Journal ArticleDOI
Progress in developing an ANN model for air pollution index forecast
Reads0
Chats0
TLDR
The development of an artificial neural network (ANN) model for the API forecasting in Shanghai is described, a multiple layer perceptron (MLP) network, with meteorological forecasting data as the main input, to output the next day average API values.About:
This article is published in Atmospheric Environment.The article was published on 2004-12-01. It has received 150 citations till now. The article focuses on the topics: Air Pollution Index.read more
Citations
More filters
Journal ArticleDOI
Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation
TL;DR: In this article, a novel hybrid model combining air mass trajectory analysis and wavelet transformation to improve the artificial neural network (ANN) forecast accuracy of daily average concentrations of PM2.5 two days in advance is presented.
Journal ArticleDOI
A review of artificial neural network models for ambient air pollution prediction
TL;DR: A protocol by Maier et al. (2010) for ANN model development is presented and applied to assess journal papers dealing with air pollution forecasting using ANN models, highlighting the need for developing systematic protocols for developing powerful ANN models.
Journal ArticleDOI
Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach
TL;DR: In this paper, an artificial neural network (ANN) framework was proposed to reduce the uncertainty of surface PM estimation from satellite data, using 3 years of MODIS optical thickness data at 0.55 μm and meteorological analyses from the rapid update cycle to estimate surface level PM2.5.
Journal ArticleDOI
An integrated neural network model for PM10 forecasting
Patricio Perez,Jorge Reyes +1 more
TL;DR: In this article, an integrated artificial neural network model was developed to forecast the maxima of 24-hour average of PM10 concentrations 1 day in advance and applied it to the case of five monitoring stations in the city of Santiago, Chile.
Journal ArticleDOI
Observations and modeling of air quality trends over 1990–2010 across the Northern Hemisphere: China, the United States and Europe
Jia Xing,Rohit Mathur,Jonathan E. Pleim,Christian Hogrefe,Chuen-Meei Gan,David C. Wong,Chao Wei,Chao Wei,Robert C. Gilliam,George Pouliot +9 more
TL;DR: In this paper, the authors used the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting (WRF) simulations and internally consistent historical emission inventories obtained from EDGAR.
References
More filters
Book
Neural networks for pattern recognition
TL;DR: This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
Journal ArticleDOI
Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity
Fei Chen,Jimy Dudhia +1 more
TL;DR: In this paper, the authors address and document a number of issues related to the implementation of an advanced land surface-hydrology model in the Penn State-NCAR fifth-generation Mesoscale Model (MM5).
Journal ArticleDOI
Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences
M.W. Gardner,Stephen Dorling +1 more
TL;DR: This paper presents a general introduction and discussion of recent applications of the multilayer perceptron, one type of artificial neural network, in the atmospheric sciences.
Journal ArticleDOI
Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part II: Preliminary Model Validation
Fei Chen,Jimy Dudhia +1 more
TL;DR: In this paper, a number of short-term numerical experiments conducted by the Penn StateNCAR fifth-generation Mesoscale Model (MM5) coupled with an advanced land surface model, alongside the simulations coupled with a simple slab model, are verified with observations.
Journal ArticleDOI
Comparing Neural Networks and Regression Models for Ozone Forecasting
TL;DR: In this paper, the authors investigated the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models, for a range of cities under different climate and o...
Related Papers (5)
Artificial neural network models for prediction of PM10 hourly concentrations, in the Greater Area of Athens, Greece
Georgios Grivas,A. Chaloulakou +1 more
Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences
M.W. Gardner,Stephen Dorling +1 more