Predictive modeling of industrial structure

被引：0

作者：

Wang, HW ^{[1
]}

Huang, W ^{[1
]}

Liu, Q ^{[1
]}

机构：

[1] Beihang Univ, Sch Econ & Management, Beijing 100083, Peoples R China

来源：

ICIM' 2004: PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT | 2004年

关键词：

compositional data; predictive modeling; industrial structure;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to study the dynamic characteristic of industrial structure, pie chart is implemented to describe the development process of each component of industry. The data set involved in a pie chart is also called as compositional data. To analysis the dynamic features of each component in a pie chart, a non-linear approach for dimensionality deduction and a predictive model are proposed for the compositional data indexed by time. Based on the modeling approach, the development trend of the Beijing's industrial structure has been studied. Finally a numerical prediction from 2000 to 2005 of the components in three industries is presented to demonstrate the. structural change trend in Beijing.

引用

页码：656 / 661

页数：6