Forecasting Algorithm

Forecasting algorithms aim to predict future values in time series data, a crucial task across diverse fields from finance to environmental science. Current research emphasizes improving accuracy and robustness, particularly for complex multivariate and hierarchical time series, employing techniques like deep learning (e.g., convolutional and recurrent neural networks), statistical methods (e.g., ARIMA), and hybrid approaches combining both. These advancements are driving improvements in real-world applications, such as resource allocation, space weather prediction, and even personal health management, by providing more accurate and reliable forecasts.