Backhaus, Jan OnneJan OnneBackhaus2021-10-132021-10-132021-10Bautechnik 98 (10): 767-774 (2021-10)http://hdl.handle.net/11420/10512Use of neural networks for the prediction of the material volume of injection sites in tunnel construction. In this paper, a method is presented that uses digital documentation on injection construction sites to calculate automated, construction-accompanying predictions of the injection quantities still to be expected. In the construction project under investigation, waterproofing injections are being made as part of the Stuttgart 21 project for a 3.2 km long, twin-tube railroad tunnel. The presented method uses a particular form of a neural network, the Feed Forward Network. The network is trained with the injection quantities per tunnelmeter of one tunnel tube to predict the other's injection quantities. After a brief introduction to the operation of neural networks, it is shown that the presented method can forecast the total injection quantities with an accuracy > 5 %. Renesco GmbH has collected the data in cooperation with eguana GmbH.de0932-8351202110767-774Building Managementconstruction managementconstruction time forecastGeotechnical engineeringgroutingneural networkstunnelingTunnellingJournal Article10.1002/bate.202100018Other