Skip to main navigation
Skip to search
Skip to main content
Prince Sattam bin Abdulaziz University Home
Home
Profiles
Research units
Projects
Research output
Prizes
Activities
Search by expertise, name or affiliation
A deep learning approach for prediction of air quality index in smart city
Adel Binbusayyis
, Muhammad Attique Khan
, Mohamed Mustaq Ahmed A
, W. R.Sam Emmanuel
Software Engineering
University of Engineering and Technology, Taxila
University of Madras
Manonmaniam Sundaranar University
Research output
:
Contribution to journal
›
Article
›
peer-review
28
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A deep learning approach for prediction of air quality index in smart city'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Engineering
Deep Learning Method
100%
Smart City
100%
Learning Approach
100%
Quality Index
100%
Air Quality
100%
Mean Square Error
25%
Root Mean Square Error
25%
Mean Absolute Error
25%
Accurate Prediction
12%
Metrics
12%
Air Pollution
12%
Real Data
12%
Fossil Fuel
12%
Input Data
12%
Comparative Analysis
12%
Processed Data
12%
Daily Basis
12%
Pollution Control
12%
Quality Data
12%
Mathematics
Mean Square Error
100%
Deep Learning Method
100%
Smart City
100%
Absolute Error
50%
Real Data
25%
Accurate Prediction
25%
Missing Value
25%
Coefficient of Determination (R2)
25%
Input Data
25%
Earth and Planetary Sciences
Smart City
100%
Root-Mean-Square Error
25%
India
25%
Air Pollution
12%
Fossil Fuel
12%
Preprocessing
12%
Pollution Control
12%
Chemical Engineering
Deep Learning Method
100%
Material Science
Fossil Fuel
100%