International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
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Crop Yield and Crop Production Predictions using Machine Learning

  • Divya Goel (Computer Engineering Department J.C. Bose University of Science and Technology, YMCA) ;
  • Payal Gulati (Computer Engineering Department J.C. Bose University of Science and Technology, YMCA)
  • 투고 : 2023.09.05
  • 발행 : 2023.09.30
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초록

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

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참고문헌

  1. Arun Kumar, Naveen Kumar, Vishal Vats, "Efficient crop yield prediction using machine learning algorithms", IRJET Volume: 05 Issue: 06, June-2018, pp 3151-3159
  2. P.Priya, U.Muthaiah, M.Balamurugan, "Predicting yield of the crop using machine learning Algorithm", IJESRT et al., 7(4): April-2018, pp 2277-2284
  3. CH. Vishnu Vardhan chowdary, Dr.K.Venkataramana, "Tomato Crop Yield Prediction using ID3", March 2018,IJIRT Volume 4 Issue 10 pp,663-62.
  4. Vaneesbeer Singh, Abid Sarwar, Vinod Sharma. "Analysis of soil and prediction of crop yield (Rice) using Machine Learning approach", IJARCS 8 (5), May-June 2017, pp 1254-1259.
  5. R. Sujatha and P. Isakki, "A study on crop yield forecasting using classification techniques" 2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16), Kovilpatti, 2016, pp. 1-4.
  6. Y. Everingham, J. Sexton, D. Skocaj, and G. Inman-Bamber, "Accurate prediction of sugarcane yield using a random forest algorithm", Agronomy for Sustainable Development, vol. 36, no. 2, 2016.
  7. Ankalaki, S., Chandra, N., Majumdar, J, "Applying Data Mining Approach and Regression Model to Forecast Annual Yield of Major Crops in Different District of Karnataka", International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, Special Issue 2, pp.25-29, 2016. https://doi.org/10.17148/IJARCCE.2016.51205
  8. N. Gandhi, L. J. Armstrong, O. Petkar and A. K. Tripathy, "Rice crop yield prediction in India using support vector machines" 2016 13th International Joint Conference on Computer Science and Software Engineering (JCSSE), Khon Kaen, 2016, pp. 1-5.
  9. Aditya Shastry, H.A. Sanjay, E. Bhanusree, "Prediction of Crop Yield using Regression Analysis", Indian Journal of Science and Technology, Vol. 9(38), pp.1-5, 2016. https://doi.org/10.17485/ijst/2016/v9i38/91714
  10. Kushwaha, A.K., Sweta Bhattacharya, "Crop yield prediction using Agro Algorithm in Hadoop", International Journal of Computer Science and Information Technology & Security (IJCSITS), Vol. 5- No2, pp.271-274, 2015.
  11. D. Ramesh and B. Vardhan, "Analysis of crop yield prediction using data mining techniques", International Journal of Research in Engineering and Technology, vol. 4, no. 1, pp. 47-473, 2015. https://doi.org/10.15623/ijret.2015.0401071
  12. Monali Paul, Santosh K. Vishwakarma, Ashok Verma, "Analysis of Soil Behavior and Prediction of Crop Yield using Data Mining approach", 2015 International Conference on Computational Intelligence and Communication Networks.
  13. Awanit Kumar, Shiv Kumar, "Prediction of production of crops using K-Means and Fuzzy Logic", IJCSMC, 2015.
  14. Fathima, G.N., Geetha, R., "Agriculture Crop Pattern Using Data Mining Techniques", International Journal of Advanced Research in Computer Science and Engineering, Vol. 4, Issue 5, pp.781-786, 2014
  15. S. Veenadhari, B. Misra and C. Singh, "Machine learning approach for forecasting crop yield based on climatic parameters" 2014 International Conference on Computer Communication and Informatics, Coimbatore, 2014, pp. 1-5.
  16. Kaur, M., Gulati, H., Kundra, H., "Data Mining in Agriculture on Crop Price Prediction: Techniques and Applications", International Journal of Computer Applications, Vol. 99-No.12, pp.1-3, 2014 https://doi.org/10.5120/17422-8273
  17. Jun Wu, Anastasiya Olesnikova, Chi- Hwa Song, Won Don Lee (2009), "The Development and Application of Decision Tree for Agriculture Data" IITSI, pp 16-20.
  18. Georg Rus, Rudolf Kruse, Martin Schneider, and Peter Wagner. "Estimation of neural network parameters for wheat yield prediction" In Max Bramer, editor, Artificial Intelligence in Theory and Practice II, volume 276 of IFIP International Federation for Information Processing, pages 109-118. Springer, July 2008.
  19. Kiran Mai,C., Murali Krishna, I.V, an A.Venugopal Reddy, "Data Mining of Geospatial Database for Agriculture Related Application", Proceedings of Map India,New Delhi, 2006,pp 83-96.
  20. Verheyen, K., Adrianens, M. Hermy and S.Deckers (2001), "High resolution continuous soil classification using morphological soil profile descriptions" Geoderma, 101:31-48.  https://doi.org/10.1016/S0016-7061(00)00088-4
  21. https://www.hilarispublisher.com/open-access/agriculturerole-on-indian-economy-2151-6219-1000176.pdf.