Artificial intelligence–based mountain soil erosion and the impact of climate conditions on marathon competitions

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Abstract

Artificial intelligence is another breakthrough under the rapid development of the Internet and technology. It provides possibilities for the learning of knowledge, the automation of knowledge acquisition, the universality of expressing knowledge, and the efficiency of searching and solving. In the context of the global development of artificial intelligence, it also provides the possibility for the activation of the agent. Mountain is an important geomorphic unit on the earth’s surface. The biodiversity and the richness of resources are the foundation for storing tourism resources, water resources, and mineral resources. These abundant resources in the mountains also provide a good ecosystem for the surrounding areas and optimize the ecological environment of the surrounding areas. But the mountain ecosystem is actually very fragile. It can be compared to the engine of global climate change. Under the influence of global climate change, the diversity of species and the production of social development services will be affected. The water and soil elements of the ecosystem will change accordingly, and the coupling process will also change. In 2020, the domestic marathon event data will increase year by year, and the number of participants will continue to increase. Marathon is a challenging sport for all people to participate in, and its key point is no longer the word “sports.” “Marathon” is people’s pursuit of health and self-challenge. Completing the full course of the marathon will give people a sense of pride and accomplishment from the bottom of their hearts. The Chinese Athletics Association held 1102 marathons in 2020, an increase of 236% from the 328 in 2019. But with the rapid development of marathon sports, many problems have also appeared.

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APA

Wang, D. (2021, June 1). Artificial intelligence–based mountain soil erosion and the impact of climate conditions on marathon competitions. Arabian Journal of Geosciences. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s12517-021-07245-6

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