Wheat Crop Yield Forecasting Using Various Regression Models
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S. Bhosale, R. Thombare, P. Dhemey, and A. Chaudhari. Crop yield prediction using data analytics and hybrid approach. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA),IEEE, pages 1–5, 2018.
B. Das, R. Sahoo, S. Pargal, G. Krishna, R. Verma, V. Chinnusamy, V. Sehgal, and V. Gupta. Comparison of different uni- and multi-variate techniques for monitoring leaf water status as an indicator of water-deficit stress in wheat through spectroscopy. Biosystems Engineering, 160:69–83, 2017. doi:10.1016/j.biosystemseng.2017.05.007.
B. Dhekale, PKS, and TPU. Weather based pre-harvest forecasting of rice at kolhapur (maharashtra). Trends Biosci, page 39–41, 2014.
U. Freie, S. Sporri, O. Stebler, and F. Holecz. Rice field mapping in sri lanka using ers sar data. Earth Observ. Q., 63:30—-35, 1999.
N. Kumar, R. Pisal, SP, Shukla, and K. Pandye. Regression technique for south gujarat. MAUSAM, 65:361–364, 2014.
R. Kumar, M. Reddy, and P. Praveen. Text classification performance analysis on machine learning. Int.J.AdvSciTechnol,
:691–697, 2019.
K. Paidipati, C. Chesneau, N. B M, K. Kumar, P. Kalpana, and C. Ku-rangi. Prediction of rice cultivation in india—support vector regression approach with various kernels for non-linear patterns. AgriEngineering, 3:182–198, 2021.
doi: 10.3390/agriengineering3020012.
K. Pramod, S. Naresh Kumar, V. Thirupathi, and C. Sandeep. Qos and security problems in 4g networks and qos mechanisms offered by 4g. International Journal of Advanced Science and Technology, 20:600–606, 2019.
P. Praveen and B. Rama. An efficient smart search using r tree on spatial data.Journal of Advanced Research in Dynamical and Control Systems, 4:1943–1949, 2019.
P. Praveen, B. Rama, and T. S. Kumar. An efficient clustering algorithm of minimum spanning tree. Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB),pages 131–135, 2017.
K. Rai, N. P. V, B. Bharti, and S. K. Pre harvest forecast models based on weather variable. Adv Biores, 4:118—-122, 2013.
R. RaviKumar, M. B. Reddy, and P. Praveen. An evaluation of feature selection algorithms in machine learning. Int J SciTechnol Res, 12:2071–2074, 2019.
M. A. Shaik, T. S. Kumar, P. Praveen, and R. Vijayaprakash. Research on multiagent experiment in clustering. International Journal of Recent Technology and Engineering (IJRTE), 8:1126–1129, 1999.
S. Tutun, M. Bataineh, M. Aladeemy, and M. Khasawneh. The Optimized Elastic Net Regression Model for Electricity Consumption Forecasting, 2016.
S. Veenadhari, B. Misra, and C. D.Singh.
Machine learning approach for forecasting crop
yield based on climatic parameters. In 2014 International Conference
on Computer Communication and In-formatics, 8:1– 5, 2014.
M. Yousefi, B. Khoshnevisan, S. Band, S. Motamedi,
M. Md Nasir, M. Arif, and R. Ahmad. Support vector regression methodology for prediction of output energy in rice production. Stochastic Environmental Research and Risk Assessment, 29, 2015. doi: 10.1007/s00477-015-1055-z
DOI: http://dx.doi.org/10.23755/rm.v46i0.1085
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