Analysis on uranic slope stability based on neural network

Yufeng Zhu; Xiaoli Ding; Zhiwei Li; Shijian Zhou

doi:10.1109/IFITA.2010.293

Analysis on uranic slope stability based on neural network

Yufeng Zhu, Xiaoli Ding, Zhiwei Li, Shijian Zhou

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems , such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.

Original language	English
Title of host publication	Proceedings - 2010 International Forum on Information Technology and Applications, IFITA 2010
Pages	421-423
Number of pages	3
Volume	3
DOIs	https://doi.org/10.1109/IFITA.2010.293
Publication status	Published - 1 Dec 2010
Externally published	Yes
Event	2010 International Forum on Information Technology and Applications, IFITA 2010 - Kunming, China Duration: 16 Jul 2010 → 18 Jul 2010

Conference

Conference	2010 International Forum on Information Technology and Applications, IFITA 2010
Country/Territory	China
City	Kunming
Period	16/07/10 → 18/07/10

Keywords

Forecast network model
Neural network
Safety of slope
Uranic slope

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications

More information

10.1109/IFITA.2010.293

Cite this

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title = "Analysis on uranic slope stability based on neural network",

abstract = "How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems , such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.",

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Zhu, Y, Ding, X, Li, Z & Zhou, S 2010, Analysis on uranic slope stability based on neural network. in Proceedings - 2010 International Forum on Information Technology and Applications, IFITA 2010. vol. 3, 5635020, pp. 421-423, 2010 International Forum on Information Technology and Applications, IFITA 2010, Kunming, China, 16/07/10. https://doi.org/10.1109/IFITA.2010.293

Analysis on uranic slope stability based on neural network. / Zhu, Yufeng; Ding, Xiaoli; Li, Zhiwei et al.
Proceedings - 2010 International Forum on Information Technology and Applications, IFITA 2010. Vol. 3 2010. p. 421-423 5635020.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Analysis on uranic slope stability based on neural network

AU - Zhu, Yufeng

AU - Ding, Xiaoli

AU - Li, Zhiwei

AU - Zhou, Shijian

PY - 2010/12/1

Y1 - 2010/12/1

N2 - How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems , such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.

AB - How to accurately predict the occurrence of landslides, and it has become one of the troubles in the mining process. The author made a brief introduction of artificial neural network and BP network model in this paper, and also analysis some important problems , such as the parameters selecting, data collecting, processing and network constituting by using the study and forecast samples which from the slope stability of Fuzhou Jin-An Uranium Industry Limited Company, and then setting a prediction model. This paper discusses the slope stability methods and its effectiveness based on the BP neural network. Examples of calculation shows that the using of artificial neural network approaching to the stability of the slope of the forecast can made satisfactory results through the training sample test. This model provides a viable method for the future stability of the slope of such evaluation. At the same time, the feasibility of the application for the neural network in the mine slope stability is proved.

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Analysis on uranic slope stability based on neural network

Abstract

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Keywords

ASJC Scopus subject areas

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