Improving the accuracy of ship emission inventories based on LSTM-CNN model
Author:
Publisher
SPIE
Reference10 articles.
1. Modelling Ships Main and Auxiliary Engine Powers with Regression-Based Machine Learning Algorithms
2. Particulate Matter (PM1, 2.5, 10) Concentration Prediction in Ship Exhaust Gas Plume through an Artificial Neural Network
3. Deep Learning-Based Ship Speed Prediction for Intelligent Maritime Traffic Management
4. Data-Based Engine Torque and NOx Raw Emission Prediction
5. Incorporation of Shipping Activity Data in Recurrent Neural Networks and Long Short-Term Memory Models to Improve Air Quality Predictions around Busan Port
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