A novel few-shot meta-learning strategy for fault diagnosis of wastewater treatment process

Key Points

• Fault diagnosis improved significantly using few-shot learning techniques, reducing time and errors.
• Key evidence showcases a 30% increase in accuracy compared to traditional methods.
• Analysis employs a meta-learning approach to adaptively learn from fewer labeled examples and enhance overall diagnostic capabilities.
• This method supports faster decision-making, but further testing in diverse treatment facilities is needed.