Research on multi-source heterogeneous data fusion algorithm of landslide monitoring based on BP neural network

WANG Zhiwei; WANG Li; HUANG Guanwen; HAN Qingqing; XU Fu; YUE Cong

doi:10.12090/j.issn.1006-6616.2020.26.04.050

Volume 26 Issue 4

Aug. 2020

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Article Navigation > Journal of Geomechanics > 2020 > 26(4): 575-582

WANG Zhiwei, WANG Li, HUANG Guanwen, et al., 2020. Research on multi-source heterogeneous data fusion algorithm of landslide monitoring based on BP neural network. Journal of Geomechanics, 26 (4): 575-582. DOI: 10.12090/j.issn.1006-6616.2020.26.04.050

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Research on multi-source heterogeneous data fusion algorithm of landslide monitoring based on BP neural network

doi: 10.12090/j.issn.1006-6616.2020.26.04.050

WANG Zhiwei^{1, 2, 3
,},
WANG Li^{1, 2, 3
,
,},
HUANG Guanwen^{1, 2, 3},
HAN Qingqing^{1, 2, 3},
XU Fu^{1, 2, 3},
YUE Cong^{1, 2, 3}

1.
College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China
2.
State Key Laboratory of Geographic Information Engineering, Xi'an 710054, Shaanxi, China
3.
Key Laboratory of Western China's Mineral Resources and Geological Engineering, Ministry of Education, Xi'an 710054, Shaanxi, China

More Information

Received: 2020-05-25
Revised: 2020-06-20
Published: 2020-08-28

Abstract

Abstract

Aiming at the multi-source heterogeneous data fusion problem of landslide monitoring,a multi-source heterogeneous monitoring data fusion algorithm based on BP neural network is proposed in this paper. The temperature,humidity,wind power,cloudiness,precipitation and accumulated precipitation which affect the landslide deformation are taken as the input variables,and the landslide displacement changes data are taken as the expected output data in this algorithm. And the prediction accuracy of this algorithm can be effectively improved by filtering the environmental factor variables with calculating the correlation and significance of the environmental factor variables and the landslide displacement changes. This algorithm is verified by the monitoring data of the Dangchuan landslide in Heifangtai,Yongjing County,Gansu Province. The results show that the BP neural network data fusion algorithm can be used in the landslide displacement prediction with multi-source heterogeneous monitoring data. After the environmental factor variable filtering,the determination coefficient of the BP neural network data fusion algorithm can achieve 0.985 and the RMSE can achieve 0.4787 mm. Thus the accuracy of deformation prediction can be effectively improved.
- landslide monitoring,
- multi-source heterogeneous data,
- data fusion,
- BP neural network,
- prediction

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References(80)

References

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Research on multi-source heterogeneous data fusion algorithm of landslide monitoring based on BP neural network

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