학술논문

InteliCrop: An Ensemble Model to Predict Crop using Machine Learning Algorithms
Document Type
Conference
Source
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Advances in Computing, Communication and Applied Informatics (ACCAI), 2022 International Conference on. :1-6 Jan, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Machine learning algorithms
Crops
Production
Predictive models
Soil
Prediction algorithms
Agriculture
Random Forest
Gradient Boosting
Logistic Regression
Ensembled model
Machine Learning and Agriculture
Language
Abstract
The agricultural sector is the prime occupation of India. Researchers are developed various scientific technology in the agriculture field for better yield. In this paper, we try to form an ensemble model using various machine learning algorithms for better rice production. Crop production prediction utilizing AI Strategies aims to deliver improved outcomes, but the ensemble model provides better predictive results compared to the individual algorithm. we tried to use a combination of symmetric machine learning algorithms to form an ensemble model for better prediction. Here symmetric algorithms such as random forest, Gradient Boosting, and Logistic Regression are individually used for the prediction of the yield of rice. While combining all the aforesaid algorithms to form an ensemble model of ers a better result (99.54%).