Implementation of Prediction of Crop Using SVM Algorithm

Abstract

Abstract: Crop forecasting is the process of predicting the yield or production of crops for a given period based on historical data, weather and other relevant factors. The prediction can be used to inform crop planting, harvesting and marketing decisions. Machine learning and artificial intelligence techniques are increasingly being used to improve the accuracy of crop forecasting. These techniques use algorithms to analyze large amounts of data, such as weather patterns, soil conditions, and crop history, to predict future crop yields. Crop prediction models can be used by farmers, agribusinesses, and governments to optimize crop management, reduce waste and maximize profit. Accurate crop forecasting can also help mitigate the impact of climate change on agricultural production by enabling farmers to adapt to changing weather conditions and other environmental factors.