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
fDate :
31 Aug.-4 Sept. 2004
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;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1441646
