DocumentCode
2163369
Title
Notice of Retraction
On the Model for the Complex Non-Linear System and Its Application to Predicting the Output of Northwest Construction Industry of China
Author
Bian-ping Su ; Kun Gao ; Yi-ping Wang
Author_Institution
Sch. of Sci., Xi´an Univ. of Archit. & Technol., Xi´an, China
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As construction Industry is part of the complex non-linear system of the national economic development, the BP neural network of the artificial intelligence can to some extent deal with problems of the complex nonlinear system. Therefore, it has been widely applied to solving macroeconomic problems at present. The paper through systematically integrating econometrics with BP neural network establishes a complex nonlinear system predictive model for economic problems which is based on causality theories to determine the input variable of BP neural network, on the momentum BP algorithm of alterable learn rate and coitegration theories to analyze the reliability of BP neural network system. Therefore, the paper reinforces the theoretical basis, improves the quality of the network model and applies the predictive model to predicting and controlling the output of northwest construction industry of China, which has obtained satisfactory results.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As construction Industry is part of the complex non-linear system of the national economic development, the BP neural network of the artificial intelligence can to some extent deal with problems of the complex nonlinear system. Therefore, it has been widely applied to solving macroeconomic problems at present. The paper through systematically integrating econometrics with BP neural network establishes a complex nonlinear system predictive model for economic problems which is based on causality theories to determine the input variable of BP neural network, on the momentum BP algorithm of alterable learn rate and coitegration theories to analyze the reliability of BP neural network system. Therefore, the paper reinforces the theoretical basis, improves the quality of the network model and applies the predictive model to predicting and controlling the output of northwest construction industry of China, which has obtained satisfactory results.
Keywords
artificial intelligence; backpropagation; causality; construction industry; econometrics; large-scale systems; macroeconomics; neural nets; nonlinear systems; reliability theory; BP algorithm; BP neural network; alterable learn rate; artificial intelligence; causality theory; coitegration theory; complex nonlinear system predictive model; econometrics; macroeconomic problems; national economic development; northwest construction industry; reliability; Artificial neural networks; Biological system modeling; Construction industry; Input variables; Mathematical model; Predictive models; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science (MASS), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5325-2
Type
conf
DOI
10.1109/ICMSS.2010.5576796
Filename
5576796
Link To Document