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

机译:少数民族地区旅游景观峰期收入估算模型的仿真分析

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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.
机译:在少数民族地区旅游景区的高峰期收入估算过程中,传统估计方法获得的估计结果受到旅游金额的可变性,现有的本地最佳问题,导致更大的错误。因此,本文提出了一种建立模型的方法来估算基于最大Lyapunov指数频谱的少数民族地区旅游景观的高峰期收入,这是第一次适用于区域旅游收入估计领域。通过使用相位空间重建方法重建经济增长指数时间序列,以及传统的Lyapunove指数频谱算法得到了改进。通过设置预估计器来缩短计算周期,以减少计算量,同时该方法具有计算每个Lyapunov指数的能力。以狼的基础为基础,采用所要求的最大Lyapunov指数,进行准确的结构估计模型。仿真结果表明,改进模型具有较高的估计精度与少数民族地区旅游景点的高峰期收入估计相比,可以迅速准确地估算少数民族地区旅游景区的高峰期收入,具有重要应用价值。

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