The invention discloses a multi-scale
time sequence prediction system and method for adaptive hierarchical frequency, which realizes standardized processes of data preprocessing, dynamic hierarchical sampling, frequency attention modeling, cross-scale attention fusion and prediction output through
modular architecture design, is clear in interface between modules, is easy to deploy and expand, and is high in practicability. The problem of non-
uniform system architecture in the prior art is solved; in the dynamic
stratified sampling step, through region division and dynamic sampling rate distribution,
adaptive matching of a down-sampling rate and a local
frequency characteristic of a non-stationary sequence is realized; in the frequency attention modeling step, through
frequency domain conversion and attention
weight distribution, the sensitivity of the
system to periodicity and frequency characteristics is enhanced, and key frequency components can be focused according to prediction task requirements; according to the cross-scale attention fusion step, through
feature dimension unification and cross-scale correlation calculation, the dependency among the scale features is effectively modeled, redundant information is filtered, and the fusion efficiency and the prediction precision are improved.