Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Showing 18 citing articles:

A novel deep learning framework for landslide susceptibility assessment using improved deep belief networks with the intelligent optimization algorithm
Shaoqiang Meng, Zhenming Shi, Gang Li, et al.
Computers and Geotechnics (2024) Vol. 167, pp. 106106-106106
Closed Access | Times Cited: 23
Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan
Nafees Ali, Jian Chen, Xiaodong Fu, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 988-988
Open Access | Times Cited: 16
Integrating a multi-dimensional deep convolutional neural network with optimized sample selection for landslide susceptibility assessment
Yueyue Wang, Xueling Wu, Kun Zou, et al.
Geo-spatial Information Science (2025), pp. 1-21
Open Access | Times Cited: 1
Landslide susceptibility assessment based on remote sensing interpretation and DBN-MLP model: a case study of Yiyuan County, China
Shufeng Li, Chao Yin, Jiaxu Li, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access
Study on the susceptibility of geological disasters in loess tableland area of northern Shaanxi based on GIS and information quantity model
Junwei Qiao, Yi Jiang, Feng Lv, et al.
All Earth (2025) Vol. 37, Iss. 1, pp. 1-15
Open Access
Landslide Susceptibility Assessment Using Recurrent Neural Network (RNN)—A Case of Chabahar and Konarak in Iran
Vahid Isazade, Abdul Baser Qasimi, Mahdi Safari Namivandi, et al.
Indian geotechnical journal (2025)
Closed Access
Increasing Landslide Susceptibility in Urbanized Areas of Petrópolis Identified Through Spatio-Temporal Analysis
Cheila Flávia de Praga Baião, José Roberto Mantovani, Enner Alcântara
Journal of South American Earth Sciences (2025), pp. 105509-105509
Closed Access
Landslide susceptibility prediction modelling based on semi‐supervised XGBoost model
Qiangqiang Shua, Hongbin Peng, Jingkai Li
Geological Journal (2024) Vol. 59, Iss. 9, pp. 2655-2667
Closed Access | Times Cited: 3
An Improved Deep Learning Approach Considering Spatiotemporal Heterogeneity for PM2.5 Prediction: A Case Study of Xinjiang, China
Yajing Wu, Zhangyan Xu, Liping Xu, et al.
Atmosphere (2024) Vol. 15, Iss. 4, pp. 460-460
Open Access | Times Cited: 3
Machine Learning Approaches for Mapping and Predicting Landslide-Prone Areas in São Sebastião (Southeast Brazil)
Enner Alcântara, Cheila Flávia de Praga Baião, Yasmim Carvalho Guimarães, et al.
Natural Hazards Research (2024)
Open Access | Times Cited: 3
Machine learning potentials for global multi-timescale diffuse irradiance estimation: synthesizing ground observations, time-series, and environmental features*
Nannan Wang, Zijian Yue, Yaolin Liu, et al.
Energy (2024) Vol. 306, pp. 132535-132535
Closed Access | Times Cited: 1
A two-stage spatial prediction modeling approach based on graph neural networks and neural processes
Lili Bao, Chunxia Zhang, Jiangshe Zhang, et al.
Expert Systems with Applications (2024) Vol. 258, pp. 125173-125173
Closed Access
Landslide Susceptibility Mapping in North Tehran, Iran: Linear Regression, Neural Networks, and Fuzzy Logic Approaches
Ali Asghar Ghaedi Vanani, Gholamreza Shoaei, Mehdi Zaré
Geotechnical and Geological Engineering (2024)
Closed Access
O9Answering new urban questions: Using eXplainable AI-driven analysis to identify determinants of Airbnb price in Dublin
Amir Panahandeh, Hamidreza Rabiei‐Dastjerdi, Polat Göktaş, et al.
Expert Systems with Applications (2024), pp. 125360-125360
Closed Access
A novel framework for debris flow susceptibility assessment considering the uncertainty of sample selection
Can Yang, Jiao Wang, Guotao Zhang
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access
Comparative study of sampling strategies for machine learning-based landslide susceptibility assessment
Xiaodong Liu, Ting Xiao, Shaohe Zhang, et al.
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 12, pp. 4935-4957
Closed Access
Improved landslide prediction by considering continuous and discrete spatial dependency
Zhice Fang, Jingjing Wang, Yi Wang, et al.
Landslides (2024)
Closed Access
A debris flow susceptibility mapping study considering sample heterogeneity
Ruiyuan Gao, Di Wu, Hailiang Liu, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 6, pp. 5459-5470
Closed Access
Page 1

Scroll to top