LSTM-ENHANCED TIME SERIES FORECASTING FOR REAL-TIME DECISION-MAKING

LSTM (Long Short Term Memory) models have revolutionized time series forecasting to provide accurate data for real-time decision-making in many fields. Moreover, Because LSTM models can deal with temporal dependency and sequence data, many applications have been seen in supply chain, finance, and energy demand. Unlike more conventional frameworks, these models are well suited for learning and predicting patterns that may not be linear and occur within volatile contexts. This paper elaborates on LSTM models, how they can be incorporated into a real-time system, and the prospects facing such a system to show their importance in meeting real-time forecasting requirements.