The application discloses a kind of
time series point value and interval value synchronous prediction method based on double decoding generation network, belong to
time series prediction technical field.For existing
time series prediction method is difficult to output point value and real physical interval value simultaneously, probability type interval lacks physical meaning,
interval prediction relies on sliding window and leads to low reliability and other problems, the application constructs the double decoding parallel architecture of the unification of space-time feature
encoder, point prediction decoder and
interval prediction decoder three;Global overall approximation strategy is adopted, and the
interval distribution of the whole time series is directly overall fitted, and the upper and lower limits of the complete interval are output at one time;Through multiple composite
loss function, the interval generation is finely constrained from five dimensions of boundary effectiveness, matching degree, coverage, width rationality and
reconstruction error.The model is trained in stages, and the point value and interval value prediction results can be output simultaneously after one forward
inference.The application is verified on measured
data set, and the point prediction accuracy and interval reliability are significantly better than existing models, which can adapt to real-time collaborative prediction scenarios such as
environmental monitoring, financial analysis, unmanned
system and other scenarios that need to obtain point value and interval value simultaneously.