Time-series forecasting is crucial across various domains. Existing models struggle with complex temporal patterns. TILDE-Q addresses this by introducing a shape-aware loss function that considers amplitude, phase distortions, and shapes of time-series sequences. Experimental results show TILDE-Q outperforms other metrics in real-world applications like electricity, traffic, and weather forecasting.
toiselle kielelle
lähdeaineistosta
arxiv.org
Tärkeimmät oivallukset
by Hyunwook Lee... klo arxiv.org 03-14-2024
https://arxiv.org/pdf/2210.15050.pdfSyvällisempiä Kysymyksiä