Due to the complex conditions of RCC gravity dam construction sites, the parameters obtained by experiments are not necessarily consistent with the actual parameters. Therefore, in order to obtain high accuracy simulation results of temperature field, the adiabatic temperature rise Q0, temperature rise constant n and thermal conductivity λ of RCC gravity dam were inverted by the genetic algorithm based on the field measured temperature data. Then, the inversed parameters were used for temperature field simulation and analysis, and the reliability and accuracy of the inversed parameters under different number of measurement points were compared. The findings indicate that the genetic algorithm can effectively enhance the speed and accuracy of the inversion. Moreover, the inversion results are more closely aligned with the measured data when a greater number of measuring points is utilized, the inversion error of nine measuring points is reduced by 1.43% compared with three measuring points, and 0.44% compared with six measuring points. Therefore, when using the genetic algorithm for parameter inversion, more measurement points should be selected to improve the accuracy of simulation calculation. The research results can provide a theoretical guidance and basis for thermal parameter inversion of RCC gravity dams.