Prediction model oriented for landslide displacement with step-like curve by applying ensemble empirical mode decomposition and the PSO-ELM method

Du, Han; Song, Danqing; Chen, Zhuo; Shu, Heping; Guo, Zhengfu

doi:10.1016/j.jclepro.2020.122248

Cited by 89 publications

(38 citation statements)

References 55 publications

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“…49 The joints can be distributed complexly due to their uncertain geometric and mechanical parameters, such as direction, dip angle, and location. [50][51][52] Given the abovementioned analysis, the dynamic mechanical properties of rock slopes with structural planes are very complicated under dynamic disturbance.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, joints, which constitute weak structural surfaces, are widely distributed throughout rock slopes 48 and negatively affect the integrity of the rock mass 49 . The joints can be distributed complexly due to their uncertain geometric and mechanical parameters, such as direction, dip angle, and location 50‐52 . Given the abovementioned analysis, the dynamic mechanical properties of rock slopes with structural planes are very complicated under dynamic disturbance.…”

Section: Introductionmentioning

confidence: 99%

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Experimental study of the influence of structural planes on the mechanical properties of sandstone specimens under cyclic dynamic disturbance

Song

Chen

et al. 2020

Energy Science & Engineering

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In recent years, with the increasing demand for mineral deposit resources and continuous consumption of shallow resources, many mines are gradually entering the deep mining state so that open-pit mines on high and steep slopes can be excavated. 1-4 The ultra-deep mine of TauTona in South Africa is known to extend at least 3500 m. 5 The Asturian coal basin in Spain has already reached depths exceeding 4000 m. 6 According to statistical analysis using the protocol

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental study of the influence of structural planes on the mechanical properties of sandstone specimens under cyclic dynamic disturbance

Song

Chen

et al. 2020

Energy Science & Engineering

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“…In recent years, the development and construction of urban development in central China have advanced rapidly (Kassomenos et al 2016;Cui et al 2018;Chen et al 2020;Du et al 2020). The construction of underground spaces inevitably rely on deep foundation pit engineering Liu, Song, et al 2020;Song, Chen, Chao, et al 2020;.…”

Section: Introductionmentioning

confidence: 99%

Monitoring analysis of influence of extra-large complex deep foundation pit on adjacent environment: a case study of Zhengzhou City, China

Song

Chen

Dong

et al. 2020

Geomatics, Natural Hazards and Risk

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Extra-large complex deep foundation pit excavation has an impact on the surrounding environment. The deformation characteristics of deep foundation pits were investigated during excavation, according to the temporal and spatial variations in displacement, using long-term on-site displacement monitoring. The results show that the deformation characteristics of the supporting structure and surrounding buildings can be divided into four stages: earth excavation, cushion construction, internal support removal and cushion completion. In the stages of earthwork excavation and support removal, the settlement deformation of the supporting pile roof, lattice column and adjacent ground is large, and cushion construction has a weakening effect on foundation pit deformation. In the stages of earthwork excavation, cushion construction and internal support removal, the nonuniform settlement between adjacent lattice columns increases the lattice column deformation, and the deformation of the foundation pit tends to be stable after the completion of the internal support. The foundation pit excavation mainly affects the settlement deformation of the adjacent pipe gallery, and its deformation increases rapidly in the early stage of earthwork excavation. Moreover, the influence degree of foundation pit excavation on the surrounding environment decreases with increasing distance from the excavation area.

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“…In addition, the conventional ELM architecture sometimes does not have good generalization capability [17,18]. To address the above issues, we propose to employ a particle swarm limiting learning machine algorithm that employs a combination of PSO and ELM [19]. Specifically, the PSO algorithm is used to optimize the weights of the input layer and the deviations of the hidden layer.…”

Section: Introductionmentioning

confidence: 99%

Inversion modeling of japonica rice canopy chlorophyll content with UAV hyperspectral remote sensing

Cao

Jiang

et al. 2020

PLoS ONE

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Chlorophyll content is an important indicator of the growth status of japonica rice. The objective of this paper is to develop an inversion model that can predict japonica rice chlorophyll content by using hyperspectral image of rice canopy collected with unmanned aerial vehicle (UAV). UAV-based hyperspectral remote sensing can provide timely and cost-effective monitoring of chlorophyll content over a large region. The study was based on hyperspectral data collected at the Shenyang Agricultural College Academician Japonica Rice Experimental Base in 2018 and 2019. In order to extract the salient information embedded in the highdimensional hyperspectral data, we first perform dimension reduction by using a successive projection algorithm (SPA). The SPA extracts the characteristic hyperspectral bands that are used as input to the inversion model. The characteristic bands extracted by SPA are 410 nm, 481 nm, 533 nm, 702 nm, and 798 nm, respectively. The inversion model is developed by using an extreme learning machine (ELM), the parameters of which are optimized by using particle swarm optimization (PSO). The PSO-ELM algorithm can accurately model the nonlinear relationship between hyperspectral data and chlorophyll content. The model achieves a coefficient of determination R 2 = 0.791 and a root mean square error of RMSE = 8.215 mg/L. The model exhibits good predictive ability and can provide data support and model reference for research on nutrient diagnosis of japonica rice.

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Prediction model oriented for landslide displacement with step-like curve by applying ensemble empirical mode decomposition and the PSO-ELM method

Cited by 89 publications

References 55 publications

Experimental study of the influence of structural planes on the mechanical properties of sandstone specimens under cyclic dynamic disturbance

Experimental study of the influence of structural planes on the mechanical properties of sandstone specimens under cyclic dynamic disturbance

Monitoring analysis of influence of extra-large complex deep foundation pit on adjacent environment: a case study of Zhengzhou City, China

Inversion modeling of japonica rice canopy chlorophyll content with UAV hyperspectral remote sensing

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