Abstract
The ecological dynamic models of algal bloom in existence are of poor environmental adaptability and hard to reflect nonlinear dynamic change of algal bloom formation mechanism. To solve this problem, time variable is applied to mechanism-based model according to algal bloom nonlinear dynamic in this paper, and mechanism feature of algal bloom is represented by time function model and effecting function model. Data-driven modeling approaches including tabu search and genetic algorithm are also adopted to optimize structure and parameter for the time-varying nonlinear modeling to improve environmental adaptability and accuracy of the model. High-precision numerical solutions of the optimized time-varying nonlinear model is obtained by fourth-order Adams predictor–corrector method. This method finally realizes effective prediction of algal bloom.
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Acknowledgments
This work was financially supported by National Natural Science Foundation of China (51179002), Major Project of Beijing Municipal Education Commission science and technology development plans (KZ 201510011011), and General Project of Beijing Municipal Education Commission science and technology development plans (SQKM 201610011009). Those supports are gratefully acknowledged.
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Wang, L., Wang, X., Xu, J. et al. Time-varying nonlinear modeling and analysis of algal bloom dynamics. Nonlinear Dyn 84, 371–378 (2016). https://doi.org/10.1007/s11071-015-2552-9
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DOI: https://doi.org/10.1007/s11071-015-2552-9