A procedure for the short–term prediction of the thermal energy consumption of an hospital is shown in this paper. At first, linear ARX models are built to get information on the influence of the input variables on the output of the system. Therefore, non-linear models based on feedforward neural networks (NNARX) are built using the information provided by the linear estimate. The results obtained from the ARX and NNARX models are compared, concluding that NNARX models provide better results than ARX models, but the analysis of ARX models is necessary to obtain guidelines in the choice of the best regression vector as input for neural models.
Neural networks for energy flows prediction in facility systems
FROSINI, LUCIA;PETRECCA, GIOVANNI
1999-01-01
Abstract
A procedure for the short–term prediction of the thermal energy consumption of an hospital is shown in this paper. At first, linear ARX models are built to get information on the influence of the input variables on the output of the system. Therefore, non-linear models based on feedforward neural networks (NNARX) are built using the information provided by the linear estimate. The results obtained from the ARX and NNARX models are compared, concluding that NNARX models provide better results than ARX models, but the analysis of ARX models is necessary to obtain guidelines in the choice of the best regression vector as input for neural models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
