Author:
Krishna M. Vamsi,Swaroopa K.,SwarnaLatha G.,Yasaswani V.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Reference24 articles.
1. Feng P, Wang B, Li Liu D, Waters C, Xiao D, Shi L, Yu Q (2020) Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique. Agric For Meteorol 285:107922
2. Elavarasan D, Vincent PD (2020) Crop yield prediction using deep reinforcement learning model for sustainable agrarian applications. IEEE Access 8:86886–86901
3. Peng B, Guan K, Zhou W, Jiang C, Frankenberg C, Sun Y, He L, Köhler P (2020) Assessing the benefit of satellite-based solar-induced chlorophyll fluorescence in crop yield prediction. Int J Appl Earth Obs Geoinf 90:102126
4. Aghighi H, Azadbakht M, Ashourloo D, Shahrabi HS, Radiom S (2018) Machine learning regression techniques for the silage maize yield prediction using time-series images of Landsat 8 OLI. IEEE J Select Top Appl Earth Observ Remote Sens 11(12):4563–4577
5. Elavarasan D, Vincent DR, Sharma V, Zomaya AY, Srinivasan K (2018) Forecasting yield by integrating agrarian factors and machine learning models: a survey. Comput Electron Agric 155:257–282
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