Farmer's Guide: Crop Prediction using Random Forest Regression

• Author(s): Raunak Jasrasaria ; Samridh Gupta ; Seema Kalonia ; Anshu Khurana
• Paper ID: 1704638
• Page: 591-596
• Published Date: 19-06-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 12 June-2023

Abstract

Out of all the three sectors of the Indian Economy, the primary sector has not enjoyed the benefits of technological advancements in recent years as much as the secondary and tertiary sectors have. Unfortunately, the agricultural sector, on which more than 70% of Indian rural households depend, has been left out of this revolution. Many programs and initiatives have been launched by governing bodies to educate farmers and provide them with technical aid to maximize their harvest. However, not much emphasis has been laid on matching the supply of various crops to their respective market demands. The lack of any such policy has resulted in a surplus crop supply leading to food waste and farmers’ money. Our system will guide farmers about how much crop they should produce in a particular year so that there is minimum or no wastage of crops.

Keywords

Random Forest regression, crop production, government data for crop production

Citations

IRE Journals:
Raunak Jasrasaria , Samridh Gupta , Seema Kalonia , Anshu Khurana "Farmer's Guide: Crop Prediction using Random Forest Regression" Iconic Research And Engineering Journals Volume 6 Issue 12 2023 Page 591-596

IEEE:
Raunak Jasrasaria , Samridh Gupta , Seema Kalonia , Anshu Khurana "Farmer's Guide: Crop Prediction using Random Forest Regression" Iconic Research And Engineering Journals, 6(12)