Uncertainty and Decision-Making in Crop Economics Using Fuzzy Hypersoft Set with MULTIMOORA Method and Machine Learning

In the agricultural industry, crop production economics and uncertainty are closely related. Due to variables including shifting market pricing, rising input costs, and unexpected weather patterns, farmers confront several economic difficulties. Their decision-making processes, resource allocation, and overall profitability may all be greatly impacted by these uncertainties. Farmers frequently use risk management techniques to handle these complications, including crop diversification, insurance, and the adoption of cutting-edge technology. This paper aims to provide the decision-making method for the farmers to increase its crop production and profitability using its resources. To address the issue of this decision-making, a fuzzy hypersoft set has been used with MCDM technique known as MULTIMOORA and a machine learning Random Forest model. Since the suggested strategies are used in case studies when there are several attributes, more bifurcations, and multiple decision-makers. Farmers may more successfully traverse the problems they encounter, guaranteeing sustainable livelihoods, food security, and a healthy agricultural sector for the future, by comprehending and effectively managing economic risks and adopting mathematical decision-making techniques.