|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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: April 2024
Volume 9 | Issue 4
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 : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 95
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Air Quality Prediction Using Feature Selection and Deep Learning model |
| Authors Name: | Adhiraj Sud |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_200704
|
| Published Paper Id: | IJNRD2306636 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | The growing number of vehicles and industry pollution leads to poor air quality, which brings serious health issues and lung problems for humans. There are safety measures followed by the Government to regulate the air quality, the detection of air quality is challenging due to the implementation cost and computations. The air quality measure is to be continuously monitored under urban areas to ensure healthy living. Artificial intelligence is the growing area in all industries, thus this work is proposed to exploit the advantages of deep learning algorithms for air quality detection. The proposed work used feature selection technique for selecting the important and relevant features brings high accuracy of air quality detection. The wrapper based technique, Recursive feature elimination (RFE) is used for feature selection and deep learning model Deep Neural Network (DNN) is used for predicting the air quality. This prediction gives an alert for the surrounding to work on further measures in controlling pollution. Experimental results showed that the deep learning model outperforms in air quality prediction with the highest accuracy. |
| Keywords: | Machine Learning, Deep learning, Recursive feature elimination, Feature selection, Air quality, Deep Neural Network |
| Cite Article: | "Air Quality Prediction Using Feature Selection and Deep Learning model", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.g339-g346, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306636.pdf |
| Downloads: | 000118757 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2306636 Registration ID: 200704 Published In: Volume 8 Issue 6, June-2023 DOI (Digital Object Identifier): Page No: g339-g346 Country: Gurgaon, Haryana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2306636 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2306636 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn