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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:

Prediction of arabica coffee production using artificial neural network and multiple linear regression techniques
Yotsaphat Kittichotsatsawat, Nakorn Tippayawong, Korrakot Yaibuathet Tippayawong
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 21

Showing 21 citing articles:

Innovative solar distillation system with prismatic absorber basin: Experimental analysis and LSTM machine learning modeling coupled with great wall construction algorithm
Ammar H. Elsheikh, Mohamed E. Zayed, Ali M. Aboghazala, et al.
Process Safety and Environmental Protection (2024) Vol. 186, pp. 1120-1133
Closed Access | Times Cited: 41
Efficiency of Fungicide Application an Using an Unmanned Aerial Vehicle and Pneumatic Sprayer for Control of Hemileia vastatrix and Cercospora coffeicola in Mountain Coffee Crops
Edney Leandro da Vitória, César Abel Krohling, Felipe Ruela Pereira Borges, et al.
Agronomy (2023) Vol. 13, Iss. 2, pp. 340-340
Open Access | Times Cited: 18
A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness
Xin Zhang, Zhi‐Kang Lin, Song Gu
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Maize Yield Prediction using Artificial Neural Networks based on a Trial Network Dataset
Paulo Vitor Duarte de Souza, Leiliane Pereira de Rezende, Aildson Pereira Duarte, et al.
Engineering Technology & Applied Science Research (2023) Vol. 13, Iss. 2, pp. 10338-10346
Open Access | Times Cited: 10
Predicting Healthcare Mutual Fund Performance Using Deep Learning and Linear Regression
Anuwat Boonprasope, Korrakot Yaibuathet Tippayawong
International Journal of Financial Studies (2024) Vol. 12, Iss. 1, pp. 23-23
Open Access | Times Cited: 2
Statistical and machine learning models for location-specific crop yield prediction using weather indices
S. Ajith, Manoj Kanti Debnath, R Karthik
International Journal of Biometeorology (2024)
Closed Access | Times Cited: 2
A Systematic Review on Crop Yield Prediction Using Machine Learning
Moon Halder, Ayon Datta, K. Siam, et al.
Lecture notes in networks and systems (2023), pp. 658-667
Closed Access | Times Cited: 6
Impacts of meteorological variables and machine learning algorithms on rice yield prediction in Korea
Subin Ha, Yong-Tak Kim, Eun‐Soon Im, et al.
International Journal of Biometeorology (2023) Vol. 67, Iss. 11, pp. 1825-1838
Closed Access | Times Cited: 5
Estimation of Coffee Plantation Production Using Segmentation and Deep Learning Techniques
Jesús Alexander Montalvan Ramos, Lili Yanina Huaman Guerrero
(2024)
Open Access | Times Cited: 1
A novel framework for the evaluation of coastal protection schemes through integration of numerical modelling and artificial intelligence into the Sand Engine App
Pavitra Kumar, Nicoletta Leonardi
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 4
Crop Insurance Premium Recommendation System Using Artificial Intelligence Techniques
M. Prakash, P. Saravanan
International Journal of Professional Business Review (2023) Vol. 8, Iss. 4, pp. e01270-e01270
Open Access | Times Cited: 2
Application of statistical and machine learning models in combination with stepwise regression for predicting rapeseed-mustard yield in Northern districts of West Bengal
S. Ajith, Manoj Kanti Debnath, Deb Sankar Gupta, et al.
International Journal of Statistics and Applied Mathematics (2023) Vol. 8, Iss. 3, pp. 141-149
Open Access | Times Cited: 2
A review on features and methods of potential fishing zone
Norsuzila Ya’acob, Nik Nur Shaadah Nik Dzulkefli, Mohd Azri Abdul Aziz, et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) Vol. 14, Iss. 3, pp. 2508-2508
Open Access
Multi-objective Optimization of Pelletized Coffee Silver Skin in Flue Gas Torrefaction for Producing Premium Solid Fuel
Kanit Manatura, Supaporn Klinkesorn, Benjapon Chalermsinsuwan, et al.
BioEnergy Research (2024) Vol. 18, Iss. 1
Closed Access
Correlation and Regression Analyses of Disease and Agronomic Traits of Ethiopian Mustard (Brassica Carinata A. Braun.) Genotypes
Birhanu Mengistu, Alemu Gemeda
American Journal of Life Sciences (2024) Vol. 12, Iss. 6, pp. 113-120
Open Access
Forecasting arabica coffee yields by auto-regressive integrated moving average and machine learning approaches
Yotsaphat Kittichotsatsawat, Anuwat Boonprasope, Erwin Rauch, et al.
AIMS Agriculture and Food (2023) Vol. 8, Iss. 4, pp. 1052-1070
Open Access | Times Cited: 1
A Compendium Probabilistic Prospective for Predicting Coffee Crop Yield Based on Agronomical Factors
C S Santhosh, K K Umesh
(2022), pp. 1-8
Closed Access | Times Cited: 1
Modelling coffee yield in Dak Lak province using machine learning algorithms
Bien Phan Hong Yen, Đào Nguyên Khôi
IOP Conference Series Earth and Environmental Science (2023) Vol. 1170, Iss. 1, pp. 012004-012004
Open Access
Effect of Rainfall and Technification on Arabica Coffee Productivity in Minas Gerais
Flavio Vanoni de Carvalho, Marcelo de Carvalho Alves, Luiz Gonsaga de Carvalho
Theoretical and Applied Engineering (2023) Vol. 7, Iss. 4
Open Access
Roasted coffee beans characterization through optoelectronic color sensing
Sebastian-Camilo Vanegas-Ayala, Daniel-David Leal-Lara, Julio Barón Velándia
Coffee Science (2023) Vol. 18, pp. 1-7
Open Access
Tracking and Predicting Productions in Agricultural Processes: Applications and Experiences
Patrizia Vizza, Giuseppe Timpano, Francesco Vescio, et al.
2021 IEEE International Conference on Big Data (Big Data) (2023), pp. 3524-3529
Closed Access
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