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A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm
A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm
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A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm

Sun, Deliang ; Wen, Haijia ; Wang, Danzhou ; Xu, Jiahui

Geomorphology (Amsterdam, Netherlands), 2020-08, Vol.362, p.107201, Article 107201 [Periódico revisado por pares]

Elsevier B.V

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The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds
The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds
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The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds

Ouédraogo, Mohamar Moussa ; Degré, Aurore ; Debouche, Charles ; Lisein, Jonathan

Geomorphology (Amsterdam, Netherlands), 2014-06, Vol.214, p.339-355 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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3
Rainfall thresholds for possible landslide occurrence in Italy
Rainfall thresholds for possible landslide occurrence in Italy
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Rainfall thresholds for possible landslide occurrence in Italy

Peruccacci, Silvia ; Brunetti, Maria Teresa ; Gariano, Stefano Luigi ; Melillo, Massimo ; Rossi, Mauro ; Guzzetti, Fausto

Geomorphology (Amsterdam, Netherlands), 2017-08, Vol.290, p.39-57 [Periódico revisado por pares]

Elsevier B.V

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4
Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques
Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques
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Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

Chen, Wei ; Pourghasemi, Hamid Reza ; Panahi, Mahdi ; Kornejady, Aiding ; Wang, Jiale ; Xie, Xiaoshen ; Cao, Shubo

Geomorphology (Amsterdam, Netherlands), 2017-11, Vol.297, p.69-85 [Periódico revisado por pares]

Elsevier B.V

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5
Scaling and design of landslide and debris-flow experiments
Scaling and design of landslide and debris-flow experiments
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Scaling and design of landslide and debris-flow experiments

Iverson, Richard M.

Geomorphology (Amsterdam, Netherlands), 2015-09, Vol.244, p.9-20 [Periódico revisado por pares]

Elsevier B.V

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Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion
Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion
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Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion

Rahmati, Omid ; Tahmasebipour, Nasser ; Haghizadeh, Ali ; Pourghasemi, Hamid Reza ; Feizizadeh, Bakhtiar

Geomorphology (Amsterdam, Netherlands), 2017-12, Vol.298, p.118-137 [Periódico revisado por pares]

Elsevier B.V

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7
Gully morphological characteristics in the loess hilly‐gully region based on 3D laser scanning technique
Gully morphological characteristics in the loess hilly‐gully region based on 3D laser scanning technique
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Gully morphological characteristics in the loess hilly‐gully region based on 3D laser scanning technique

Wu, Hongyan ; Xu, Ximeng ; Zheng, Fenli ; Qin, Chao ; He, Xu

Earth surface processes and landforms, 2018-06, Vol.43 (8), p.1701-1710 [Periódico revisado por pares]

Bognor Regis: Wiley Subscription Services, Inc

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8
Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models
Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models
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Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models

Hong, Haoyuan ; Pourghasemi, Hamid Reza ; Pourtaghi, Zohre Sadat

Geomorphology (Amsterdam, Netherlands), 2016-04, Vol.259, p.105-118 [Periódico revisado por pares]

Elsevier B.V

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9
Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
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Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)

Trigila, Alessandro ; Iadanza, Carla ; Esposito, Carlo ; Scarascia-Mugnozza, Gabriele

Geomorphology (Amsterdam, Netherlands), 2015-11, Vol.249, p.119-136 [Periódico revisado por pares]

Elsevier B.V

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10
An approach for measuring confinement and assessing the influence of valley setting on river forms and processes
An approach for measuring confinement and assessing the influence of valley setting on river forms and processes
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An approach for measuring confinement and assessing the influence of valley setting on river forms and processes

Fryirs, Kirstie A. ; Wheaton, Joseph M. ; Brierley, Gary J.

Earth surface processes and landforms, 2016-04, Vol.41 (5), p.701-710 [Periódico revisado por pares]

Bognor Regis: Blackwell Publishing Ltd

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