Return on investment framework for profitable crop recommendation system by using optimized multilayer perceptron regressor

Surekha Janrao, Deven Shah


Return on investment (ROI) plays very important role as a financial dimension in the agriculture sector. Many government agencies like Indian space research organization (ISRO), Indian council of agricultural research (ICAR), and Nitiayog are working on different agriculture projects to improve profitability and sustainability. This paper presents ROI framework to recommend more profitable crop to the farmers as per the current market price and demand which is missing in the existing crop recommendation system. Crop price prediction (CPP) and crop yield prediction (CYP) system are integrated in the ROI framework to predict more demandable crop to yield. This framework is designed by applying data analysis to provide regression statistics which further helps for model selection and improve the performance also. Optimized multilayer perceptron regressor algorithm has been evaluated through experimental results and it has been observed that it gives better performance as compared to other existing regression techniques.


machine learning; multilayer perceptron; recommendation system; regression; return on investment;

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