Decision Support System for predicting crop yield using fuzzy logic

Agriculture is an important sector of the Indian economy, employing a large portion of the country’s workforce and contributing significantly to the country’s gross domestic product. However the farmers are facing a lot of problems in getting a good yield due to the climate change, soil degradation, water scarcity etc and unable to choose the crop they want cultivate. To overcome this problem we are considering factors that affect the crop such as soil quality, rainfall, temperature, pH etc.. The system will take into these factors such as soil type, weather conditions, and crop variety to provide accurate yield predictions. Fuzzy logic will be used to handle the uncertainties and imprecise data associated with agricultural systems. The project will leverage machine learning algorithms and statistical models to build a robust prediction engine and evaluate its performance against traditional approaches. The system will be tested on real-world datasets to demonstrate its effectiveness in improving crop yield prediction accuracy. Ultimately, the decision support system developed in this project will help farmers optimize crop yield and improve their overall profitability while reducing the environmental impact of their operations.