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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:

Crop yield forecasting using data mining
Pallavi Kamath, Pallavi Patil, S Shrilatha, et al.
Global Transitions Proceedings (2021) Vol. 2, Iss. 2, pp. 402-407
Open Access | Times Cited: 74

Showing 26-50 of 74 citing articles:

Models for feature selection and efficient crop yield prediction in the groundnut production
Kuruguntu Mohan Krithika, N. Maheswari, Manickam Sivagami
Research in Agricultural Engineering (2022) Vol. 68, Iss. 3, pp. 131-141
Open Access | Times Cited: 7
Optimized Farming: Crop Recommendation System Using Predictive Analytics
Monica R. Mundada
International journal of intelligent engineering and systems (2023) Vol. 16, Iss. 3, pp. 579-592
Open Access | Times Cited: 3
Crop Yield Forecasting using Machine Learning Techniques - A Systematic Literature Review
Dmak Dissanayake, R. M. K. T. Rathnayake, L. L. Gihan Chathuranga
KDU Journal of Multidisciplinary Studies (2023) Vol. 5, Iss. 1, pp. 54-65
Open Access | Times Cited: 3
A Global Forecasting Approach to Large-Scale Crop Production Prediction with Time Series Transformers
Sebastian C. Ibañez, Christopher Monterola
(2023)
Open Access | Times Cited: 3
Efficient Crop Yield Prediction of Kharif Crop using Deep Neural Network
Preeti Saini, Bharti Nagpal
2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) (2022), pp. 376-380
Closed Access | Times Cited: 5
A review of crop yield prediction based on Indian agriculture sector using machine learning
Deepthi Thomas
AIP conference proceedings (2023) Vol. 2773, pp. 020002-020002
Closed Access | Times Cited: 2
A Comparative Analysis of Regression Models for Crop Yield Prediction Based on Rainfall Data: Experimental Study and Future Perspective
Priyanshu Tiwari, Ronit Raj, Himansu Das, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 2
RANC-CROP Recommendation Attributed to Soil Nutrients and Stock Analysis Using Machine Learning
Jesline Daniel, R. Shyamala, R. Pugalenthi, et al.
IETE Journal of Research (2022) Vol. 69, Iss. 11, pp. 8077-8089
Closed Access | Times Cited: 4
Machine Learning approaches for Crop Yield Prediction: A Review
Malika Kulyal, Parul Saxena
2020 5th International Conference on Computing, Communication and Security (ICCCS) (2022), pp. 1-7
Closed Access | Times Cited: 4
A Prognostic Reasoning Model for Improving Areacanut Crop Productivity using Data Analytics Approach
Permanki Guthu Rithesh Pakkala, Bellipady Shamantha
(2022), pp. 1-6
Closed Access | Times Cited: 3
Crop Yield Prediction for Cereals using Machine Learning
Shweta Koparde, Akanksha Behare, Simran Kasare, et al.
Soft Computing Research Society eBooks (2024), pp. 407-418
Open Access
ML Techniques for Crop Demand Prediction- A Study
Pachila Shyamala, K. Deepa, S. Sangeetha
(2024), pp. 1-5
Closed Access
Forecasting Agricultural Crop Profitability and Yield in India
Astha Tripathi
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 2, pp. 308-315
Open Access
Revolutionizing of Crop Management Using a Smart Approach with AI Technology
JASHWANTH REDDY
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) Vol. 08, Iss. 03, pp. 1-5
Open Access
Crop Yield Prediction Using Machine Learning Techniques Based on Soil and Environment Traits – A Survey
G. Mariammal, S. Sridevi
(2024), pp. 1-6
Closed Access
Improved top-down attention phasmatodea population spiking neural network based multi crop recommendation framework
R Chetan, D. V. Ashoka, Ajay Prakash B
Multimedia Tools and Applications (2024)
Closed Access
Survey on Crop Price Prediction and Recommendation Using Machine Learning and Weather Forecasting
Sumit Done
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 5, pp. 5466-5470
Open Access
Image processing and impact analyses of terminal heat stress on yield of lentil
Hena Gain, Ruturaj Nivas Patil, Konduri Malik, et al.
3 Biotech (2024) Vol. 14, Iss. 8
Closed Access
Design of Web Based Recommendation System for Farmers using Machine Learning
Amritya Mewar, Kartik Riyal, Rishi Vyas, et al.
(2024), pp. 1-6
Closed Access
Data Analytics in Ensemble Learning for Effective Crop Yield Prediction
Deeksha Tripathi, Saroj Kumar Biswas, Barnana Baruah
Engineering Research Express (2024) Vol. 6, Iss. 3, pp. 035237-035237
Closed Access
Fertilizer type and quantity recommendation to increase oilseed crops yield prediction with inorganic fertilizers using machine learning algorithms
C. Mithra, A. Suhasini
Ecology Environment and Conservation (2023) Vol. 29, pp. 358-372
Open Access | Times Cited: 1
Comparison of Machine Learning Techniques to Estimate Increase in Crop Productivity
Sandhya Umrao, Sanjay Kumar, Harsha Gupta, et al.
(2023), pp. 626-631
Closed Access | Times Cited: 1
A Review of the Internet of Things and Deep Learning in Agriculture: A Smart Agriculture Prespective
Azeem Ayaz Mirani, Rozina Chohan, Saima Siraj, et al.
Journal of Hunan University Natural Sciences (2023) Vol. 50, Iss. 10
Open Access | Times Cited: 1
Selection and Justification of the Use of Various Types of Solar Panels to Ensure Reliable Power Supply to the Key Consumers of the Mineral Resource Complex Enterprises
R Yu Zimin, Semen D. Palmin
(2023), pp. 191-194
Closed Access | Times Cited: 1
Comparative Analysis of Deep Semantic Segmentation Architectures for Disease Identification in Turmeric Crops
C Rajasekaran, K. Raguvaran, K B Javanthi
TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) (2022), pp. 1-5
Closed Access | Times Cited: 2

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