An Efficient Crop Yield Prediction for Agriculture - Jahnavi.M, K., SatwikI, Sravani.N and Sandeep.Y (International Journal of Advanced Science and Technology, 2020)
Agriculture acknowledges an essential movement in the improvement of the national economy. It hand-off on air and other natural perspectives. A section of the parts on which agriculture is poor are Soil, atmosphere, flooding, waste products, temperature, precipitation, crops, bug showers and herb. The gather yield is subject to these sections and in this manner hard to anticipate. To know the status of yield creation, in this work we perform illuminating assessment on rural data utilizing differing AI techniques. Gather yield checks join reviewing crop yields from accessible recorded data, for example, precipitation data, soil data, and striking harvest yields. This longing will assist ranchers with envisioning crop yield before creating. Here we are using three datasets like as earth dataset, precipitation dataset, and creation dataset of Andhra pradesh state, by then we structure an accumulated instructive records and on this dataset we utilize random forest calculation to get the bona fide contemplated yield and the exactness of methodology. in addition, the utilization of the calculations is finished utilizing python programming and spyder contraption. The presentation of calculation is indicated utilizing mean without a doubt error, cross support and exactness and it is discovered that random forest is giving precision of 99% with incredibly less mean square error (MSE).