1. Implementation of statistical techniques to analyze agriculture data.
- Author
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Sivalingam, Vijayan, Vinitha, Nair, Ganesh, Athira, Puthanpurayil, Sindhu Karyankandi, Adapa, Sowmya, Pesala, Sahithi, and Chellappa, Vijayalakshmi
- Subjects
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SOIL erosion , *AGRICULTURE , *CLIMATE change , *MACHINE learning , *CROPS - Abstract
This paper mainly deals with the design and analysis of Agriculture data using Machine Learning (ML) techniques. Agriculture includes cultivating the soil and we can grow different types of crops. In India there are 28 states and 8 Union Territories. In each and every state people are farming and they are developing our agriculture in so many ways. Every state has its own farm for example: - Andhra Pradesh-Rice, Bazra, maize, ragi, pulses etc; the other name for agriculture is "Back Bone of India ". The sediment pressure is due to erosion and soil loss. Diffusion in nature occurs in the fine-grained sediments. Statistical analysis is being carried out for effective solution based on different parameters. This helps to get more information for farmers to make critical farming decisions. Researchers focused on agriculture and found an optimal option to increase production. Experimental data is analyzed and the production is optimized for agriculture such that it is more resilient to climatic change. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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