• S.Gokila
• S.Omprakash

The perfect knowledge of yield before harvest has been a wish puzzling human being since the beginning of agriculture because seasonal forecast of crop yield plays a critical role in decision making for different stakeholders from farmers to policy makers to governments for food security, to commodities traders. Different methods have been used to forecast yield with different levels of granularity, accuracy and timing. Yield forecast are mainly based on field surveys, statistical regressions between historical yield and in-season variables, crop simulation models, or on integration between statistical modeling with dynamic process-based crop simulation models. The proposed approach use the firefly optimization (FFO) for feature selection algorithm and the Random Forest (RF) technique in predicting the crop yield prediction based on Seasonal climate forecasts. The performance of the proposed approach is evaluated using the implementation result.

Crop yield prediction, Accuracy, Climate forecast, Firefly algorithm, Random forest

"A NOVEL APPROACH IN CROP YIELD PREDICTION BASED ON SEASONAL CLIMATE FORECASTS USING FFO_RF ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.397-402, May-2019, Available :http://www.jetir.org/papers/JETIR1905770.pdf

"A NOVEL APPROACH IN CROP YIELD PREDICTION BASED ON SEASONAL CLIMATE FORECASTS USING FFO_RF ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp397-402, May-2019, Available at : http://www.jetir.org/papers/JETIR1905770.pdf