FARM-PRODUCTS PRICE PREDICTION USING MACHINE LEARNING

Registration ID: IJNRD_185530

Published ID: IJNRD2301019

DOI: Click Here to Get

K. Chanikya , A. Rakesh , D. Anusha

FARM-PRODUCTS PRICE PREDICTION USING MACHINE LEARNING

India is an agriculturally based nation, and farmers give their entire lives to the country's economy. They encounter serious issues when the crop is not worth the price and when they are ignorant about the marketing price for the crop or commodity in question in a given cluster. Farmers currently suffer significant losses as a result of price volatility brought on by climatic change and other price-influencing factors. From the standpoint of the agricultural industry, the current stage of demand for a crop or Agri-product is reflected in its market price. In order to adapt the production schedule and maximize profit, it is crucial for Agri management to simultaneously monitor and estimate market prices. Accurate crop price forecasting is crucial for crop production control. Such a forecast will assist related industries in planning their supply chain strategies. Generally speaking, farmers can boost their profit and avoid severe loss by using this application, which provides them with a forecast in advance. which ultimately boosts the economy of the nation. Therefore, the goal of this project is to create an application that can calculate the price of agricultural products and assist farmers in anticipating the price of a given commodity. This is possible with the aid of machine learning algorithms, and it primarily relies on the discovery of pertinent data models that aid in reaching high accuracy and generality for price prediction.

Published Paper   E-Certificate

K. Chanikya, A. Rakesh, & D. Anusha (January-2023). FARM-PRODUCTS PRICE PREDICTION USING MACHINE LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(1), a136-a158. https://ijnrd.org/papers/IJNRD2301019.pdf

Volume 8 Issue 1, January-2023

Pages : a136-a158

Paper Reg. ID: IJNRD_185530

Published Paper Id: IJNRD2301019

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Research Area: Engineering

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