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A probabilistic deep learning approach for thermal and exer..:
Flores-Tlacuahuac, Antonio
;
Gutierrez-Limon, Miguel Angel
;
Sales-Cruz, Mauricio
Computers & Chemical Engineering. 168 (2022) - p. 108029 , 2022
Link:
https://doi.org/10.1016/j.compchemeng.2022.108029
RT Journal T1
A probabilistic deep learning approach for thermal and exergy forecasting in organic Rankine cycles
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.compchemeng.2022.108029&Exemplar=1&LAN=DE A1 Flores-Tlacuahuac, Antonio A1 Gutierrez-Limon, Miguel Angel A1 Sales-Cruz, Mauricio PB Elsevier BV YR 2022 SN 0098-1354 JF Computers & Chemical Engineering VO 168 SP 108029 LK http://dx.doi.org/https://doi.org/10.1016/j.compchemeng.2022.108029 DO https://doi.org/10.1016/j.compchemeng.2022.108029 SF ELIB - SuUB Bremen
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