Abstract
In recent years, with the continuous development of artificial intelligence, deep learning, as an important method of artificial intelligence learning, has made great progress. At present, deep learning has been successfully applied in many engineering fields. Environmental science itself involves a wide range, among which environmental geochemistry is an important branch. The combination of environmental geochemical problems and deep learning can better study the role of geochemical problems in environmental investigation, and also can use the basic situation of regional environmental elements to predict mineral resources.
Highlights
The so-called environment is the synthesis of various factors for human survival and development [1]
Chemical pollutants in soil and sediment enter food and cause human food chain poisoning. It is less affected by human activities, and the regional environmental indicators exceed the standard, which is mostly caused by the natural geological evolution
Based on deep learning method, this paper mainly studies the prediction of mineral resources using environmental geochemical data
Summary
The so-called environment is the synthesis of various factors for human survival and development [1]. An important purpose of environmental geochemical survey is to determine the environmental background and its changing trend, and monitor it regularly, so as to provide scientific data for the protection of human living environment and sustainable development. Soil is the main medium of environmental geochemical element survey. Chemical pollutants in soil and sediment enter food and cause human food chain poisoning. It is less affected by human activities, and the regional environmental indicators exceed the standard, which is mostly caused by the natural geological evolution. The method of deep learning is used to learn the soil geochemical elements corresponding to the known deposit location in the region, and other unknown areas are learned
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