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01-Applied Mathematics & Information Sciences
An International Journal


Volumes > Volume 17 > No. 5


Revitalizing Indian Agriculture with Machine Learning - based Crop Yield Prediction for Promising Future

PP: 1140-1149
D Anitha, V Nivasan, P Navinkumar, A K Pradhapdurai,
Farmer's knowledge and hands on expertise crop cultivation was undertaken earlier and now. Even though farmers has well knowledge in cultivation climate plays major role in yield which may increases or decreases the yield this factor is not in farmer hands. As a result, new person for farming are unable to select the appropriate crop/s based on soil and environmental parameters, and the process of manually predicting the appropriate crop/s of land has frequently failed. Machine learning is used to predict best crop to grow in a particular land based on the parameters like Soil minerals, moisture and temperature. By analyzing these parameters optimal crop to grow in particular land will be predicted accurately. Initially dataset preprocessing is done which removes irrelevant data and required field has been extracted through feature extraction. Next classification step is implemented which plays important role in prediction. In our proposed method SVM and Linear Regression is implemented which achieves maximum accuracy. Therefore by giving land mineral content like potassium, nitrogen and PH value, temperature and moisture as input it will predict optimal crop to grow with its yield. Apart from entered input soil mineral values and optimal crop to grow are also predicted as suggestion in order to improve performance of the system. Hence our project will be useful for farmers to predict accurate crop for production. Compared to existing methods our proposed methods achieve better results.

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