Nonlinear dynamic numerical analysis and prediction of complex system based on bivariate cycling time stochastic differential equation

Abstract In order to deal with the problem of low precision and ignoring the influence of some factors on the growth system of cyanobacteria, this paper considers the effects of light, water temperature and other influencing factors to analyze cyanobacteria growth system. The time stochastic differential equation of cyanobacteria growth with double nutrient cycling is established. The numerical analysis and the intelligent evolutionary algorithm are used to optimize the steady parameters in the time stochastic differential equation of cyanobacteria growth. The light, water temperature and other factors is used to build time series modeling. The time stochastic parameters and the prediction of cyanobacteria biomass is realized. The bifurcation theory and the central manifold theory were used to analyze the nonlinear dynamics of cyanobacteria growth with double nutrient cycling system, so that the conditions of cyanobacteria bloom and prediction of cyanobacteria blooms are achieved. Compared with the existing research, the method proposed in this paper not only determines the conditions of cyanobacteria bloom, but also improves the accuracy of water bloom prediction, and provides an effective reference for environmental protection departments.