基于卡尔曼滤波的旅游经济发展趋势预测算法研究
Research on Tourism Economic Development Trend Prediction Algorithm Based on Kalman Filter
袁学勇1
作者信息
- 1. 安徽六安职业技术学院,安徽 六安 237158
- 折叠
摘要
旅游经济是经济体中十分重要的一部分,对其发展趋势进行预测,对旅游市场的决策制定以及市场开发等都有着很大的影响.基于此,提出基于卡尔曼滤波的旅游经济发展趋势预测算法.通过在权威渠道选取旅游经济数据,引入卡尔曼滤波原理,在算法框架中定义卡尔曼滤波的矩阵,并利用新息方程求解该算法.实证预测结果显示:在未来几年内,旅游经济在 2027 年之前将呈现出较高增长率的发展趋势,2027 年至2034 年旅游经济增长率发展趋势放缓,于2035 年呈现负增长发展趋势后,再次呈现正向增长的发展趋势,这表明旅游经济整体上将呈现正向增长的发展趋势.
Abstract
As a crucial part of the economy,predicting the development trend of the tourism economy has a significant im-pact on decision-making and market development in the tourism market.Based on this,a tourism economic development trend prediction algorithm based on Kalman filtering is proposed.By selecting tourism economic data from authoritative channels,introducing the principle of Kalman filtering,defining the matrix of Kalman filtering in the algorithm framework,and using the innovation equation to solve the algorithm.The empirical prediction results show that in the coming years,the tourism economy will show a high growth rate development trend before 2027.The development trend of the tourism econo-my growth rate will slow down from 2027 to 2034,and after showing a negative growth trend in 2035,it will once again show a positive growth trend,indicating that the overall tourism economy will show a positive growth trend.
关键词
旅游经济/经济发展/预测算法/卡尔曼滤波/发展趋势预测Key words
Tourism economy/Economic development/Prediction algorithm/Kalman filtering/Development trend pre-diction引用本文复制引用
出版年
2024
NETL
NSTL
万方数据