Tensioning-Phase Box Girder Deformation Prediction Model Based on Ant Colony Algorithm and Residual Correction

• Main Authors: Gangnian Xu, Youzhi Wang, Shangbin Liu, Shimin Wang
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2018/1872578

The girder of prestressed concrete continuous box girder bridge strengthened by a stay cable system has a very complex deformation mechanism, and it is difficult to establish accurate numerical model for prediction. For these problems, a prediction method based on the combination of ant colony algorithm and residual combination correction model is proposed. In this method, the measuring points are considered as the cities in TSP ant colony algorithm, the information function model and heuristic function model are constructed, the pheromone update mechanism and ant search mechanism are established, and the deformation prediction of the main girder based on ant colony algorithm prediction model is achieved. On this basis, in order to fit the random change process of main girder deflection better, the periodic function generated by harmonic transform and sine function are introduced to modify the predicted results, which makes up for the low precision defect of single model. The results show that compared with finite element method, unequal interval gray model (1,1) (UIGM (1,1)), one-time residual correction UIGM (1,1), Markov chain residual correction UIGM (1,1), and ant colony algorithm model, this model can reflect the space-time effect and casual fluctuation feature of the development of girder deformation better and also has higher prediction accuracy and efficiency. The mean relative error of the predictive value is 3.39%, the posterior error ratio is 0.060, and the accuracy level reaches level 1. This model provides a new way for the girder deformation prediction of bridge strengthened by the stay cable system.