Oil is a crucial strategic resource and a guarantee for the steady operation of a nation. Lack of oil supply has a significant impact on both national security and social, economic, and social development. Given that the PRD region is one of China's most significant economic zones, we took nine indicators from both supply and demand (pipeline transportation of refined oil products, oil and by-product production, electricity consumption, car and motor vessel ownership, population, GDP, output value of primary, secondary, and tertiary industries), and obtained the oil consumption of the PRD for a lengthy period of 15 years. We have also designed and implemented an oil consumption forecasting model based on a long and short-term memory network algorithm, with a loss rate of 0.1, which verifies the validity of the model. The suggested model is a useful tool for predicting regional oil consumption and can serve as a foundation for study of future oil supply and demand in the PRD region.
[1]
Chi Qin Lai,et al.
LSTM network as a screening tool to detect moderate traumatic brain injury from resting-state electroencephalogram
,
2022,
Expert Syst. Appl..
[2]
Niaz Muhammad Shahani,et al.
Predictive modeling of drilling rate index using machine learning approaches: LSTM, simple RNN, and RFA
,
2022,
Petroleum Science and Technology.
[3]
S. Hochreiter,et al.
Long Short-Term Memory
,
1997,
Neural Computation.
[4]
Jiahao Yan,et al.
LSTM enhanced by dual-attention-based encoder-decoder for daily peak load forecasting
,
2022,
Electric Power Systems Research.
[5]
W. Bo.
Study on Index System Designing of Chinese Petroleum Economic Security
,
2010
.
[6]
Yang Xin.
Analysis of Future Trend Prediction of China's Petroleum Consumption
,
2009
.