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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:

Integrating multilayer perceptron neural nets with hybrid ensemble classifiers for deforestation probability assessment in Eastern India
Sunil Saha, Gopal Chandra Paul, Biswajeet Pradhan, et al.
Geomatics Natural Hazards and Risk (2020) Vol. 12, Iss. 1, pp. 29-62
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation
Manoranjan Mishra, Rajkumar Guria, Biswaranjan Baraj, et al.
The Science of The Total Environment (2024) Vol. 926, pp. 171713-171713
Closed Access | Times Cited: 26
Flood susceptibility mapping in an arid region of Pakistan through ensemble machine learning model
Andaleeb Yaseen, Jianzhong Lu, Xiaoling Chen
Stochastic Environmental Research and Risk Assessment (2022) Vol. 36, Iss. 10, pp. 3041-3061
Open Access | Times Cited: 40
Global Review of Modification, Optimization, and Improvement Models for Aquifer Vulnerability Assessment in the Era of Climate Change
Mojgan Bordbar, Fatemeh Rezaie, Sayed M. Bateni, et al.
Current Climate Change Reports (2024) Vol. 9, Iss. 4, pp. 45-67
Closed Access | Times Cited: 9
Detection of areas prone to flood risk using state-of-the-art machine learning models
Romulus Costache, Alireza Arabameri, Ismail Elkhrachy, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1488-1507
Open Access | Times Cited: 53
Proposing an ensemble machine learning based drought vulnerability index using M5P, dagging, random sub-space and rotation forest models
Sunil Saha, Barnali Kundu, Gopal Chandra Paul, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 7, pp. 2513-2540
Open Access | Times Cited: 18
Multi-Layer Perceptron-Based Classification with Application to Outlier Detection in Saudi Arabia Stock Returns
Khudhayr A. Rashedi, Mohd Tahir Ismail, S. Al Wadi, et al.
Journal of risk and financial management (2024) Vol. 17, Iss. 2, pp. 69-69
Open Access | Times Cited: 8
Constructing the machine learning techniques based spatial drought vulnerability index in Karnataka state of India
Sunil Saha, Priyanka Gogoi, Amiya Gayen, et al.
Journal of Cleaner Production (2021) Vol. 314, pp. 128073-128073
Closed Access | Times Cited: 41
Deep learning algorithms to develop Flood susceptibility map in Data-Scarce and Ungauged River Basin in India
Sunil Saha, Amiya Gayen, Bijoy Bayen
Stochastic Environmental Research and Risk Assessment (2022) Vol. 36, Iss. 10, pp. 3295-3310
Closed Access | Times Cited: 25
Flood susceptibility evaluation through deep learning optimizer ensembles and GIS techniques
Romulus Costache, Alireza Arabameri, Iulia Costache, et al.
Journal of Environmental Management (2022) Vol. 316, pp. 115316-115316
Open Access | Times Cited: 24
A comparative study of heterogeneous and homogeneous ensemble approaches for landslide susceptibility assessment in the Djebahia region, Algeria
Zakaria Matougui, Lynda Djerbal, Ramdane Bahar
Environmental Science and Pollution Research (2023) Vol. 31, Iss. 28, pp. 40554-40580
Closed Access | Times Cited: 14
Robustness analysis of machine learning classifiers in predicting spatial gully erosion susceptibility with altered training samples
Tusar Kanti Hembram, Sunil Saha, Biswajeet Pradhan, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 794-828
Open Access | Times Cited: 25
Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models
Nibas Chandra Deb, Jayanta Kumar Basak, Sijan Karki, et al.
Journal of Agriculture and Food Research (2025) Vol. 19, pp. 101700-101700
Open Access
Prediction of main particulars of container ships using artificial intelligence algorithms
Darin Majnarić, Sandi Baressi Šegota, Ivan Lorencin, et al.
Ocean Engineering (2022) Vol. 265, pp. 112571-112571
Closed Access | Times Cited: 16
Preparing coastal erosion vulnerability index applying deep learning techniques in Odisha state of India
Badal Mohanty, Raju Sarkar, Sunil Saha
International Journal of Disaster Risk Reduction (2023) Vol. 96, pp. 103986-103986
Closed Access | Times Cited: 9
Entropy-Based Hybrid Integration of Random Forest and Support Vector Machine for Landslide Susceptibility Analysis
Amol Sharma, Chander Prakash, V. S. Manivasagam
Geomatics (2021) Vol. 1, Iss. 4, pp. 399-416
Open Access | Times Cited: 20
Prediction of drinking water requirements by applying statistical and machine learning models in growing-finishing stage of pigs
Jayanta Kumar Basak, Bhola Paudel, Shihab Ahmad Shahriar, et al.
Computers and Electronics in Agriculture (2023) Vol. 210, pp. 107934-107934
Closed Access | Times Cited: 8
Examining the drivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-making models
Rajkumar Guria, Manoranjan Mishra, Biswaranjan Baraj, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 11
Closed Access | Times Cited: 2
Advanced data mining techniques for landslide susceptibility mapping
Muhammad Bello Ibrahim, Zahiraniza Mustaffa, Abdul‐Lateef Balogun, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 2430-2461
Open Access | Times Cited: 10
Reconstructing deforestation patterns in China from 2000 to 2019
Yajuan Zhang, Lijin Zhang, Huan Wang, et al.
Ecological Modelling (2022) Vol. 465, pp. 109874-109874
Open Access | Times Cited: 7
Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting
Prince Waqas Khan, Yung-Cheol Byun
Computers, materials & continua/Computers, materials & continua (Print) (2021) Vol. 69, Iss. 2, pp. 1893-1913
Open Access | Times Cited: 8
Proposing novel ensemble approach of particle swarm optimized and machine learning algorithms for drought vulnerability mapping in Jharkhand, India
Sunil Saha, Amiya Gayen, Priyanka Gogoi, et al.
Geocarto International (2021) Vol. 37, Iss. 25, pp. 8004-8035
Closed Access | Times Cited: 7
Flood Susceptibility Mapping in Arid Region of Pakistan through ensemble Machine Learning Model.
Andaleeb Yaseen, Jianzhong Lu, Chen Xiaoling
Research Square (Research Square) (2022)
Open Access | Times Cited: 5
An Ensemble of J48 Decision Tree with AdaBoost and Bagging for Flood Susceptibility Mapping in the Sundarbans of West Bengal, India
Sujata Pal, Anik Saha, Priyanka Gogoi, et al.
Disaster risk reduction (2024), pp. 117-133
Closed Access
The Development of Deep Learning Methods to Select Passion Fruit for the Ageing Society
Akksatcha Duangsuphasin, Preecha Rungsaksangmanee, Athakorn Kengpol, et al.
(2021), pp. 282-287
Closed Access | Times Cited: 1
Design of a Decision Support System for Vegetarian Food Flavoring by Using Deep Learning for the Ageing Society
Akksatcha Duangsuphasin, Athakorn Kengpol, Rui M. Lima
(2021), pp. 54-59
Closed Access | Times Cited: 1
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