Research on Intelligent Grading Evaluation of Water Conservancy Project Safety Risks Based on Deep Learning

Abstract

With the rise of artificial intelligence and big data technologies, it is increasingly significant to apply these emerging technologies to scientific decision-making in water conservancy project construction management in the face of many problems in the process of water conservancy project construction. Different from using traditional assessment methods for risk classification of water conservancy construction hazards, this paper integrates a priori attention and constructs a transformer risk prediction model based on a sliding window, which deeply explores the data value of water conservancy construction hazards information, further predicts the risk level of water conservancy construction hazards and realizes efficient and intelligent management of water conservancy project construction hazard identification management.

Keywords

• deep learning
• hazard sources
• risk evaluation
• transformer model
• task scenarios
• a priori knowledge