 |
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)
|
Issue: October 2025
Volume 10 | Issue 10
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 113
Article Submitted : 18365
Article Published : 7814
Total Authors : 20641
Total Reviewer : 756
Total Countries : 142
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AGRICULURE OR FARM LAND PRICE PREDICTION USING MACHINE LEARNING |
| Authors Name: | Puneetharaj K R , Vishwas D R , Divyashree S R |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_189860
|
| Published Paper Id: | IJRTI2405044 |
| Published In: | Volume 9 Issue 5, May-2024 |
| DOI: | |
| Abstract: | Prediction for Agriculture or Farm Land A ground-breaking method for predicting land values in the agriculture industry is to use machine learning. Using sophisticated machine learning methods, such as Random Forest and Decision Tree algorithms, this study explores the complex dynamics of agricultural land valuation. The model provides stakeholders with actionable insights for well-informed decision-making by reliably predicting land prices through the analysis of historical data and critical criteria including soil index, density, and location. Our method shows great accuracy rates through thorough testing and validation, highlighting its potential to transform agricultural industry decision-making processes. In addition to making significant advances in the field of agricultural machine learning, this research has applications for landowners, farmers, and policymakers. In order to improve the model's efficacy and adaptability in various agricultural contexts, the study offers future research directions, such as the integration of real-time data sources and the investigation of cooperative data-sharing projects. |
| Keywords: | Agricultural land prediction, Random Forest |
| Cite Article: | "AGRICULURE OR FARM LAND PRICE PREDICTION USING MACHINE LEARNING", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.298 - 303, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405044.pdf |
| Downloads: | 000205121 |
| 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: IJRTI2405044
Registration ID:189860
Published In: Volume 9 Issue 5, May-2024
DOI (Digital Object Identifier):
Page No: 298 - 303 Country: Tumkur District, Karnataka, INDIA Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2405044 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2405044 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
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
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||