Research and Application on CNN-ERI Geological Identification Model
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Abstract
With the improvement of geological exploration accuracy requirements of infrastructure projects, it is of great significance to research the application of artificial intelligence technology in geological exploration data analysis and processing. Based on the data dimensionality reduction processing function of convolutional neural network technology, an improved CNN-ERI geological identification model was proposed. This model's superiority in geological identification is analyzed. The influence of data volume and environmental factors on the identification accuracy of the model is researched. Taking a tunnel project as an example, the specific application of this model is discussed.
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