The application belongs to the technical field of
information processing, and provides a kind of energy-consuming enterprise
time series data prediction method and
system based on reversible calculation, the energy-consuming enterprise
time series data prediction model in the application is a trained
deep learning model, the input sample during training includes local
time series information and hierarchical time series information;At the same time, the actual time
series data is compared with the predicted time
series data, and the predicted result is revised according to the comparison result, on the basis of considering the particularity and complexity of hierarchical time series information, through the reversible calculation of the comparison of actual time
series data and predicted sequence data, in the
high energy-consuming enterprise time series
data prediction task, the modeling of long-term dependence relationship, flexibility,
adaptation to different time scales, support
variable length sequence, multi-
task learning and
processing of abnormal value and fluctuation can be embodied Better characteristics, selecting
root mean square error as
loss function can make the prediction model get better constraint on enterprise time series data prediction task.