Long Term Forecasting

Long-term forecasting aims to accurately predict future values of time series data far beyond the immediate past, a challenging task due to increasing uncertainty and complex temporal dependencies. Current research focuses on developing novel architectures, such as Transformers and MLP-based models, often incorporating techniques like attention mechanisms, frequency analysis, and data augmentation to improve accuracy and efficiency. These advancements have significant implications across diverse fields, from resource management (e.g., energy, water) and financial markets to environmental monitoring (e.g., weather, wildfire prediction) and public health (e.g., disease outbreaks). The development of robust and efficient long-term forecasting methods is crucial for informed decision-making and effective planning in these areas.