Intelligent progress prediction for power grid engineering projects based on unstructured text data and deep learning

Key Points

• The research aims to develop an intelligent system for predicting progress in power grid engineering projects using deep learning techniques applied to unstructured text data.
• Utilized deep learning algorithms on unstructured text data
• Analyzed performance metrics to assess prediction accuracy
• Conducted case studies within power grid engineering contexts
• Achieved significant improvements in prediction accuracy compared to traditional methods
• Demonstrated the effectiveness of unstructured text data in enhancing project management
• Provided insights into engineering project timelines and resource allocation