Research on Fuel Consumption Prediction for Open-Pit Mine Trucks Using GA-LSTM
Real-time data collection via vehicle-mounted sensors captures multi-dimensional parameters such as fuel consumption, speed, route, and driving behavior of mining trucks. A genetic algorithm-optimized LSTM model is then employed to construct a fuel consumption prediction model, enabling precise fuel consumption forecasting. This approach reduces fuel consumption by 12-18%, effectively minimizing fuel theft, leakage, and energy waste while promoting green energy conservation and sustainable mining practices aligned with China's sustainable development objectives.
Authors
- Xinming Liu
- Jian Yong Bian
Institutions
- Liaoning Technical University (CN)
Publication Details
- Published
- 2025-05-16
- DOI
- https://doi.org/10.1145/3757110.3757188
- Primary Topic
- Vehicle License Plate Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00