Ozone Pollution Prediction around Industrial Areas Using Fuzzy Neural Network Approach-Reference-Cited by-同舟云学术

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Ozone Pollution Prediction around Industrial Areas Using Fuzzy Neural Network Approach

Published:2013-11-08 Issue:7 Volume:42 Page:871-879
ISSN:1863-0650
Container-title:CLEAN - Soil, Air, Water
language:en
Short-container-title:Clean Soil Air Water

Author:

Zahedi Gholamreza¹,Saba Sahar²,Elkamel Ali³,Bahadori Alireza⁴

Affiliation:

1. Chemical and Biochemical Engineering Department; Missouri University of Science and Technology; Rolla USA

2. Chemical Engineering Department; Razi University; Kermanshah Iran

3. Chemical Engineering Department; University of Waterloo; Waterloo Canada

4. Southern Cross University; School of Environment, Science and Engineering; Lismore NSW Australia

Publisher

Wiley

Subject

Pollution,Water Science and Technology,Environmental Chemistry

Reference34 articles.

1. Spectral Analysis of Air Pollutants, Part 2: Ozone Time Series;Sebald;Atmos. Environ.,2000

2. Characterizing Changes in Surface Ozone Levels in Metropolitan and Rural Areas in the United States for 1980-2008 and 1994-2008;Lefohen;Atmos. Environ.,2010

3. The Effects of Volcanic Eruption on Atmospheric Chemistry;Glasow;Chem. Geol.,2009

4. Ozone and Urban Forests in Italy;Paoletti;Environ. Pollut.,2009

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1. Temporal convolutional denoising autoencoder network for air pollution prediction with missing values;Urban Climate;2021-07

2. Optimized dosage control of the ozonation process in drinking water treatment;Measurement and Control;2021-04-16

3. A novel approach for exposure assessment in air pollution epidemiological studies using neuro-fuzzy inference systems: Comparison of exposure estimates and exposure-health associations;Environmental Research;2017-04

4. MPC for Ozone Dosage in Water Treatment Process based on Disturbance Observer;Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics;2017

5. Development of ANFIS models for PM short-term prediction. case study;2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI);2016-06

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