- S. Piccolroaz, S. Zhu, R. Ladwig, L. Carrea, S. Oliver, A. P. Piotrowski, M. Ptak, R. Shinohara, M. Sojka, R. I. Woolway, D. Z. Zhu, “Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects”, Reviews of Geophysics, 62, № 1, 2024, e2023RG000816
- Jing Zhang, Jing Tian, Yang Cao, Yuxiang Yang, Xiaobin Xu, “Deep time–frequency representation and progressive decision fusion for ECG classification”, Knowledge-Based Systems, 190, 2020, 105402
- Saptarshi Sengupta, Sanchita Basak, Richard Peters, “Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives”, MAKE, 1, № 1, 2018, 157
- Giacomo Borghi, Michael Herty, Lorenzo Pareschi, 2022 IEEE 61st Conference on Decision and Control (CDC), 2022, 4131
- Pavel Trojovský, Mohammad Dehghani, “Subtraction-Average-Based Optimizer: A New Swarm-Inspired Metaheuristic Algorithm for Solving Optimization Problems”, Biomimetics, 8, № 2, 2023, 149
- Gustavo Mendes Platt, Marcelo Escobar Aragão, Fernanda Cabral Borges, Douglas Alves Goulart, “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”, Ing. Inv., 40, № 1, 2020, 27
- Javier Del Ser, Eneko Osaba, Daniel Molina, Xin-She Yang, Sancho Salcedo-Sanz, David Camacho, Swagatam Das, Ponnuthurai N. Suganthan, Carlos A. Coello Coello, Francisco Herrera, “Bio-inspired computation: Where we stand and what's next”, Swarm and Evolutionary Computation, 48, 2019, 220
- Jean Bigeon, Sébastien Le Digabel, Ludovic Salomon, “DMulti-MADS: mesh adaptive direct multisearch for bound-constrained blackbox multiobjective optimization”, Comput Optim Appl, 79, № 2, 2021, 301
- Daniela Lera, Yaroslav D. Sergeyev, 2070, 2019, 020033
- Afshin Faramarzi, Mohammad Heidarinejad, Seyedali Mirjalili, Amir H. Gandomi, “Marine Predators Algorithm: A nature-inspired metaheuristic”, Expert Systems with Applications, 152, 2020, 113377