Open AccessThe neighbor point selection method for local prediction based on information criterion
Author(s) -
Meng Qing-Fang,
Yungui Peng,
Qu Huai-Jing,
Min Han
Publication year - 2008
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.57.1423
Subject(s) - computer science , computation , k nearest neighbors algorithm , chaotic , selection (genetic algorithm) , point (geometry) , algorithm , series (stratigraphy) , data mining , artificial intelligence , mathematics , paleontology , geometry , biology
The number of nearest neighbor points is an important parameter for the local prediction method, which has an important impact on the prediction accuracy and computation complexity of the local model. Based on the information criterion, the neighbor point selection method for the local prediction method is proposed in this paper. We illustrate this method by analyzing chaotic time series from Lorenz model and the experimental laser data- Santa Fe Data A. Simulation results show that using the proposed method to select neighbor points, the one-step and multi-step prediction accuracy of the local prediction method is good, and the computation complexity is reduced.