Crop Recommender System Using Machine Learning Approach
| Autor: | Anmol Anmol, Kumar Shaurya, Shilpa Mangesh Pande, Karuna Rohilla, B. R Aishwarya, P. Ramesh |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
business.industry Computer science Yield (finance) Crop yield 04 agricultural and veterinary sciences Recommender system Machine learning computer.software_genre 01 natural sciences Gross domestic product Random forest Support vector machine Agriculture 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Artificial intelligence business computer Hectare 0105 earth and related environmental sciences |
| Zdroj: | 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). |
| DOI: | 10.1109/iccmc51019.2021.9418351 |
| Popis: | Agriculture and its allied sectors are undoubtedly the largest providers of livelihoods in rural India. The agriculture sector is also a significant contributor factor to the country’s Gross Domestic Product (GDP). Blessing to the country is the overwhelming size of the agricultural sector. However, regrettable is the yield per hectare of crops in comparison to international standards. This is one of the possible causes for a higher suicide rate among marginal farmers in India. This paper proposes a viable and user-friendly yield prediction system for the farmers. The proposed system provides connectivity to farmers via a mobile application. GPS helps to identify the user location. The user provides the area & soil type as input. Machine learning algorithms allow choosing the most profitable crop list or predicting the crop yield for a user-selected crop. To predict the crop yield, selected Machine Learning algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), Multivariate Linear Regression (MLR), and K-Nearest Neighbour (KNN) are used. Among them, the Random Forest showed the best results with 95% accuracy. Additionally, the system also suggests the best time to use the fertilizers to boost up the yield. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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