang and David Howard and Emma Hart and Gusz Eiben and Tome Eftimov and William La Cava and Boris Naujoks and Pietro Oliveto and Vanessa Volz and Thomas Weise and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Rui Wang and Ran Cheng and Guohua Wu and Miqing Li and Hisao Ishibuchi and Jonathan Fieldsend and Ozgur Akman and Khulood Alyahya and Juergen Branke and John R. Woodward and Daniel R. Tauritz and Marco Baioletti and Josu Ceberio Uribe and John McCall and Alfredo Milani and Stefan Wagner and Michael Affenzeller and Bradley Alexander and Alexander (Sandy) Brownlee and Saemundur O. Haraldsson and Markus Wagner and Nayat Sanchez-Pi and Luis Marti and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and Matthew Johns and Nick Ross and Ed Keedwell and Herman Mahmoud and David Walker and Anthony Stein and Masaya Nakata and David Paetzel and Neil Vaughan and Stephen Smith and Stefano Cagnoni and Robert M. Patton and Ivanoe De Falco and Antonio Della Cioppa and Umberto Scafuri and Ernesto Tarantino and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Erik Hemberg and Riyad Alshammari and Tokunbo Makanju and Fuijimino-shi and Ivan Zelinka and Swagatam Das and Ponnuthurai Nagaratnam and Roman Senkerik editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pages 129-130, internet, 2020. Association for Computing Machinery. details