@INPROCEEDINGS { Rsds4662,
author = {Chan, Chien-Chung and Yen, Leon and Tzeng, Gwo-Hshiung and Shieh, How-Ming and Yang, Yu-Ping Ou}, 
title = {Business Aviation Decision-Making Using Rough Sets}, 
booktitle = {Proceedings of the Sixth International Conference on Rough Sets and Current Trends in Computing (RSCTC'2008)}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 5306, 
pages = {329--338}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {November}, 
year = 2008, 
abstract = {Business aviation has been popular in the United States, Europe, and South America, however, top economies in East Asia, including Japan, Korea, and Taiwan, have been more conservative and lag behind in the development of business aviation. In this paper, we hope to discover possible trends and needs of business aviation for supporting the government to make decision in anticipation of eventual deregulation in the near future. We adopt knowledge-discovery tools based on rough set to analyze the potential for business aviation through an empirical study. Although our empirical study uses data from Taiwan, we are optimistic that our proposed method can be similarly applied in other countries to help governments there make decisions about a deregulated market.}, 
keywords = {rough set theory, information system, decision rule, business aviation, data mining, decision making, }, 
}