Comparison of static MLP and dynamic NARX neural networks for forecasting of atmospheric PM10 and SO2 concentrations in an industrial site of Turkey-Reference-Cited by-同舟云学术

Comparison of static MLP and dynamic NARX neural networks for forecasting of atmospheric PM10 and SO2 concentrations in an industrial site of Turkey

Published:2020-06-01 Issue:3-4 Volume:21 Page:363-374
ISSN:1527-5922
Container-title:Environmental Forensics
language:en
Short-container-title:Environmental Forensics

Author:

Gündoğdu Serdar¹

Affiliation:

1. Computer Technology Program, Bergama Vocational High School, Dokuz Eylul University, Bergama-Izmir, Turkey

Publisher

Informa UK Limited

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal

Link

https://www.tandfonline.com/doi/pdf/10.1080/15275922.2020.1771637

Reference55 articles.

1. Akyürek, Ö., Arslan, O., and Karademir, A. 2013. SO2 ve PM10 Hava Kirliliği Parametrelerinin CBS ile Konumsal Analizi: Kocaeli Örneği. 4. Coğrafi Bilgi Sistemleri Kongresi, Ankara, Türkiye, 1–12.

2. Predicting Particulate Matter (PM2.5) Concentrations in the Air of Shahr-e Ray City, Iran, by Using an Artificial Neural Network

3. Predicting PM2.5 Concentrations Using Artificial Neural Networks and Markov Chain, a Case Study Karaj City

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