244
A. V. Panteleev and M. M. S. Karane
6. Rere, L.M., Fanany, M.I., Arymurthy, A.: Metaheuristic algorithms for convolution neural
network. Comput. Intell. Neuro Sci. 2016, 1537325 (2016)
7. Panteleev, A., Karane, M.: Hybrid multi-agent optimization method of interpolation search.
AIP Conf. Proc. 2181, 020028 (2019)
8. Neumaier, A.: Personal page. https://www.mat.univie.ac.at/~neum/. Last accessed 2020/09/20
9. Mishra, S.K.: Some new test functions for global optimization and performance of repulsive
particle swarm method. https://ssrn.com/abstract=926132. Last accessed 2020/09/20
10. Bacanin, N., Pelevic, B., Tuba, M.: Krill herd (KH) algorithm for portfolio optimization. In:
International Conference on Mathematics and Computers in Business, Manufacturing and
Tourism, pp. 39–44. Baltimore, USA (2013)
11. Gandomi, A.H., Alavi, A.H.: Krill herd: a new bio-inspired optimization algorithm. Commun.
Nonlinear Sci. Numer. Simulat. 17(5), 4831–4845 (2012)
12. Rybakov, K.A.: Modeling linear nonstationary stochastic systems by spectral method. Diff.
Eqn. Control Process. (3), 98–128 (in Russian) (2020)
13. Rybakov, K.A.: Spectral method of analysis and optimal estimation in linear stochastic systems.
Int. J. Model. Simul. Sci. Comput. 11(3), 2050022 (2020)
14. Panteleev, A.V., Karane, M.M.S.: Multi-agent optimization algorithms for a single class
of optimal deterministic control systems. In: Jain, L.C., Favorskaya, M.N., Nikitin, I.S.,
Reviznikov, D.L. (eds.) Advances in Computational Mechanics and Numerical Simulation.
SIST, vol. 173, pp. 271–291. Springer, Singapore (2020)
15. Finkelstein, E.A.: Computational technologies of approximation of the reachable set of a
controlled system: Dissertation for the Degree of Canada of Technology Sciences. Institute
of System Dynamics and Control Theory, Irkutsk (in Russian) (2018)
A. V. Panteleev and M. M. S. Karane
6. Rere, L.M., Fanany, M.I., Arymurthy, A.: Metaheuristic algorithms for convolution neural
network. Comput. Intell. Neuro Sci. 2016, 1537325 (2016)
7. Panteleev, A., Karane, M.: Hybrid multi-agent optimization method of interpolation search.
AIP Conf. Proc. 2181, 020028 (2019)
8. Neumaier, A.: Personal page. https://www.mat.univie.ac.at/~neum/. Last accessed 2020/09/20
9. Mishra, S.K.: Some new test functions for global optimization and performance of repulsive
particle swarm method. https://ssrn.com/abstract=926132. Last accessed 2020/09/20
10. Bacanin, N., Pelevic, B., Tuba, M.: Krill herd (KH) algorithm for portfolio optimization. In:
International Conference on Mathematics and Computers in Business, Manufacturing and
Tourism, pp. 39–44. Baltimore, USA (2013)
11. Gandomi, A.H., Alavi, A.H.: Krill herd: a new bio-inspired optimization algorithm. Commun.
Nonlinear Sci. Numer. Simulat. 17(5), 4831–4845 (2012)
12. Rybakov, K.A.: Modeling linear nonstationary stochastic systems by spectral method. Diff.
Eqn. Control Process. (3), 98–128 (in Russian) (2020)
13. Rybakov, K.A.: Spectral method of analysis and optimal estimation in linear stochastic systems.
Int. J. Model. Simul. Sci. Comput. 11(3), 2050022 (2020)
14. Panteleev, A.V., Karane, M.M.S.: Multi-agent optimization algorithms for a single class
of optimal deterministic control systems. In: Jain, L.C., Favorskaya, M.N., Nikitin, I.S.,
Reviznikov, D.L. (eds.) Advances in Computational Mechanics and Numerical Simulation.
SIST, vol. 173, pp. 271–291. Springer, Singapore (2020)
15. Finkelstein, E.A.: Computational technologies of approximation of the reachable set of a
controlled system: Dissertation for the Degree of Canada of Technology Sciences. Institute
of System Dynamics and Control Theory, Irkutsk (in Russian) (2018)