%0 Journal Article %1 Mandler2023CompFluids %A Mandler, Hannes %A Weigand, Bernhard %D 2023 %I Elsevier BV %J Computers & Fluids %K EXC2075 PN1 PN1-2(II) PN1-2B selected %P 105993 %R 10.1016/j.compfluid.2023.105993 %T Feature importance in neural networks as a means of interpretation for data-driven turbulence models %U https://doi.org/10.1016%2Fj.compfluid.2023.105993

@article{Mandler2023CompFluids, added-at = {2025-02-14T11:14:18.000+0100}, author = {Mandler, Hannes and Weigand, Bernhard}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2143b6521951fcaf082601ece058cbee3/simtechpuma}, doi = {10.1016/j.compfluid.2023.105993}, interhash = {9b26d70addf342754939409943e1e7cf}, intrahash = {143b6521951fcaf082601ece058cbee3}, journal = {Computers {\&} Fluids}, keywords = {EXC2075 PN1 PN1-2(II) PN1-2B selected}, month = {07}, pages = 105993, publisher = {Elsevier {BV}}, timestamp = {2025-02-14T11:14:18.000+0100}, title = {Feature importance in neural networks as a means of interpretation for data-driven turbulence models}, url = {https://doi.org/10.1016%2Fj.compfluid.2023.105993}, year = 2023 }