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According to the randomness of thermal parameters of laboratory test and the defects of traditional back analysis method which is easy to fall into premature and has low efficiency and great computational complexity, the back analysis method based on parallel particle swarm optimization is developed. The back analysis steps of thermal parameters of mass concrete structure is demonstrated detailedly. When three-dimensional finite element relocating mesh method and improved BP neural network method are used to inverse thermal parameters based on the measured temperature, the parameters which reflect the true performance can be obtained. The results show that this method has a better stability and convergency and is feasible to inverse thermal parameters.