Multi-agent simulation model of grassland land use change

Yuxian Shen

doi:10.1117/12.2646801

7 September 2022 Multi-agent simulation model of grassland land use change

Yuxian Shen

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123290Q (2022) https://doi.org/10.1117/12.2646801
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

To complete the simulation model design of grassland land use change based on Repast Simphony platform, it is necessary to simulate and predict the state feedback and specific change process of grassland land under different influencing factors such as complexity, nonlinearity and interactivity. In this process of model design, the grassland land use change in a certain area is taken as the research object, the present situation of grassland land use and the significance of model establishment are deeply discussed, and the model establishment objectives, model environment and so on are analyzed, and finally the simulation experiment is completed. Through simulation, it can be determined that the transfer of animal husbandry labor force, industrial utilization mode and government policy have certain influence on the sustainable development of grassland ecology. At this stage, the problems of oversimplification and low simulation degree existing in the application of multi-agent system are perfected and supplemented, which has high practical value. Therefore, the multi-agent simulation model of grassland land use change can provide some support for the government to carry out grassland management and herdsmen to make rational use of grassland.

Citation Download Citation

Yuxian Shen "Multi-agent simulation model of grassland land use change", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123290Q (7 September 2022); https://doi.org/10.1117/12.2646801

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