Genetic entropy spectral estimation method and its application to annual runoff periodic identification

An improved entropy spectral estimation method,Genetic Entropy Spectral estimation(GES),is proposed to identify the implicit periods in annual runof time series.The method is based on the accelerating genetic algorithm(AGA),which is mainly used to optimize the parameters of maximum entropy spectral analysis method(MESA),and minimize the four equivalent conditions of MESA.Compared to the traditional variation spectral method and Burg spectral method,the entropy estimation results based on the improved method is not depend on the selection of initial value,further more,the method has high adaptability for data length,signal noise ratio and initial phases.Taking Houdacheng station in the Sanchuanhe River basin as a case,an annual runof series from 1956 to 2000 is studied with the method.And results show that there are two prominent periods of 12.29 years and 2.67 years in the time series with 95% confidence level.GES method can provide a new approach for variation law and phases analysis study of runof series.