Krishi: A Price Prediction System

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Naman Mishra; Chandni Agrawal; Piyush Kumar; Vijay Sehrawat; Tara Chand Verma

Krishi: A Price Prediction System

Authors: Naman Mishra, Chandni Agrawal, Piyush Kumar, Vijay Sehrawat, Tara Chand Verma

Unique Paper ID: 151698
Volume: 8
Issue: 1
PageNo: 580-583

Keywords: Arhati Crop Farmer Machine Learning MSP SARIMA Weather

Abstract:
In todayâ€™s world where price prediction systems have become an essential need and are implemented in almost all sectors including estimation of transportation costs or real estate fares, for a country where a major area of land is being used for cultivation this paper tries to understand the importance of price prediction in this field and by overcoming the obstacles and hurdles, find a suitable solution by using the technologies and researches done till date to provide a farmer-friendly solution. This work was done keeping in mind the new Indian Agriculture Acts of 2020 as the middlemen or â€œArhatisâ€ (in Hindi) were not just a product link between farmer and customers but also the economic link and were often the ones that decided the prices of crops. With their absence an efficient system is required that can predict the prices for farmers and help them decide accordingly their future ventures.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 1
PageNo: 580-583

Krishi: A Price Prediction System

Available:https://ijirt.org/article?manuscript=151698

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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