Open AccessA Crop Recommendation System to Improve Crop Productivity using Ensemble Technique
Author(s) -
Shikha Ujjainia,
Pratima Gautam,
S. Veenadhari
Publication year - 2021
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d8507.0210421
Subject(s) - productivity , production (economics) , agricultural engineering , agriculture , agricultural productivity , computer science , machine learning , transformation (genetics) , crop production , ensemble learning , industrial engineering , artificial intelligence , engineering , economics , ecology , biochemistry , chemistry , macroeconomics , gene , biology
An integration of technology with crop yielding prediction methodology brought a major transformation in the production level globally. Machine learning concept has boosted that technology in such a manner that has further optimized the situation of farmer and agricultural industry. The combination of different types of algorithm enhances the competency of technological device to a level where the prediction becomes very effective and least deviation can be expected from the agricultural industry in the production level. The research of machine learning states about the integration of three types of models which is usually followed separately in programming the device. The study has proved the intervention of Information technology in the agricultural industry via different functions. An effective prediction by using the ensemble algorithm makes the agricultural industry competent enough to maintain the expected amount of production of crop.