Recommending and Predicting Crop Yield using Smart Machine Learning Algorithm (SMLA)

Agriculture is always needed by every human and responsible for the economic growth of a country. Developed countries likewise America, Japan, China are leading and making other countries too dependent on their technologies. But developing countries like India are expecting a lot of new technologica...

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Published in:Current Agriculture Research Journal 2023-09, Vol.11 (2), p.686-694
Main Authors: Sutha, K., Indumathi, N., Uma Shankari, S.
Format: Article
Language:English
Subjects:
Accuracy
Agricultural production
Agriculture
Algorithms
Automation
Classification
Crop diseases
Crop yield
Crops
Decision trees
Developed countries
Developing countries
Economic development
Economic growth
Electronic commerce
Farmers
Fertilizers
Innovations
LDCs
Learning algorithms
Machine learning
Nutrients
Outdoor air quality
Pesticides
Rain
Regression analysis
Technological change
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Indumathi, N.
Uma Shankari, S.
description Agriculture is always needed by every human and responsible for the economic growth of a country. Developed countries likewise America, Japan, China are leading and making other countries too dependent on their technologies. But developing countries like India are expecting a lot of new technological innovations in the field of agriculture. Innovations may be in the form of smart machines, automation systems, sensor-based instruments, etc. and an advantage for society. In this paper, we have proposed Recommending and Predicting Crop Yield using Smart Machine Learning Algorithm (SMLA). The proposed algorithm namely SMLA is compared with other traditional algorithms to predict crop yield. In comparison to other algorithms the proposed algorithm works efficiently and produces 95% accuracy.
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subjects Accuracy
Agricultural production
Agriculture
Algorithms
Automation
Classification
Crop diseases
Crop yield
Crops
Decision trees
Developed countries
Developing countries
Economic development
Economic growth
Electronic commerce
Farmers
Fertilizers
Innovations
LDCs
Learning algorithms
Machine learning
Nutrients
Outdoor air quality
Pesticides
Rain
Regression analysis
Technological change
title Recommending and Predicting Crop Yield using Smart Machine Learning Algorithm (SMLA)
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