Simulation analysis of peak period income estimation model in tourism scenic of minority Areas

Abstract

in the process of peak period income estimation in the tourism scenic of minority areas, the estimation results obtained by traditional estimation methods are affected by the mutability of tourist amount, existing local optimal problem, causing bigger error. Therefore, this paper proposes a method of establishing model to estimate the peak period income in tourism scenic of minority areas based on the largest Lyapunov exponent spectrum, and for the first time, this program is applied to the regional tourism revenue estimation field. By using phase space reconstruction method reconstruct the economic growth index time series, and the traditional Lyapunove exponent spectrum algorithm is improved. Computing period is shorten by setting the pre-estimator, to reduce the amount of calculation, and at the same time the method has the ability of calculating each Lyapunov exponent. Taking the requested maximum Lyapunov exponent as the basis of Wolf one step estimation method make accurate structural estimation model. The simulation results show, the improved model has the higher estimation accuracy compared with other models for peak period income estimation in tourist attractions of minority areas, can rapidly and accurately estimate the peak period income in tourist scenic areas of minority areas, which has important application value.