Krishi: A Price Prediction System

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Krishi: A Price Prediction System
Author(s):
Naman Mishra, Chandni Agrawal, Piyush Kumar, Vijay Sehrawat, Tara Chand Verma
Keywords:
Arhati, Crop, Farmer, Machine Learning, MSP, SARIMA, Weather
Abstract
In today’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 “Arhatis” (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.
Article Details
Unique Paper ID: 151698 Publication Volume & Issue: Volume 8, Issue 1 Page(s): 580 - 583
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