基于ACO_SVM的扬州市旅游业年总收入预测
Prediction of Annual Tourism Revenue of Yangzhou City Based on ACO_SVM
苏丹 1杨奥莉2
作者信息
- 1. 扬州工业职业技术学院 基础科学部,江苏 扬州 225000
- 2. 浙江师范大学 数学与计算机科学学院,浙江 金华 321000
- 折叠
摘要
以扬州市2002-2021 年旅游业年总收入及相关指标的实际数据为例,引入ACO优化算法对SVM模型的关键性参数进行寻优处理,建立基于ACO_SVM的旅游业年总收入预测模型,并结合MATLAB进行模型实验,最终精度达到93.8%.进行ACO_SVM模型与SVM模型两组预测结果对比,验证了基于ACO_SVM的预测模型的有效性,对提高扬州市旅游业与旅行社的服务质量更具参考价值.
Abstract
The study takes the actual data of the tourism annual revenue and related indicators of Yangzhou City from 2002 to 2021 as an example,introduces ACO optimization algorithm to optimize the key parameters of the SVM model,constructs the tourism annual revenue prediction model based on ACO_SVM,and realizes the model experiment in combination with MATLAB.The final accuracy reaches 93.8%.The study compares ACO_SVM model and SVM model,and verifies the validity of the ACO_SVM model,which is of more reference value for the improvement of the service quality of tourism and travel agencies in Yangzhou City.
关键词
旅游业年总收入预测/支持向量机/蚁群算法/参数优化/扬州市Key words
Prediction of total annual tourism revenue/Support vector machine/Ant colony algorithm/Parameter optimization/Yangzhou City引用本文复制引用
出版年
2024
NETL
NSTL
万方数据