基于相空间重构和小波分析- 粒子群向量机的滑坡地下水位预测

黄, 发明

doi:10.3799/dqkx.2015.105

Eart. Scie.

2015

DOI: 10.3799/dqkx.2015.105

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基于相空间重构和小波分析- 粒子群向量机的滑坡地下水位预测

发明黄¹

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Cited by 3 publications

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A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide

Huang

Jiang

et al. 2017

Sci Rep

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It is important to monitor the displacement time series and to explore the failure mechanism of reservoir landslide for early warning. Traditionally, it is a challenge to monitor the landslide displacements real-timely and automatically. Globe Position System (GPS) is considered as the best real-time monitoring technology, however, the accuracies of the landslide displacements monitored by GPS are not assessed effectively. A web-based GPS system is developed to monitor the landslide displacements real-timely and automatically in this study. And the discrete wavelet transform (DWT) is proposed to assess the accuracy of the GPS monitoring displacements. Wangmiao landslide in Three Gorges Reservoir area in China is used as case study. The results show that the web-based GPS system has advantages of high precision, real-time, remote control and automation for landslide monitoring; the Root Mean Square Errors of the monitoring landslide displacements are less than 5 mm. Meanwhile, the results also show that a rapidly falling reservoir water level can trigger the reactivation of Wangmiao landslide. Heavy rainfall is also an important factor, but not a crucial component.

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A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide

Huang

Jiang

et al. 2017

Sci Rep

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Online prediction of dense medium suspension density based on phase space reconstruction

Sun

Cao

Yue

et al. 2017

Particulate Science and Technology

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Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

Huang

Zhou

et al. 2020

IOP Conf. Ser.: Earth Environ. Sci.

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The landslide susceptibility prediction (LSP) is generally implemented using certain types of single models; however, certain drawbacks exist in the single models; e.g., it is difficult to clearly reflect the weights of landslide-related environmental factors if only the information value (IV) model is adopted. To overcome these limitations, this study proposes an IV-logistic regression (IV-LR) model for LSP. The landslides that occurred in the southern part of Chongyi County, China, are used as study cases. Nine environmental factors—elevation, slope, plane curvature, profile curvature, relief amplitude, distance to river, lithology, normalized difference vegetable index, and normalized difference built-up index—are adopted based on remote sensing and geographic information system. Certain landslide grid units and the same number of non-landslide grid units are used as the output variables of these models. The IV, LR, and IV-LR models are used to implement the LSP in the southern part of Chongyi County. The predicted landslides susceptibility in Chongyi County mostly occurred in areas with low elevations, close distance to rivers, carbonate lithology, low vegetation coverage rate, and densely populated areas. The results show that the prediction rate of the IV-LR model (80.4%) is higher than that of the LR model (76.8%), followed by the IV model (72.8%); they further demonstrate that the IV-LR model has its unique superiority and rationality compared with the IV and LR models.

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基于相空间重构和小波分析- 粒子群向量机的滑坡地下水位预测

Cited by 3 publications

References 0 publications

A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide

A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide

Online prediction of dense medium suspension density based on phase space reconstruction

Landslide Susceptibility Prediction Based on the Information Value-Logistic Regression Model and Geographic Information System

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