The Crop Price Prediction Using Machine Learning: Preliminary Stage

The objective of our research is mostly concerned with agriculture. Farmers are the key players in agriculture. Knowing how much a crop will cost will enable you to make smarter judgments, which will reduce the losses and lower the risk of price changes. An ML model that forecasts agricultural...

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Bibliographic Details
Main Authors: Ramya, T.K., Shreedhara N, Hegde, Mohd Norshahriel, Abd Rani
Format: Article
Language:English
Published: INTI International University 2024
Subjects:
Online Access:http://eprints.intimal.edu.my/1925/
http://eprints.intimal.edu.my/1925/1/jods2024_09.pdf
Description
Summary:The objective of our research is mostly concerned with agriculture. Farmers are the key players in agriculture. Knowing how much a crop will cost will enable you to make smarter judgments, which will reduce the losses and lower the risk of price changes. An ML model that forecasts agricultural prices in advance while accurately analyzing the crop may be able to solve this issue. A predictive system, a statistical method combining machine learning and data collecting, is used in many applications, including healthcare, retail, education, and government sectors. Its usage in the agriculture sector has comparable relevance. The back-end predictive model for this project is created utilizing machine learning algorithms. The steps involved in creating a predictive model are data collecting, data cleaning, data mining, and validation. The goal is to give farmers an intuitive user interface, and this model should correctly forecast crop market value given the real-time variables provided.