Study and its application of spatio-temporal forecast algorithm

被引：0
|
作者：
Xu, W [1 ]
Huang, HK [1 ]
Qin, Y [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
来源：
2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3 | 2004年
关键词：
spatio-temporal forecast; spatio-temporal data mining; integration;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Spatio-temproal data mining is one of important topics in data mining research, in which spatio-temporal forecast is the most widely used. By analyzing the limitation of current spatio-temporal forecast methods, this paper presents all integrated algorithm based on data fusing, and method fusing, and applies the method successfully to railway passenger flow forecast. Experimental results show the algorithm is effective.
引用
收藏
页码：1638 / 1641
页数：4
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