Forecasting of CO and O₃concentrations using optimized deep learning: A case study for Kuala Lumpur, Malaysia

Engineering

• Deep Learning Method 100%
• Long Short-Term Memory Network 100%
• Long Short-Term Memory 100%
• Air Quality 57%
• Carbon Monoxide 42%
• Mean Absolute Error 14%
• Air Pollution 14%
• Atmospheric Aerosol 14%
• Root Mean Square Error 14%
• Perceptron 14%
• Optimization Technique 14%
• Data Series 14%
• Quality Data 14%
• Target Site 14%
• Recurrent 14%

Earth and Planetary Sciences

• Long Short-Term Memory Network 100%
• Malaysia 100%
• Air Quality 42%
• Carbon Monoxide 42%
• Emissions 14%
• Root-Mean-Square Error 14%
• Air Pollution 14%
• Air Pollutant 14%
• Sulphur Dioxide 14%
• Atmospheric Aerosol 14%
• Time Series 14%
• Nitrogen Dioxide 14%
• Self Organizing Systems 14%
• Pollutant Concentration 14%
• Environmental Health 14%
• Gated Recurrent Unit 14%

Chemical Engineering

• Deep Learning Method 100%
• Long Short-Term Memory 100%
• Long Short-Term Memory Network 100%
• Multilayer Neural Networks 14%
• Atmospheric Aerosol 14%