Title :
Time Series Prediction as a Problem of Missing Values: Application to ESTSP2007 and NN3 Competition Benchmarks
Author :
Sorjamaa, Antti ; Lendasse, Amaury
Author_Institution :
Helsinki Univ. of Technol., Helsinki
Abstract :
In this paper, time series prediction is considered as a problem of missing values. A method for the determination of the missing time series values is presented. The method is based on two projection methods: a nonlinear one (Self-Organized Maps) and a linear one (Empirical Orthogonal Functions). The presented global methodology combines the advantages of both methods to get accurate candidates for the prediction values. The methods are applied to two time series competition datasets.
Keywords :
mathematics computing; self-organising feature maps; time series; empirical orthogonal functions; missing time series values; missing values problem; self-organized maps; time series prediction; Databases; Informatics; Interpolation; Lattices; Neural networks; Predictive models; Self organizing feature maps; Stochastic processes; Topology; Unsupervised learning;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371429
