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Xin Huang

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Proceedings Article | 5 July 2024 Paper

Simulation and prediction study based on Lotka-Volterra model and grey neural network

Boren Xie, Xin Huang, Dongyang Wang

Proceedings Volume 13184, 1318462 (2024) https://doi.org/10.1117/12.3032961

KEYWORDS: Data modeling, Neural networks, Differential equations, Machine learning, Modeling, Computer simulations, Systems modeling, Binary data, Visualization, Visual process modeling

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In this research, we innovatively utilize differential equations to simulate ituation in the real world, offering a rigorous mathematical framework for our predictive model. The Lotka-Volterra model forms the basis of our simulation, enabling the detailed representation of species interactions over time. Through sophisticated data processing techniques, including normalization and imputation for missing values, we enhance the fidelity of our simulation inputs. The application of a grey neural network, tailored with a sigmoid activation function and optimized learning rate, allows for the accurate prediction of future population trends. A key contribution of our work is the visualization of simulation results, achieved through graphical representations, which not only validates our model but also provides intuitive insights into the complex dynamics governing species populations. This study not only showcases the integration of mathematical modeling with neural networks for ecological predictions but also demonstrates the power of visualization in comprehending and communicating complex data patterns.

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