Flood safety evaluation model for under-construction water conservancy projects based on BP neural network

To enhance the intelligence level of flood safety evaluation for water conservancy projects under construction, an intelligent evaluation model for flood safety status of water conservancy projects under construction based on Back Propagation (BP) neural network was constructed. This model considers a multidimensional indicator system and utilizes the learning ability of BP neural network for nonlinear problems. Through training with actual engineering case data, it predicts and analyzes the flood safety level of water conservancy projects under construction. The research results indicate that the maximum relative error of the model's prediction results is within 4%, demonstrating good generalization ability and effectively assisting water administrative authorities and engineering participating units in quickly conducting flood safety evaluations. This study can provide reference for the intelligent management of flood safety in water conservancy projects under construction.