Gokhan KilicLevent Eren2025-10-062018092698510926-985110.1016/j.jappgeo.2018.02.026https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042944979&doi=10.1016%2Fj.jappgeo.2018.02.026&partnerID=40&md5=ddd76dcfd1fefbeb775eb4deb24c2643https://gcris.yasar.edu.tr/handle/123456789/9570This paper reports on the fundamental role played by Ground Penetrating Radar (GPR) alongside advanced processing and presentation methods during the tunnel boring project at a Dam and Hydro–Electric Power Station. It identifies from collected GPR data such issues as incomplete grouting and the presence of karst conduits and voids and provides full details of the procedures adopted. In particular the application of collected GPR data to the Neural Network (NN) method is discussed. © 2023 Elsevier B.V. All rights reserved.EnglishGpr, Karst Conduits, Ndt, Neural Network, Tbm, Geological Surveys, Ground Penetrating Radar Systems, Landforms, Ground Penetrating Radar, It Identify, Karst Conduit, Karst Voids, Network-based, Neural Network Method, Neural-networks, Radar Data, Tbm, Tunnel Boring, Nondestructive Examination, Artificial Neural Network, Dam, Ground Penetrating Radar, Hydroelectric Power Plant, Karst, Tunnel, VoidGeological surveys, Ground penetrating radar systems, Landforms, Ground Penetrating Radar, IT Identify, Karst conduit, Karst voids, Network-based, Neural network method, Neural-networks, Radar data, TBM, Tunnel boring, Nondestructive examination, artificial neural network, dam, ground penetrating radar, hydroelectric power plant, karst, tunnel, voidArticle