Abstract: Due to the complexity and uncertainty of geotechnical engineering，it is difficult to obtain the geotechnical parameters accurately. This paper presents a method of back analysis of geotechnical parameters displacement of foundation pit，which combines the advantages of improved adaptive genetic algorithm（IAGA）and multi-output support vector ma chine（M-SVR）. This method makes full use of the advantages of genetic algorithm in global optimization and small sample data modeling of support vector machine，and overcomes the disadvantages of traditional genetic algorithm，such as easily falling into local extremum，low efficiency and instability in the search of complex function optimization，and large calcula? tion amount and low precision in building multi-point model by using single output support vector machine. By applying this method to the back analysis of the geotechnical parameters of the foundation pit in the pile supporting system of Yingkou Xin glong Building，the average relative error between the calculated displacement value with the equivalent geotechnical param eter value and the actual displacement is only 2.83%，which verifies its applicability and accuracy. Finally，through the com? parison of the shear strength parameters obtained from the back analysis with the results of laboratory test，andof the elastic modulus withthe empirical value，the recommended initial parameter value of the three-dimensional numerical simulation for this type of foundation pit is given. The average relative error between the displacement value calculated by the recommended parameter and the actual observation value is 4.07%，which satisfies the application of practical engineering.

Key words: Soft soil foundation pit, Multi-output support vector regression, Improved adaptive genetic algorithm, Shear strength index, Back analysis of displacements