Abstract
The strength reduction method is often used to predict the stability of soil slopes with complex soil properties and failure mechanisms. However, it requires a considerable computational effort. In this paper, we make use of a convolutional neural network to reduce the computational cost. The factor of safety of 600 slopes with different inclination and soil properties is first calculated with the strength reduction method. A convolutional neural network is then trained and validated. We demonstrate the performance of our approach and show how to augment the dataset to further enhance its capability and prevent overfitting.