Air pollution prediction by using an artificial neural network model
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Air pollution prediction by using an artificial neural network model
Authors
Keywords
-
Journal
Clean Technologies and Environmental Policy
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-05-28
DOI
10.1007/s10098-019-01709-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
- (2018) Stefan Elfwing et al. NEURAL NETWORKS
- Spatial estimation of urban air pollution with the use of artificial neural network models
- (2018) A. Alimissis et al. ATMOSPHERIC ENVIRONMENT
- Temporal and spatial variations of particulate matter and gaseous pollutants in the urban area of Tehran
- (2016) O. Alizadeh-Choobari et al. ATMOSPHERIC ENVIRONMENT
- Development of ANFIS models for air quality forecasting and input optimization for reducing the computational cost and time
- (2016) Kanchan Prasad et al. ATMOSPHERIC ENVIRONMENT
- Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ
- (2016) Yang Zhang et al. ATMOSPHERIC ENVIRONMENT
- Chemical composition of PM10 and its in vitro toxicological impacts on lung cells during the Middle Eastern Dust (MED) storms in Ahvaz, Iran
- (2016) Abolfazl Naimabadi et al. ENVIRONMENTAL POLLUTION
- Assessment of resident's exposure level and health economic costs of PM10 in Beijing from 2008 to 2012
- (2016) Qing Hou et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Temporal profile of PM 10 and associated health effects in one of the most polluted cities of the world (Ahvaz, Iran) between 2009 and 2014
- (2016) Heidar Maleki et al. Aeolian Research
- Forecasting O 3 levels in industrial area surroundings up to 24 h in advance, combining classification trees and MLP models
- (2016) Rita M. Durão et al. Atmospheric Pollution Research
- Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions
- (2016) Yun Bai et al. Atmospheric Pollution Research
- Artificial neural networks forecasting of PM 2.5 pollution using air mass trajectory based geographic model and wavelet transformation
- (2015) Xiao Feng et al. ATMOSPHERIC ENVIRONMENT
- On the severe haze in Beijing during January 2013: Unraveling the effects of meteorological anomalies with WRF-Chem
- (2015) Li Zhang et al. ATMOSPHERIC ENVIRONMENT
- A new structure identification scheme for ANFIS and its application for the simulation of virtual air pollution monitoring stations in urban areas
- (2015) Hamid Taheri Shahraiyni et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Prediction of particulate matter concentration profile in an opencast copper mine in India using an artificial neural network model
- (2015) Aditya Kumar Patra et al. Air Quality Atmosphere and Health
- Comparisons of GM (1,1), and BPNN for predicting hourly particulate matter in Dali area of Taichung City, Taiwan
- (2015) Li Chen et al. Atmospheric Pollution Research
- Neural network forecast of daily pollution concentration using optimal meteorological data at synoptic and local scales
- (2015) Ana Russo et al. Atmospheric Pollution Research
- Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering
- (2014) M.A. Elangasinghe et al. ATMOSPHERIC ENVIRONMENT
- Analysis and forecasting of the particulate matter (PM) concentration levels over four major cities of China using hybrid models
- (2014) Shanshan Qin et al. ATMOSPHERIC ENVIRONMENT
- Spatiotemporal distribution and short-term trends of particulate matter concentration over China, 2006–2010
- (2014) Ling Yao et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- RBF neural network inferential sensor for process emission monitoring
- (2013) Surajdeen A. Iliyas et al. CONTROL ENGINEERING PRACTICE
- Desert dust and human health disorders
- (2013) Andrew S. Goudie ENVIRONMENT INTERNATIONAL
- Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean
- (2013) Gianluigi de Gennaro et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Impact of the March 2009 dust event in Saudi Arabia on aerosol optical properties, meteorological parameters, sky temperature and emissivity
- (2011) A. Maghrabi et al. ATMOSPHERIC ENVIRONMENT
- Economic damages of ozone air pollution to crops using combined air quality and GIS modelling
- (2010) Ch. Vlachokostas et al. ATMOSPHERIC ENVIRONMENT
- Identification of regional atmospheric PM10 transport pathways using HYSPLIT, MM5-CMAQ and synoptic pressure pattern analysis
- (2010) F. Wang et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: Multiple regression approach
- (2009) Pawan Gupta et al. JOURNAL OF GEOPHYSICAL RESEARCH
- Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach
- (2008) Ming Cai et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Economic assessment of the health effects related to particulate matter pollution in 111 Chinese cities by using economic burden of disease analysis
- (2007) Minsi Zhang et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started