2024
DOI: 10.31358/techne.v23i1.456
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Advancing Natural Gas Price Predictions with ConcaveLSTM

Mohammad Diqi,
Putra Wanda,
Hamzah
et al.

Abstract: This study investigates the application of the ConcaveLSTM model, a novel machine learning approach combining the strengths of Stacked Long Short-Term Memory (LSTM) and Bidirectional LSTM, for predicting natural gas prices. Given the inherent volatility and complexity of energy markets, accurate forecasting models are crucial for effective decision-making. The research employs a comprehensive dataset from 1997 to 2020, focusing on the daily price of natural gas in US Dollars per Million British thermal units (… Show more

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