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Resumen de: NL4000175A

The present invention provides a geotechnical engineering geological disaster prediction method and system based on deep learning. The geotechnical engineering geological disaster prediction method and system based on deep learning include a data acquisition module, a data preprocessing module, a feature extraction module, a deep learning model module, and a prediction output module. The data acquisition module uses remote sensing technology, geological exploration equipment, and sensors to collect multidimensional data such as soil properties, meteorological data, groundwater level, and terrain slope. The geotechnical engineering geological disaster prediction method and system based on deep learning ensure the accuracy and reliability of the original data and improve the quality of model training by adopting multi-source data acquisition as well as optimization of the data preprocessing and feature extraction modules. In particular, the deep learning model module adopts a convolutional neural network structure to capture spatial features in geological data, enabling automatic learning of more complex patterns, thereby improving prediction accuracy.