Crop Yield Prediction Using Naïve Bayes Algorithm
DOI:
https://doi.org//10.32628/CSEIT228338Keywords:
KNN, Naïve Bayes,Crop predictionAbstract
Agriculture is that the backbone of India and it plays important role in economy.It Is source of production for about 58 per cent of India’s population in step with government of the day’s estimates, States’s food production was about 291.95 MT in 2019-20; for 2020-21, the govt. had set the target up to 298.3 MT, which was two per cent more from the previous year’s output.Food production must double by 2050 to match the country’s population and income growth. the small and marginal farmers, therefore, have a big role within the country’s food security and meeting the SDG goals.Nearly 14 per cent of the population (189.2 million) continues to be undernourished in India, in line with State of Food Security and Nutrition within the planet, 2020 report. the planet Hunger Index 2020 placed India at the 94th position among 107 countries. Achieving ‘zero hunger’ by 2030 is also a humungous challenge, and needs an integrated and multi-dimensional approach for overall sustainable agriculture and food systems within the country.
References
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- Crop Prediction and Disease Detection .International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 — Nov 2019.
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- Balamurugan have implemented crop yield prediction by using only the random forest classi- fier. Various features like rainfall, temperature and season were taken into account to predict the crop yield. Other machine learning algorithms were not applied to the datasets. With the absence of other algorithms, comparison and quantification were missing thus unable to provide algorithm.
- Aruvansh Nigam, Saksham Garg, Archit Agrawal conducted experiments on Indian govern- ment dataset and its been established that Random Forest machine learning algorithm gives the best yield prediction accuracy. Sequential model thats Simple RNN works for rainfall prediction while LSTM is good for temperature . The paper puts several factors like rainfall, temperature, season, area etc. together for yield prediction. Results shows that Random Forest is best classier algorithm when all parameters are combined.
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