Open AccessAmalgamation of Machine Learning Algorithms for Crop Yield Prediction
Author(s) -
Dipesh Kumar,
K. Mohan Kumar
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.e3004.049620
Subject(s) - artificial neural network , machine learning , agriculture , yield (engineering) , productivity , crop yield , computer science , artificial intelligence , population , algorithm , regression , linear regression , regression analysis , work (physics) , agricultural engineering , mathematics , engineering , statistics , geography , economics , agronomy , economic growth , materials science , demography , archaeology , sociology , metallurgy , biology , mechanical engineering
Agriculture is India’s prime occupation. In Indian economy agriculture plays a major role by means of providing more employment opportunities for the people. In order to provide food to the huge population of India, agriculture sector needs to maximize its crop productivity. This research work presents an approach which uses different Machine learning (ML) techniques by considering the various parameters of cultivated crop to predict the best yield. Further in this Multiple Linear Regression (MLR) technique and artificial neural networks (ANN) are used to make a brief analysis for the prediction crop yield. With the above idea a new model was created, and from this numerical results were obtained. The accuracy and efficiency of the method has been explored and results from the artificial neural network and regression methods were obtained and compared.