Dam deformation monitoring model based on neural network with ant colony optimization algorithm

摘要

Back propagation algorithm (BP) is widely used as a multilayer feedforward neural network model in the analysis of water engineering projects monitoring data, but it has low solution accuracy, slow search speed and easy to get into a local minimum. To overcome these shortcomings, in this paper, a new learning method of neural network with ant colony optimization (ACO) is introduced to achieve optimization solution of the model weights, the ACO-BP monitoring model of dam deformation is established as well. And actual examples show that the ant colony algorithm is effective and rapid.