Multi Horizon

Multi-horizon time series forecasting aims to predict multiple future time points simultaneously, improving upon single-step predictions by capturing temporal dependencies and reducing error accumulation. Current research focuses on developing advanced neural network architectures, including variations of transformers, graph neural networks, and recurrent neural networks, often incorporating attention mechanisms and memory components to enhance accuracy and efficiency across diverse datasets. These advancements are significantly impacting various fields, from healthcare (e.g., vital sign prediction) to energy management (e.g., line loss rate forecasting) and transportation (e.g., flight trajectory prediction), by enabling more accurate and timely decision-making.