Loading

Yield Forecasting for Indian Crops with Ensemble Model
Lokesh C K1, Senthil S2 

1Lokesh C K, School of CSA, REVA University, Bengaluru, India.
2Dr. S. Senthil, School of CSA, REVA University, Bengaluru, India.

Manuscript received on 03 March 2019 | Revised Manuscript received on 08 March 2019 | Manuscript published on 30 July 2019 | PP: 6404-6407 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2220078219/19©BEIESP | DOI: 10.35940/ijrte.B2220.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In fast developing economies like India, there is fast depletion of agricultural lands and many people migrate to cities leaving agriculture. In these conditions effective yield prediction of crops is a must for planning food policies and securing food for the people. Import only at time of huge price rise is not a solution and predictive import of crops based on yield predicted is a way to keep food inflation under control. Towards this end, an Ensemble model for prediction of yield of India Rabbi Crops is proposed in this work. An Ensemble machine learning model is built based on past histories and macro climatic and monsoon conditions to forecast the yield for crops in work.
Index Terms: Ensemble Model, Machine Learning, ARIMA-LR, Bayes net. Kmeans-Neural Network

Scope of the Article: Machine Learning