A note on the Gamma test analysis of noisy input/output data and noisy time series

2007 ◽  
Vol 229 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Antonia J. Jones ◽  
D. Evans ◽  
S.E. Kemp
Keyword(s):  
Time Series ◽  
Gamma Test ◽  
Input Output ◽  
Output Data ◽  
Test Analysis ◽  
Noisy Input ◽  
Noisy Time Series

A Novel Modeling Method Based on Multi-Dimensional Taylor Network and its Application in Time Series Prediction

2014 ◽  
Vol 940 ◽  
pp. 480-484 ◽  
Author(s):  
Yi Lin ◽  
Hong Sen Yan ◽  
Bo Zhou
Keyword(s):  
Time Series ◽  
Prior Knowledge ◽  
Dynamic Characteristics ◽  
Prediction Accuracy ◽  
Time Series Prediction ◽  
Nonlinear Time Series ◽  
Modeling Method ◽  
Input Output ◽  
Output Data ◽  
Bridge Tower

A novel modeling method based on multi-dimensional Taylor network is proposed. The structure and the principle of the multi-dimensional Taylor network are introduced. Based on this, the method is applied in the nonlinear time series prediction based on multi-dimensional Taylor network. It provides a new method to predict the time series, which can describe the dynamic characteristics without prior knowledge and can realize the prediction of the nonlinear time series just with input-output data. An example of predicting the stress data of a large span bridge tower induced by strong typhoon is taken at last in this paper. Results indicate the validity and the better prediction accuracy of this method in nonlinear time series prediction.

A Novel Nonlinear Time Series Prediction Method and its Application in Structural Vibration Response Prediction

2014 ◽  
Vol 599-601 ◽  
pp. 1918-1921 ◽  
Author(s):  
Yi Lin ◽  
Hong Sen Yan ◽  
Bo Zhou
Keyword(s):  
Time Series ◽  
Prediction Accuracy ◽  
Time Series Prediction ◽  
Prediction Method ◽  
Response Prediction ◽  
Nonlinear Time Series ◽  
Vibration Response ◽  
Structural Vibration ◽  
Input Output ◽  
Output Data

A novel nonlinear time series prediction method is proposed in this paper. This prediction method is based on the Multi-dimensional Taylor Network. The structure of the Multi-dimensional Taylor Network is introduced firstly. The Multi-dimensional Taylor Network provides a new method to predict the nonlinear time series. The prediction model based on the Multi-dimensional Taylor Network can realize the prediction of the nonlinear time series just with input-output data without the system mechanism, and it can describe the dynamic characteristics of the system. Finally, the new prediction method is applied in the structural vibration response prediction. Results indicate the validity and the better prediction accuracy of this method.

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