Vegetable Yield Prediction: A Review and Experimental Evaluation of Algorithms

Author:

Banerjee Tumpa,Bagchi BikramadittyaORCID

Publisher

Springer Nature Singapore

Reference28 articles.

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3. Brdar S, Culibrk D, Marinkovic B, Crnobarac J, Crnojevic V (2011) Support vector machines with features contribution analysis for agricultural yield prediction. In: second international workshop on sensing technologies in agriculture, forestry and environment (EcoSense 2011). Belgrade, Serbia, pp 43–47

4. Dang C, Liu Y, Yue H, Qian J, Zhu R (2020) Autumn crop yield prediction using data-driven approaches: support vector machines, random forest, and deep neural network methods. Can J Remote Sens 47(2):162–181 October

5. Das P, Jha G, Lama A, Parsad R, Mishra D (2020) Empirical mode decomposition based support vector regression for agricultural price forecasting. J Extension Educ 56(12):7–12

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