Sunghyun Sim

Hybrid Temporal Autoencoder and Similarity Matching for Low Aggregation Level Long Time Series Forecasting

Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data spar...