Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
Assessments of landslide disasters are becoming increasingly urgent. The aim of this study
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
Identifying the essential conditioning factors of landslide susceptibility models under different grid resolutions using hybrid machine learning: A case of Wushan and …
This study attempts to identify the essential conditioning factors of landslides to increase the
predictive ability of landslide susceptibility models and explore the effects of different grid …
predictive ability of landslide susceptibility models and explore the effects of different grid …
[HTML][HTML] Landslide susceptibility assessment by using convolutional neural network
This study performs a GIS-based landslide susceptibility assessment using a convolutional
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …
GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches
In arid and semi-arid areas, groundwater resource is one of the most important water
sources by the humankind. Knowledge of groundwater distribution over space, associated …
sources by the humankind. Knowledge of groundwater distribution over space, associated …
Landslide susceptibility modeling using integrated ensemble weights of evidence with logistic regression and random forest models
W Chen, Z Sun, J Han - Applied sciences, 2019 - mdpi.com
The main aim of this study was to compare the performances of the hybrid approaches of
traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE …
traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE …
[HTML][HTML] Hydrography90m: A new high-resolution global hydrographic dataset
The geographic distribution of streams and rivers drives a multitude of patterns and
processes in hydrology, geomorphology, geography, and ecology. Therefore, a …
processes in hydrology, geomorphology, geography, and ecology. Therefore, a …
Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree
W Chen, X Zhao, H Shahabi, A Shirzadi… - Geocarto …, 2019 - Taylor & Francis
In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic
regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility …
regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility …
Landslide susceptibility evaluation using hybrid integration of evidential belief function and machine learning techniques
Y Li, W Chen - Water, 2019 - mdpi.com
In this study, Random SubSpace-based classification and regression tree (RSCART) was
introduced for landslide susceptibility modeling, and CART model and logistic regression …
introduced for landslide susceptibility modeling, and CART model and logistic regression …
Intelligent approach based on random forest for safety risk prediction of deep foundation pit in subway stations
The number of safety accidents caused by excavation of deep foundation pits in subway
stations has been increasing rapidly in recent years. Thus, precisely predicting the safety …
stations has been increasing rapidly in recent years. Thus, precisely predicting the safety …
[HTML][HTML] Bibliometric analysis of landslide research based on the WOS database
This work, based on the Web of Science (WOS) database, collected 20,888 research articles
published from 1982 to November 2021 on the topic of landslide (s). We performed a …
published from 1982 to November 2021 on the topic of landslide (s). We performed a …