A Fuzzy Logic Approach for Best Crop Selection

Abstract

The agricultural sector faces challenges in selecting suitable crop due to complexity and uncertainty of environmental factors. By using fuzzy technique, we enhance the accuracy in crop selection compare to traditional statistical method. Statistical approaches often rely on precise numerical threshold while, fuzzy logic excels in capturing the vagueness associated with linguistic terms by standard intersection. Considering all parameters like temperature, soil compatibility, water required, production cost and profit enabling farmers to make context aware approach for crop selection. First calculating the gradation of variables and taking minimum intersection of all fuzzy sets from all parameters and then preferring the crop with maximum index. Finite accuracy got by fuzzy logic can be trusted more than statistical method.