کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1713129 | 1013215 | 2007 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Chaotic time series multi-step direct prediction with partial least squares regression
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares (PLS) is proposed in this article, where PLS, the method for predicting a set of dependent variables forming a large set of predictors, is used to model the dynamic evolution between the space points and the corresponding future points. The model can eliminate error accumulation with the common single-step local model algorithm, and refrain from the high multi-collinearity problem in the reconstructed state space with the increase of embedding dimension. Simulation predictions are done on the Mackey-Glass chaotic time series with the model. The satisfying prediction accuracy is obtained and the model efficiency verified. In the experiments, the number of extracted components in PLS is set with cross-validation procedure.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 3, 2007, Pages 611-615
Journal: Journal of Systems Engineering and Electronics - Volume 18, Issue 3, 2007, Pages 611-615
نویسندگان
Liu Zunxiong, Liu Jianhui,