On the public citation graph

Improving Rockfall Susceptibility Mapping by Tr-Rf Transfer Learning Model

https://doi.org/10.2139/ssrn.4649857
0 signed · 49 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10064-022-02601-6openalex-extracted
Construction of small sample seismic landslide susceptibility evaluation model based on Transfer Learning: a case study of Jiuzhaigou earthquake
inferredcites →https://doi.org/10.1007/s10346-016-0713-7openalex-extracted
Rockfall susceptibility zoning based on back analysis of rockfall deposit inventory in Gunung Kelir, Java
inferredcites →https://doi.org/10.1007/s10346-016-0769-4openalex-extracted
Applying Information Theory and GIS-based quantitative methods to produce landslide susceptibility maps in Nancheng County, China
inferredcites →https://doi.org/10.1007/s11069-018-3299-7openalex-extracted
Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models
inferredcites →https://doi.org/10.1007/s11629-018-4833-5openalex-extracted
Landslide susceptibility mapping using Genetic Algorithm for the Rule Set Production (GARP) model
inferredcites →https://doi.org/10.1007/s12524-021-01451-1openalex-extracted
Landslide Susceptibility Mapping Using Machine Learning Algorithm: A Case Study Along Karakoram Highway (KKH), Pakistan
inferredcites →https://doi.org/10.1007/s42452-020-3060-1openalex-extracted
Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest
inferredcites →https://doi.org/10.1016/j.cageo.2012.08.023openalex-extracted
A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
inferredcites →https://doi.org/10.1016/j.catena.2019.104364openalex-extracted
Investigating the effects of different landslide positioning techniques, landslide partitioning approaches, and presence-absence balances on landslide susceptibility mapping
inferredcites →https://doi.org/10.1016/j.catena.2022.106799openalex-extracted
Landslide susceptibility assessment through TrAdaBoost transfer learning models using two landslide inventories
inferredcites →https://doi.org/10.1016/j.chemolab.2019.103824openalex-extracted
Cross components calibration transfer of NIR spectroscopy model through PCA and weighted ELM-based TrAdaBoost algorithm
inferredcites →https://doi.org/10.1016/j.earscirev.2018.03.001openalex-extracted
A review of statistically-based landslide susceptibility models
inferredcites →https://doi.org/10.1016/j.earscirev.2020.103225openalex-extracted
Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
inferredcites →https://doi.org/10.1016/j.enggeo.2010.09.009openalex-extracted
Landslide susceptibility mapping in Injae, Korea, using a decision tree
inferredcites →https://doi.org/10.1016/j.enggeo.2019.105237openalex-extracted
Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment
inferredcites →https://doi.org/10.1016/j.enggeo.2021.106301openalex-extracted
Rockfall susceptibility and network-ranked susceptibility along the Italian railway
inferredcites →https://doi.org/10.1016/j.geomorph.2016.01.008openalex-extracted
Regional-scale controls on the spatial activity of rockfalls (Turtmann Valley, Swiss Alps) — A multivariate modeling approach
inferredcites →https://doi.org/10.1016/j.geomorph.2020.107084openalex-extracted
Regional susceptibility assessments with heterogeneous landslide information: Slope unit- vs. pixel-based approach
inferredcites →https://doi.org/10.1016/j.geomorph.2020.107124openalex-extracted
Parameter-free delineation of slope units and terrain subdivision of Italy
inferredcites →https://doi.org/10.1016/j.geomorph.2020.107201openalex-extracted
A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm
inferredcites →https://doi.org/10.1016/j.gsf.2020.07.012openalex-extracted
Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer
inferredcites →https://doi.org/10.1016/j.gsf.2020.09.002openalex-extracted
Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks
inferredcites →https://doi.org/10.1016/j.gsf.2021.101211openalex-extracted
Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
inferredcites →https://doi.org/10.1016/j.ijrmms.2017.07.013openalex-extracted
Qualitative evolving rockfall hazard assessment for highwalls
inferredcites →https://doi.org/10.1016/j.measurement.2021.109340openalex-extracted
Cross target attributes and sample types quantitative analysis modeling of near-infrared spectroscopy based on instance transfer learning
inferredcites →https://doi.org/10.1016/j.neucom.2013.10.044openalex-extracted
Deformation prediction of landslide based on functional network
inferredcites →https://doi.org/10.1016/j.scitotenv.2018.04.055openalex-extracted
GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-extracted
Random Forests
inferredcites →https://doi.org/10.1038/ngeo2686openalex-extracted
Rockfall triggering by cyclic thermal stressing of exfoliation fractures
inferredcites →https://doi.org/10.1038/s41598-019-43146-1openalex-extracted
Monitoring and early warning method for a rockfall along railways based on vibration signal characteristics
inferredcites →https://doi.org/10.1080/13658810802443457openalex-extracted
Geographical Detectors‐Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China
inferredcites →https://doi.org/10.1080/19475705.2021.1943544openalex-extracted
Exploring novel hybrid soft computing models for landslide susceptibility mapping in Son La hydropower reservoir basin
inferredcites →https://doi.org/10.1109/icassp43922.2022.9746999openalex-extracted
Feature Augmentation Learning for Few-Shot Palmprint Image Recognition With Unconstrained Acquisition
inferredcites →https://doi.org/10.1109/jstars.2018.2859836openalex-extracted
TrAdaBoost Based on Improved Particle Swarm Optimization for Cross-Domain Scene Classification With Limited Samples
inferredcites →https://doi.org/10.1109/tkde.2009.191openalex-extracted
A Survey on Transfer Learning
inferredcites →https://doi.org/10.1126/science.aba1510openalex-extracted
Global threat of arsenic in groundwater
inferredcites →https://doi.org/10.1145/1273496.1273521openalex-extracted
Boosting for transfer learning
inferredcites →https://doi.org/10.3390/app112311193openalex-extracted
Deep Transfer Learning Approach for Identifying Slope Surface Cracks
inferredcites →https://doi.org/10.3390/rs10121923openalex-extracted
Rockfall Simulation Based on UAV Photogrammetry Data Obtained during an Emergency Declaration: Application at a Cultural Heritage Site
inferredcites →https://doi.org/10.3390/rs12071194openalex-extracted
Shallow Landslide Susceptibility Models Based on Artificial Neural Networks Considering the Factor Selection Method and Various Non-Linear Activation Functions
inferredcites →https://doi.org/10.3390/rs13132546openalex-extracted
Applicability of Susceptibility Model for Rock and Loess Earthquake Landslides in the Eastern Tibetan Plateau
inferredcites →https://doi.org/10.3390/rs13132625openalex-extracted
Quantitative Assessment of Landslide Risk Based on Susceptibility Mapping Using Random Forest and GeoDetector
inferredcites →https://doi.org/10.3390/rs14112707openalex-extracted
Landslide Susceptibility Mapping Based on the Germinal Center Optimization Algorithm and Support Vector Classification
inferredcites →https://doi.org/10.3390/s23083856openalex-extracted
Improving Recognition Accuracy of Pesticides in Groundwater by Applying TrAdaBoost Transfer Learning Method
inferredcites →https://doi.org/10.5194/gmd-9-3975-2016openalex-extracted
Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling
inferredcites →https://doi.org/10.5194/nhess-11-2617-2011openalex-extracted
Rockfall characterisation and structural protection – a review
inferredcites →https://doi.org/10.5194/nhess-18-321-2018openalex-extracted
UAV-based mapping, back analysis and trajectory modeling of a coseismic rockfall in Lefkada island, Greece
inferredcites →https://doi.org/10.5194/nhess-5-853-2005openalex-extracted
Spatial prediction models for landslide hazards: review, comparison and evaluation
inferredcites →https://doi.org/10.5194/se-5-1329-2014openalex-extracted
Characterization and interaction of driving factors in karst rocky desertification: a case study from Changshun, China
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.