A characteristic prediction method was proposed and variable specific heat calculation was applied to the performance analysis and programming of compressor based on object-oriented theory.Also

a method named particle swarm optimization(PSO) based on back propagation (BP) neural network was presented by combining the global optimization ability of the PSO with the local optimization ability of the BP neural network

and the prediction error and fitting error were analyzed.The fitting error is mostly within 0.5% while the highest prediction error is within 0.8%;and both the fitting accuracy and prediction accuracy could meet the requirements.Variable specific heat calculation method was applied to the compressor performance calculation

and object-oriented method was used to build the compressor performance computing program.Compared with several working condition points of the compressor

the output parameter errors are less than 1.12%.Therefore

the characteristic prediction method and performance mathematical model are suitable for compressor performance calculation

and the compressor calculation procedure is also suitable for gas turbine performance calculation.