| 基于Kohonen网络的城市居民国内旅游需求分类研究 |
| |
| 引用本文： | 徐晓娜,翁钢民.基于Kohonen网络的城市居民国内旅游需求分类研究[J].软科学,2007,21(1):14-16,21. |
| |
| 作者姓名： | 徐晓娜 翁钢民 |
| |
| 作者单位： | 1. 燕山大学,经济管理学院,河北,秦皇岛,066004
2. 燕山大学,经济管理学院,河北,秦皇岛,066004;天津大学,管理学院,天津,300072 |
| |
| 摘 要： | 基于人工神经网络(ANN)中自组织特征映射神经网络(Kohonen)的聚类功能,提取7个反映旅游需求发展情况的特征指标,对我国城市居民的旅游需求进行分类,将39个城市分为6类。对分类结果进行了分析,对方法进行了讨论,指出Kohonen网络可以避免传统聚类方法难以克服的一些缺点,是一种具有强大的自学习功能、良好的自组织性和自适应性、能迅速客观地得到聚类结果的聚类方法。
|
| 关 键 词： | Kohonen网络 国内旅游需求分类 城市居民 |
| 文章编号： | 1001-8409（2007）01-0014-03 |
| 修稿时间： | 2006-08-14 |
Research on Classification of Domestic Tourism Demand among Urban Residents Based on Kohonen Network |
| |
| XU Xiao-na,WENG Gang-min.Research on Classification of Domestic Tourism Demand among Urban Residents Based on Kohonen Network[J].Soft Science,2007,21(1):14-16,21. |
| |
| Authors: | XU Xiao-na WENG Gang-min |
| |
| Institution: | 1. School of Economics and Management, Yanshan University, Qinhuangdao 066004 ; 2. School of Management, Tianfing University, Tianjing 300072 |
| |
| Abstract: | Based on the clustering function of self organizing feature map in ANN,the authors choose seven factors which reflect the characteristics of tourism demand to classify the tourism demand of urban residents.Thirty-nine cities are classified into six classes.Though analyzing the classification and discussing the method,this paper points out that the Kohenen Network can overcome some shortcomings in the traditional clustering methods,and the strong self-learning function,excellent self-organizing feature and self-adapting of Kohenen Network can work effectively on cluster result. |
| |
| Keywords: | Kohonen network classification of domestic tourism demand urban residents |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
