Articles | Volume 9, issue 5
Research article
03 Sep 2021
Research article |  | 03 Sep 2021

Inverse modeling of turbidity currents using an artificial neural network approach: verification for field application

Hajime Naruse and Kento Nakao

Data sets

Training and test data set of thickness distribution of turbidites Hajime Naruse

Model code and software

nninv1d Hajime Naruse

Short summary
This paper proposes a method to reconstruct the hydraulic conditions of turbidity currents from turbidites. We investigated the validity and problems of this method in application to actual field datasets using artificial data. Once this method is established, it is expected that the method will elucidate the generation process of turbidity currents and will help to predict the geometry of resultant turbidites in deep-sea environments.