Smart Farming System using ML

Authors: Sani Pandey, Shivam Singh, Rajnish Kr. Thakur, Madhu Verma

Country: India

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Abstract: It is widely recognized that agriculture serves as the fundamental pillar of India's economy. This research paper delves into the realm of yield predictions, encompassing the vast array of crops cultivated throughout the nation. What sets this script apart is its unique ability to anticipate agricultural production for any chosen year, employing easily comprehensible variables such as state, district, season, and area. To achieve this feat, the article draws upon an assortment of regression techniques, including the notable Kernel Ridge, Lasso, and ENet algorithms. These sophisticated statistical methods form the bedrock of the paper's prediction methodology, enabling accurate estimations of crop output.

Keywords: Crop Yield Prediction, Kernel Ridge, ENet, Stacked Regression, Machine Learning (ML)

Paper Id: 230150

Published On: 2023-05-23

Published In: Volume 11, Issue 3, May-June 2023

Cite This: Smart Farming System using ML - Sani Pandey, Shivam Singh, Rajnish Kr. Thakur, Madhu Verma - IJIRMPS Volume 11, Issue 3, May-June 2023.

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