The differences of space distributions and time profiles between the γ-ray and proton induced showers in YBJ-ARGO experiment are studied using Monte Carlo simulation data.An artificial neural algorithm is used to identify the primary γ-ray and proton induced showers.It is shown that the separation of γ-rays and protons can be achieved with a good efficiency in the energy range of 0.1~10 TeV.

A Monte Carlo simulation for the hybrid experiment of air shower array and emulsion chambers at Yangbajing is done with different interaction models.The feasibility of distinguishing primary cosmic ray components by use of the method of artificial neural netwo rks is studied with the simulation data.T he analysis indicates that the showers induced by primary protons can be efficiently selected by using this method, but the results obtained appear to be dependent on interaction model.The corresponding systematic error is also estimated.