Modelling studies on energy use pattern in agriculture: A mini review

Abstract

To meet out the demand of food production on decreasing arable land energy use of the crop is more important to attain self-sufficient in agriculture. Energy use efficiency and energy productivity for cereals, millet, fodder, oilseeds, commercial crop, sugar crop, plantation, vegetable and fruit shows energy utilized by crops at various stages differ by crop cultivation practice. Evolution of mathematical model to machine learning is rapidly increases over the decades. In machine learning, evolution of neural network algorithm is rapid than any other models. Mostly for energy auditing supervised machine learning models were used. Artificial Neural Network is most accurate predicted model and Data Envelopment Analysis (DEA) is most used model for energy auditing. Model performance is also measured by coefficient of determination, root mean square error. Even though DEA is used frequently for energy auditing it as its own drawbacks. At future prediction of data machine learning will get lead than mathematical\econometrical models.