Forecasting Model

Time series forecasting models aim to predict future values based on historical data, a crucial task across diverse fields from finance and energy to healthcare and environmental science. Current research emphasizes improving accuracy and robustness through advanced architectures like transformers, recurrent neural networks (RNNs, including LSTMs), and hybrid models combining machine learning with statistical methods, often incorporating external data sources like news or market indicators to enhance predictive power. These advancements are significant because accurate forecasting enables better resource allocation, risk management, and informed decision-making in various sectors, ultimately leading to improved efficiency and outcomes.