Abstract
When modeling such phenomena as population dynamics, controllable flows, etc., a problem arises of adapting the existing models to a phenomenon under study. For this purpose, we propose to derive new models from the first principles by stochastization of one-step processes. Research can be represented as an iterative process that consists in obtaining a model and its further refinement. The number of such iterations can be extremely large. This work is aimed at software implementation (by means of computer algebra) of a method for stochastization of one-step processes. As a basis of the software implementation, we use the SymPy computer algebra system. Based on a developed algorithm, we derive stochastic differential equations and their interaction schemes. The operation of the program is demonstrated on the Verhulst and Lotka–Volterra models.
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Original Russian Text © M.N. Gevorkyan, A.V. Demidova, T.R. Velieva, A.V. Korol’kova, D.S. Kulyabov, L.A. Sevast’yanov, 2018, published in Programmirovanie, 2018, Vol. 44, No. 2.
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Gevorkyan, M.N., Demidova, A.V., Velieva, T.R. et al. Implementing a Method for Stochastization of One-Step Processes in a Computer Algebra System. Program Comput Soft 44, 86–93 (2018). https://doi.org/10.1134/S0361768818020044
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DOI: https://doi.org/10.1134/S0361768818020044