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OpenAlex Citation Counts

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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:

Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm: A Case Study in the Nam Dam Commune, Vietnam
Quoc Cuong Tran, Duc Do Minh, Abolfazl Jaafari, et al.
Applied Sciences (2020) Vol. 10, Iss. 11, pp. 3710-3710
Open Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms
Asish Saha, Subodh Chandra Pal, Alireza Arabameri, et al.
Water (2021) Vol. 13, Iss. 2, pp. 241-241
Open Access | Times Cited: 141
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Binh Thai Pham, T. Nguyen‐Thoi, Chongchong Qi, et al.
CATENA (2020) Vol. 195, pp. 104805-104805
Closed Access | Times Cited: 136
Deep learning neural networks for spatially explicit prediction of flash flood probability
Mahdi Panahi, Abolfazl Jaafari, Ataollah Shirzadi, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101076-101076
Open Access | Times Cited: 120
Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques
Alireza Arabameri, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Journal of Hydrology Regional Studies (2021) Vol. 36, pp. 100848-100848
Open Access | Times Cited: 97
Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques
Binh Thai Pham, Abolfazl Jaafari, Tran Van Phong, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101105-101105
Open Access | Times Cited: 95
Mapping forest fire susceptibility using spatially explicit ensemble models based on the locally weighted learning algorithm
Tran Thi Tuyen, Abolfazl Jaafari, Hoang Phan Hải Yen, et al.
Ecological Informatics (2021) Vol. 63, pp. 101292-101292
Closed Access | Times Cited: 90
Landslide susceptibility mapping using CNN-1D and 2D deep learning algorithms: comparison of their performance at Asir Region, KSA
Ahmed M. Youssef, Biswajeet Pradhan, Abhirup Dikshit, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 4
Closed Access | Times Cited: 67
Classification of earthquakes, explosions and mining-induced earthquakes based on XGBoost algorithm
Tingting Wang, Yinju Bian, Yixiao Zhang, et al.
Computers & Geosciences (2022) Vol. 170, pp. 105242-105242
Open Access | Times Cited: 53
GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria
Hazem Ghassan Abdo, Hussein Almohamad, Ahmed Abdullah Al Dughairi, et al.
Sustainability (2022) Vol. 14, Iss. 8, pp. 4668-4668
Open Access | Times Cited: 52
Mapping Landslide Susceptibility Using Machine Learning Algorithms and GIS: A Case Study in Shexian County, Anhui Province, China
Zitao Wang, Qimeng Liu, Yu Liu
Symmetry (2020) Vol. 12, Iss. 12, pp. 1954-1954
Open Access | Times Cited: 65
Rainfall induced landslide susceptibility mapping using novel hybrid soft computing methods based on multi-layer perceptron neural network classifier
Mehebub Sahana, Binh Thai Pham, Manas Shukla, et al.
Geocarto International (2020) Vol. 37, Iss. 10, pp. 2747-2771
Closed Access | Times Cited: 56
Novel Ensemble Forecasting of Streamflow Using Locally Weighted Learning Algorithm
Rana Muhammad Adnan, Abolfazl Jaafari, Aadhityaa Mohanavelu, et al.
Sustainability (2021) Vol. 13, Iss. 11, pp. 5877-5877
Open Access | Times Cited: 48
Groundwater potential mapping in the Central Highlands of Vietnam using spatially explicit machine learning
Tran Xuan Bien, Abolfazl Jaafari, Tran Van Phong, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 131-146
Closed Access | Times Cited: 18
Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides
Binh Thai Pham, Abolfazl Jaafari, T. Nguyen‐Thoi, et al.
International Journal of Digital Earth (2020) Vol. 14, Iss. 5, pp. 575-596
Closed Access | Times Cited: 48
Assessment of Landslide Susceptibility Combining Deep Learning with Semi-Supervised Learning in Jiaohe County, Jilin Province, China
Jingyu Yao, Shengwu Qin, Shuangshuang Qiao, et al.
Applied Sciences (2020) Vol. 10, Iss. 16, pp. 5640-5640
Open Access | Times Cited: 44
GIS-based ensemble computational models for flood susceptibility prediction in the Quang Binh Province, Vietnam
Chinh Luu, Binh Thai Pham, Tran Van Phong, et al.
Journal of Hydrology (2021) Vol. 599, pp. 126500-126500
Closed Access | Times Cited: 41
Landslide susceptibility mapping using state-of-the-art machine learning ensembles
Binh Thai Pham, Vu Duy Vinh, Romulus Costache, et al.
Geocarto International (2021) Vol. 37, Iss. 18, pp. 5175-5200
Closed Access | Times Cited: 35
Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Mapping
Duong Hai Ha, Phong Tung Nguyen, Romulus Costache, et al.
Water Resources Management (2021) Vol. 35, Iss. 13, pp. 4415-4433
Closed Access | Times Cited: 33
Hybrid artificial intelligence models based on adaptive neuro fuzzy inference system and metaheuristic optimization algorithms for prediction of daily rainfall
Binh Thai Pham, Kien-Trinh Thi Bui, Indra Prakash, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024) Vol. 134, pp. 103563-103563
Closed Access | Times Cited: 6
Groundwater spring potential mapping: Assessment the contribution of hydrogeological factors
Rui Zhao, Chenchen Fan, Alireza Arabameri, et al.
Advances in Space Research (2024) Vol. 74, Iss. 1, pp. 48-64
Closed Access | Times Cited: 6
Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province, Vietnam
Hoang Phan Hải Yen, Binh Thai Pham, Tran Van Phong, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101154-101154
Open Access | Times Cited: 31
Integrating Support Vector Machines with Different Ensemble Learners for Improving Streamflow Simulation in an Ungauged Watershed
Yahi Takai Eddine, Nadir Marouf, Sehtal Sabah, et al.
Water Resources Management (2023) Vol. 38, Iss. 2, pp. 553-567
Closed Access | Times Cited: 12
Exploring deep learning models for roadside landslide prediction: Insights and implications from comparative analysis
Tiep Nguyen Viet, Dam Duc Nguyen, Manh Nguyen Duc, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024), pp. 103741-103741
Closed Access | Times Cited: 4
A machine learning approach in spatial predicting of landslides and flash flood susceptible zones for a road network
Hang Ha, Quynh Duy Bui, Thanh Dong Khuc, et al.
Modeling Earth Systems and Environment (2022) Vol. 8, Iss. 4, pp. 4341-4357
Closed Access | Times Cited: 18
Application of a Novel Hybrid Machine Learning Algorithm in Shallow Landslide Susceptibility Mapping in a Mountainous Area
Bahareh Ghasemian, Himan Shahabi, Ataollah Shirzadi, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 16
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