Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: A case study of Mashhad
Quantity prediction of municipal solid waste (MSW) is crucial for design and programming
municipal solid waste management system (MSWMS). Because effect of various parameters …
municipal solid waste management system (MSWMS). Because effect of various parameters …
Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model
Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring
and forecasting of air quality parameters have become popular as an important topic in …
and forecasting of air quality parameters have become popular as an important topic in …
[HTML][HTML] Development of artificial intelligence based NO2 forecasting models at Taj Mahal, Agra
The statistical regression and specific computational intelligence based models are
presented in this paper for the forecasting of hourly NO 2 concentrations at a historical …
presented in this paper for the forecasting of hourly NO 2 concentrations at a historical …
An expert system for predicting longitudinal dispersion coefficient in natural streams by using ANFIS
H Riahi-Madvar, SA Ayyoubzadeh, E Khadangi… - Expert Systems with …, 2009 - Elsevier
Longitudinal dispersion coefficient in rivers and natural streams usually is estimated by
simple inaccurate empirical relations, because of the complexity of the phenomena. So, in …
simple inaccurate empirical relations, because of the complexity of the phenomena. So, in …
[HTML][HTML] Artificial neural network an innovative approach in air pollutant prediction for environmental applications: A review
Air pollution in the environment is growing daily as a result of urbanization and population
growth, which causes numerous health issues. Information about air quality and …
growth, which causes numerous health issues. Information about air quality and …
Using wavelet–feedforward neural networks to improve air pollution forecasting in urban environments
D Dunea, A Pohoata, S Iordache - Environmental monitoring and …, 2015 - Springer
The paper presents the screening of various feedforward neural networks (FANN) and
wavelet–feedforward neural networks (WFANN) applied to time series of ground-level ozone …
wavelet–feedforward neural networks (WFANN) applied to time series of ground-level ozone …
Seasonal variation of air pollution index: Hong Kong case study
XK Wang, WZ Lu - Chemosphere, 2006 - Elsevier
Air pollution is an important and popular topic in Hong Kong as concerns have been raised
about the health impacts caused by vehicle exhausts in recent years. In Hong Kong, sulphur …
about the health impacts caused by vehicle exhausts in recent years. In Hong Kong, sulphur …
Prediction of particulate matter concentration profile in an opencast copper mine in India using an artificial neural network model
Particulate matter (PM) is a major pollutant in and around opencast mine areas. The
problem of degradation of air quality due to opencast mine is more severe than those in …
problem of degradation of air quality due to opencast mine is more severe than those in …
Comparison of neural network and principal component-regression analysis to predict the solid waste generation in Tehran
Background: Municipal solid waste (MSW) is the natural result of human activities. MSW
generation modeling is of prime importance in designing and programming municipal solid …
generation modeling is of prime importance in designing and programming municipal solid …
High spatiotemporal characterization of on-road PM2. 5 concentrations in high-density urban areas using mobile monitoring
Mobile air quality monitoring reports air pollutant concentrations at a high spatiotemporal
resolution, enabling the characterization of heterogeneous human exposure and localized …
resolution, enabling the characterization of heterogeneous human exposure and localized …