Predicting disc cutter wear using two optimized machine learning techniques

Author:

Ghorbani EbrahimORCID,Yagiz SaffetORCID

Funder

Nazarbayev University

Publisher

Springer Science and Business Media LLC

Reference60 articles.

1. Maidl B, et al. Mechanised shield tunnelling. Wilhelm Ernst & Sohn; 2012.

2. Bruland A. Hard rock tunnel boring advance rate and cutter wear. Trondheim: Norwegian Institute of Technology. 1999.

3. Wijk G. A model of tunnel boring machine performance. Geotech Geol Eng. 1992;10:19–40.

4. Rostami J, Ozdemir L. A new model for performance prediction of hard rock TBMs. In: Proceedings of the rapid excavation and tunneling conference. 1993.

5. Yagiz S. Assessment of brittleness using rock strength and density with punch penetration test. Tunn Undergr Space Technol. 2009;24(1):66–74.

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