DocumentCode
526580
Title
Notice of Retraction
Artificial neural networks applied in environmental quality assessment
Author
Liu Yijun ; Tang Jiali ; Jiang Hongfen ; Zhu Guangping ; Yu Zhimin
Author_Institution
Sch. of Comput. Eng., Jiangsu Teachers Univ. of Technol., Changzhou, China
Volume
3
fYear
2010
fDate
9-11 July 2010
Firstpage
546
Lastpage
549
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.
The problem of environmental quality assessment is a pattern recognition problem, and a well-trained ANN can exploit the underlying nonlinear relationships that determine the environmental rating of a region. In this study, we are trying with the neural network model to make an effective analysis for environmental quality assessment. A 4-9-1 three-layer feedforward neural network using the backpropagation and Levenberg-Marquardt algorithms has been used in the proposed artificial neural network. The case study shows that this neural network is efficient and forms a useful tool for the prediction of environmental quality.
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.
The problem of environmental quality assessment is a pattern recognition problem, and a well-trained ANN can exploit the underlying nonlinear relationships that determine the environmental rating of a region. In this study, we are trying with the neural network model to make an effective analysis for environmental quality assessment. A 4-9-1 three-layer feedforward neural network using the backpropagation and Levenberg-Marquardt algorithms has been used in the proposed artificial neural network. The case study shows that this neural network is efficient and forms a useful tool for the prediction of environmental quality.
Keywords
backpropagation; environmental science computing; feedforward neural nets; optimisation; pattern recognition; quality management; 4-9-1 three layer feedforward neural network; Levenberg-Marquardt algorithm; artificial neural network; backpropagation; environmental quality assessment; pattern recognition problem; Algorithm design and analysis; Artificial neural networks; Prediction algorithms; Soil; Levenberg-Marquardt algorithm; artificial neural network; backpropagation algorithm; environmental quality assessment;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564630
Filename
5564630
Link To Document