Network Stability Study Based on Improved Lotka-Volterra Model with AHP

This paper utilizes the Lotka-Volterra model integrated with machine learning techniques for research. Firstly, a dynamic regulation model is constructed by introducing multiple parameters and variables, with a series of equations to describe their dynamic relationships. Then, the AHP model combined with machine learning algorithms is adopted. A random forest model is trained with historical data to determine weights, and a multi-level analysis structure is built, along with the establishment of several related models. An ecological network model encompassing multiple species and trophic levels is also established. Based on the Lotka-Volterra model, multiple sets of differential equations are set up to describe the relationships among species, and a neural network model is used to evaluate the impact of relevant factors on system stability. Through model analysis, this study draws many conclusions, such as the influence of different parameter changes on various aspects of the system. Meanwhile, the advantages and limitations of the model are summarized, providing methodological references and improvement directions for future research.