@inbook{410d2fa0d90e43bb8ec33affc62d45a0,
title = "Offshore geotechnical properties, a VR/neural-interpretation: Part 2",
abstract = "Natural soil is one of the most variable materials because of physical and chemical changes. The variation in soil properties significantly affects the failure mechanism and bearing capacity of a footing. The purpose of this study is to show the advantageous capabilities of neural networks for 3D-interpretation of properties where only scarce geotechnical data is available. The application example is a project in deep water Gulf of Mexico where millions of site-specific strength values are neuro-determined. This neuronal model is incorporated into a Virtual Reality engine for an effective exploiting and proper visualization of the computer-generated strengths.",
keywords = "Neural networks, Offshore geotechnical properties, Virtual reality",
author = "Silvia Garc{\'i}a and Paulina Trejo and Alberto Garc{\'i}a and C{\'e}sar Dumas and Celestino Valle-Molina",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.",
year = "2019",
doi = "10.1007/978-981-13-2306-5_7",
language = "Ingl{\'e}s",
series = "Lecture Notes in Civil Engineering",
publisher = "Springer",
pages = "67--73",
booktitle = "Lecture Notes in Civil Engineering",
}