Hybrid neural network models for forecasting ozone and particulate matter concentrations in the Republic of China

Author:

Braik Malik,Sheta AlaaORCID,Al-Hiary Heba

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Management, Monitoring, Policy and Law,Atmospheric Science,Pollution

Reference25 articles.

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2. Alkasassbeh M, Sheta A, Faris H, Turabieh H (2013) Prediction of PM10 and TSP air pollution parameters using artificial neural network autoregressive, external input models: a case study in salt, Jordan. Middle-East J Sci Res 14(7):999–1009

3. Cetin M, Onac AK, Sevik H, Sen B (2019) Temporal and regional change of some air pollution parameters in bursa. Air Qual Atmos Health 2(3):31–316

4. Chang S, Pai T, Ho H, Leu H, Shieh Y (2007) Evaluating Taiwan’s air quality variation trends using grey system theory. J Chin Inst Eng 30(2):361–367

5. Cobourn WG, Dolcine L, French M, Hubbard MC (2000) A comparison of nonlinear regression and neural network models for ground-level ozone forecasting. J Air Waste Manage Assoc 50(11):1999–2009

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