Abstract：An intelligent algorithm by which multiple rheological parameters of rock can be analyzed simultaneously is proposed. This method，namely the pattern-genetic-neural network algorithm (PGNNA)， naturally combines pattern search (PS)，genetic algorithm (GA)，and neural network (NN). The samples produced by uniform design are used to train NN whose architecture is determined in global optimization by pattern-genetic algorithm(PGA). NN that has optimal architecture and has been trained by optimal prediction algorithm is used to describe relationship between the rock rheological parameters and displacement. Rheological parameters are searched in global space by PGNNA，instead of a certain numerical calculation. This method improves the precision of back analysis on parameters，shorts the time of calculation，which is almost impossible for some traditional methods because of the long time of calculation. The practical engineering example shows feasibility and advantages of this method.
