Damage Detection of Self-Anchored Suspension Bridge Based on Neural Network Model and Genetic-Simulated Annealing Algorithm
According to the characteristics of self-anchored suspension bridge, a new method to detect damage is introduced in this paper.It works in two stages.First, a BP neural network model is built to predict damaged position. Next, based on the characteristics of genetic algorithm and simulated annealing algorithm, a new approach, genetic-simulated annealing algorithm, is put forward to identify damage extent of detected positions. Compared with the traditional genetic algorithm, the global convergence effect of this algorithm is enhanced by using of the Metropolis acceptance rule of the simulated annealing algorithm in the searching process.
Chaohe Chen, Yong Huang and Guangfan Li
Q. C. Zhang and Q. S. Sun, "Damage Detection of Self-Anchored Suspension Bridge Based on Neural Network Model and Genetic-Simulated Annealing Algorithm", Advanced Materials Research, Vols. 243-249, pp. 1963-1967, 2011