The study of species population change is one of the most classic topics in biology. In this paper, we consider not only intra-race competition but also competition between two species. It is assumed that the resources in the environment are finite in this paper. Improved on the Logistic Population Growth Model from Malthusian model, we built the Competitive Hunter Model for trout and bass referring to the Lotka-Volterra Model. In this paper, we presented the assumptions of the model and analyzed the equilibrium points of the model in numerical analysis and the typical trajectories in phase planes in graphical analysis.
This paper considers how best strategies should be chosen to effectively mitigate light pollution situations in cities with different light pollution scenarios. Firstly, a mathematical programming model is used to analyze the light pollution characteristics of four typical areas: protected areas, rural communities, suburban communities and urban communities, and four states are abstracted. Subsequently, using reinforcement learning models, the four abstracted states are used as the state space of the intelligences, while promoting green building and eco-city design, rationalizing the layout and height of road lighting, and improving the performance of lighting equipment and lighting solutions as the three governance strategies, constitute the action space. Through continuous training it was concluded that areas with strong road and residential lighting, frequent night-time camping and other activities adopt the strategy of rationalizing the layout and height of road lighting; areas with dense night-time light sources, high light intensity and long duration adopt the strategy of promoting green architecture and eco-urban design. And areas with a high demand for night lighting, high air pollution index or large open areas adopt the conclusion of increasing lighting equipment and lighting solutions.
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