DocumentCode
436607
Title
Study and its application of spatio-temporal forecast algorithm
Author
Xu, Wei ; Huang, Houkuan ; Qin, Yong
Author_Institution
Sch. of Comput. & Inf. Technol., Beijing Jiao Tong Univ., China
Volume
2
fYear
2004
fDate
31 Aug.-4 Sept. 2004
Firstpage
1638
Abstract
Spatio-temporal 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 an 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.
Keywords
data mining; forecasting theory; railway engineering; sensor fusion; temporal databases; visual databases; data fusing; method fusing; railway passenger flow forecast; spatio-temporal data mining; spatio-temporal forecast method; Artificial neural networks; History; Neural networks; Neurons; Polynomials; Signal analysis; Time series analysis; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN
0-7803-8406-7
Type
conf
DOI
10.1109/ICOSP.2004.1441646
Filename
1441646
Link To Document