Real-time monitoring and prediction model for dams based on particle swarm optimization neural network

Particle Swarm Optimization（PSO）is introduced in the field of dam monitoring, and then a new dam monitoring model based on PSO Neural Network（PSONN）is put forward. The model makes full use of the global optimization of PSO and local accurate searching of BP Neural Network（BPNN）to provide better initial weights for BPNN. Seriatim PSONN（SPSONN）model, Whole PSONN（WPSONN）model, Seriatim BPNN（SBPNN）model and Whole BPNN（WBPNN）model are compared here, the results show that the seriatim prediction models are superior to those whole models with higher forecast precision. Furthermore, the PSONN models exhibit faster convergence rate, less iterative number and better forecast precision than the BPNN ones. Especially, the SPSONN model is more efficient to satisfy the demand of real-time prediction of dam monitoring.