基于改进的灰色模型的旅游需求预测研究  

Study on Tourism Demand Forecasting Based on Improved Grey Model

作　　者：李瑶 曹菡[1] 马晶 

机构地区：[1]陕西师范大学计算机科学学院,西安710119 [2]陕西师范大学旅游与环境学院,西安710119

出　　处：《计算机科学》2018年第1期122-127,共6页Computer Science

基　　金：国家自然科学基金面上项目(41271387);国家国际科技合作专项项目(2012DFA11270)资助

摘　　要：针对海南省旅游需求预测问题,对传统的灰马尔科夫模型进行改进,提出了一种动态优化子集模糊灰马尔科夫预测模型。该模型首先根据GM(1,1)模型预测结果的平均绝对误差百分比,通过输入子集法来确定最优输入子集个数;然后利用模糊集理论,将计算出的隶属度向量作为马尔科夫转移矩阵向量的权重,以修正预测值。为了能够根据时间推移进行预测,建立了等维递补的动态预测模型。实验以海南省各市县旅游饭店接待情况为例,验证了该模型可以有效地提高预测数据的准确性。Aiming at the tourism demand forecasting problems in Hainan Province,this paper proposed a novel dynamic optimal input subset fuzzy grey-Markov prediction model based on traditional grey-Markov model.This model firstly determines the optimal number of input subsets through input subset method according to the mean absolute percentage error of the prediction of GM(1,1)model,then calculates the membership vector and takes it as weight vector of Markov transfer matrix vector so that the forecast value can be revised through fuzzy set theory.An equal dimension increasing dynamic grey prediction model was created based on the characteristic of the passage of time,which enables us to predict the tourism demand.The number of tourists received by hotels in Hainan Province is taken as an example to show that the model can effectively improve the accuracy of forecasting data.

关 键 词：预测 灰色模型 模糊集 海南省 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]