| Home > Publications database > Towards a neural network based flux density prediction – Using generative models to enhance CSP raytracing > print |
| 001 | 1025685 | ||
| 005 | 20250203103301.0 | ||
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| 037 | _ | _ | |a FZJ-2024-03074 |
| 100 | 1 | _ | |a Pargmann, Max |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a THE INTERNATIONAL CONFERENCE ON BATTERY FOR RENEWABLE ENERGY AND ELECTRIC VEHICLES (ICB-REV) 2022 |c South Tangerang |d 2021-09-27 - 2021-10-01 |w Indonesia |
| 245 | _ | _ | |a Towards a neural network based flux density prediction – Using generative models to enhance CSP raytracing |
| 260 | _ | _ | |c 2023 |b AIP Publishing |
| 300 | _ | _ | |a 030015-1–030015-12 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
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| 700 | 1 | _ | |a Pitz-Paal, Robert |0 P:(DE-HGF)0 |b 4 |
| 770 | _ | _ | |a SolarPACES: Solar Power & Chemical Energy Systems |
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