The histories of differential pressure fluctuations and their Fast Fourier Transform spectrum have close relation with the flow regimes.Unfortunately,each type of flow regime is very difficult or impossible to be distinguished from the other on the basis of the fluctuations or the spectrum.The present paper provides a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on the basis of the combination of the Counter Propagation Network (CPN) and the FFT spectrum of the differential pressure fluctuations. The CPN takes advantages of simpler algorithm and fast training processes.Furthermore,it does not require a great deal of samples.The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN.With the presented test cases,the possibility can be higher than 90 percent for different liquid phase velocity. The histories of differential pressure fluctuations and their Fast Fourier Transform spectrum have close relation with the flow regimes. Unfortunately, each type of flow regime is very difficult or impossible to be distinguished from the other on the basis of the fluctuations or the spectrum. Present paper provides a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on the basis of the combination of the Counter Propagation Network (CPN) and the FFT spectrum of the differential pressure fluctuations. The CPN takes advantage of simpler algorithm and fast training processes.Furthermore, it does not require a great deal of samples. The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN.With the presented test cases, the possibility can be higher than 90 percent for different liquid phase velocity.