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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 Entropy and Rotation Forest-Based Credal Decision Tree Classifier for Landslide Susceptibility Modeling
Qingfeng He, Zhihao Xu, Shaojun Li, et al.
Entropy (2019) Vol. 21, Iss. 2, pp. 106-106
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

Machine learning in medical applications: A review of state-of-the-art methods
Mohammad Shehab, Laith Abualigah, Qusai Y. Shambour, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105458-105458
Closed Access | Times Cited: 334
Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models
Ebrahim Nohani, Meysam Moharrami, Siyamack Sharafi, et al.
Water (2019) Vol. 11, Iss. 7, pp. 1402-1402
Open Access | Times Cited: 215
GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment
Binh Thai Pham, Mohammadtaghi Avand, Saeid Janizadeh, et al.
Water (2020) Vol. 12, Iss. 3, pp. 683-683
Open Access | Times Cited: 207
Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer
Wei Chen, Xi Chen, Jianbing Peng, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 1, pp. 93-107
Open Access | Times Cited: 167
GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment
Anna Roccati, Guido Paliaga, Fabio Luino, et al.
Land (2021) Vol. 10, Iss. 2, pp. 162-162
Open Access | Times Cited: 110
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
Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran
Viet‐Ha Nhu, Ataollah Shirzadi, Himan Shahabi, et al.
Forests (2020) Vol. 11, Iss. 4, pp. 421-421
Open Access | Times Cited: 115
Decision tree based ensemble machine learning approaches for landslide susceptibility mapping
Alireza Arabameri, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Geocarto International (2021) Vol. 37, Iss. 16, pp. 4594-4627
Closed Access | Times Cited: 105
Landslide Susceptibility Evaluation Using Hybrid Integration of Evidential Belief Function and Machine Learning Techniques
Yang Li, Wei Chen
Water (2019) Vol. 12, Iss. 1, pp. 113-113
Open Access | Times Cited: 92
Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers
Binh Thai Pham, Tran Van Phong, T. Nguyen‐Thoi, et al.
Geocarto International (2020) Vol. 37, Iss. 3, pp. 735-757
Closed Access | Times Cited: 92
Hybrid Computational Intelligence Methods for Landslide Susceptibility Mapping
Guirong Wang, Xinxiang Lei, Wei Chen, et al.
Symmetry (2020) Vol. 12, Iss. 3, pp. 325-325
Open Access | Times Cited: 76
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
Risk Assessment of Resources Exposed to Rainfall Induced Landslide with the Development of GIS and RS Based Ensemble Metaheuristic Machine Learning Algorithms
Javed Mallick, Saeed Alqadhi, Swapan Talukdar, et al.
Sustainability (2021) Vol. 13, Iss. 2, pp. 457-457
Open Access | Times Cited: 58
Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques
Bilal Khan, Rashid Naseem, Muhammad Arif Shah, et al.
Journal of Healthcare Engineering (2021) Vol. 2021, pp. 1-16
Open Access | Times Cited: 58
Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia
Siti Norsakinah Selamat, Nuriah Abd Majid, Mohd Raihan Taha, et al.
Land (2022) Vol. 11, Iss. 6, pp. 833-833
Open Access | Times Cited: 42
Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzău River Catchment, Romania
Mihnea Cristian Popa, Daniel Peptenatu, Cristian-Constantin Drăghici, et al.
Water (2019) Vol. 11, Iss. 10, pp. 2116-2116
Open Access | Times Cited: 73
Landslide spatial modelling using unsupervised factor optimisation and regularised greedy forests
Maher Ibrahim Sameen, Raju Sarkar, Biswajeet Pradhan, et al.
Computers & Geosciences (2019) Vol. 134, pp. 104336-104336
Open Access | Times Cited: 56
Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling
Phong Tung Nguyen, Duong Hai Ha, Huu Duy Nguyen, et al.
Sustainability (2020) Vol. 12, Iss. 7, pp. 2622-2622
Open Access | Times Cited: 53
Bagging-based machine learning algorithms for landslide susceptibility modeling
Tingyu Zhang, Quan Fu, Hao Wang, et al.
Natural Hazards (2021) Vol. 110, Iss. 2, pp. 823-846
Open Access | Times Cited: 50
Automatic Classification of Fatty Liver Disease Based on Supervised Learning and Genetic Algorithm
Ahmed Gaber, Hassan Youness, Alaa Hamdy, et al.
Applied Sciences (2022) Vol. 12, Iss. 1, pp. 521-521
Open Access | Times Cited: 32
Novel Credal Decision Tree-Based Ensemble Approaches for Predicting the Landslide Susceptibility
Alireza Arabameri, Ebrahim Karimi Sangchini, Subodh Chandra Pal, et al.
Remote Sensing (2020) Vol. 12, Iss. 20, pp. 3389-3389
Open Access | Times Cited: 49
GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam
Viet-Tien Nguyen, Trong Hien Tran, Ngoc Ha, et al.
Sustainability (2019) Vol. 11, Iss. 24, pp. 7118-7118
Open Access | Times Cited: 48
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
GIS-based ensemble soft computing models for landslide susceptibility mapping
Binh Thai Pham, Tran Van Phong, T. Nguyen‐Thoi, et al.
Advances in Space Research (2020) Vol. 66, Iss. 6, pp. 1303-1320
Closed Access | Times Cited: 43
Groundwater Potential Mapping Using GIS‐Based Hybrid Artificial Intelligence Methods
Tran Van Phong, Binh Thai Pham, Phan Trọng Trịnh, et al.
Ground Water (2021) Vol. 59, Iss. 5, pp. 745-760
Closed Access | Times Cited: 35
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