کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410023 679114 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction for noisy nonlinear time series by echo state network based on dual estimation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Prediction for noisy nonlinear time series by echo state network based on dual estimation
چکیده انگلیسی

When using echo state networks (ESNs) to establish a regression model for noisy nonlinear time series, only the output uncertainty was usually concerned in some literature. However, the unconsidered internal states uncertainty is actually important as well. In this study, an improved ESN model with noise addition is proposed, in which the additive noises describe the internal state uncertainty and the output uncertainty. In terms of the parameters determination of this prediction model, a nonlinear/linear dual estimation consisting of a nonlinear Kalman filter and a linear one is proposed to perform the supervised learning. For verifying the effectiveness of the proposed method, the noisy Mackey Glass time series and the generation flow of blast furnace gas (BFG) in steel industry practice are both employed. The experimental results demonstrate that the proposed method is effective and robust for noisy nonlinear time series prediction.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 82, 1 April 2012, Pages 186–195
نویسندگان
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