Fugro wins geotechnical machine-learning competition

A team of Fugro employees has won a global competition in geotechnical machine-learning.

Competing with 60 other teams from industry and academia around the world, the Fugro team came first in the pile-driving prediction event organised as part of the International Symposium on Frontiers in Offshore Geotechnics (ISFOG) 2020 conference, which will be held in Austin, Texas, in August.

The competition ran from April to December 2019, and ended on 1 January 2020, when it was announced that Fugro had won.

Using the supplied dataset of cone penetration test results, hammer energy and pile dimensions, competing teams had to predict the most accurate pile installation driving blowcount versus depth for jacket piles installed in the North Sea; in essence, the number of hammer blows required to drive the pile a given unit of depth. The Fugro team combined machine-learning techniques with their geotechnical expertise to develop a stable and reliable pile-driving model that proved the clear winner.

Fugro ranked first in ISFOG’s recent offshore pile-driving prediction competition, where machine-learning tools predicted hammer blow count for applications such as the typical offshore installation using a hydraulic hammer shown in this photo

The competition was hosted on Kaggle, a subsidiary of Google that is an online community of data scientists and machine-learning practitioners. The multidisciplinary Fugro team, comprising data scientists, geotechnical consultants and pile installation specialists from around the world, worked together for 4 months in the latter part of 2019 to accomplish this achievement.

Website Fugro 

Website ISGOF

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