IJRTI
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 8

Issue Published : 88

Article Submitted : 8769

Article Published : 4490

Total Authors : 11663

Total Reviewer : 551

Total Countries : 86

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Crop Price Prediction
Authors Name: Dr. G. Dhanabalan , N. Roshini , P. Ganesh Sai Kumar , P. Venkatesh
Download E-Certificate: Download
Author Reg. ID:
IJRTI_186196
Published Paper Id: IJRTI2304198
Published In: Volume 8 Issue 4, April-2023
DOI:
Abstract: This project target is largely concentrated on farming. In farming, farmers play the most important part. When the price falls after the crop, farmers face immense losses. A country’s GDP(Gross Domestic Product ) is affected by the price oscillations of agrarian products. Crop price estimation and evaluation are done to take an intelligent decision before cultivating a specific type of crop. Predicting the price of a crop will help in taking better opinions which results in minimizing the loss and managing the threat of price oscillations. Price prediction, currently, has come to a veritably important agrarian problem that’s to be answered only grounded on the available data. The end of this project is to forecast the crop price for the coming gyration. This work is grounded on chancing suitable data models that help in achieving high delicacy and generality for price prediction. For working on this problem, different Data Mining ways were estimated on different data sets. This work presents a system that uses data analytics ways in order to prognosticate the price of the crop. The proposed system will apply machine literacy algorithms and prognosticate the price of the crop grounded on the Yield and price of the former time’s crops. This provides a planter with a perception of the unborn price of the crop that he is going to gather. In this project, we predicted the price of different crops by assaying the former prices of different crops. We used the Random Forest and Linear Regression(Supervised machine literacy algorithms) to dissect the former data and prognosticate the price for the rearmost data and estimate the price of the crop.
Keywords: Price Prediction, Random Forest, Linear Regression, Crop Price, Regression, Forecasting, Machine Learning.
Cite Article: "Crop Price Prediction", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1205 - 1208, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304198.pdf
Downloads: 000130
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2304198
Registration ID:186196
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1205 - 1208
Country: Thiruvallur , Tamil Nadu, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304198
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304198
Share Article:

Share Facebook Twitter Google+ Pinterest LinkedIn Email Tumblr WhatsApp Google Gmail

Click Here to Download This Article

Article Preview
Click Here to Download This Article
Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Join RMS/Earn 300
IJRTI

Indexing Partner
Copyright © 2023 - All Rights Reserved - IJRTI