Pregled bibliografske jedinice broj: 935914
Cycle reservoir with regular jumps for forecasting ozone concentrations: two real cases from the east of Croatia
Cycle reservoir with regular jumps for forecasting ozone concentrations: two real cases from the east of Croatia // Air Quality Atmosphere and Health, 11 (2018), 559-569 doi:10.1007/s11869-018-0561-9 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 935914 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Cycle reservoir with regular jumps for forecasting ozone concentrations: two real cases from the east of Croatia
Autori
Sheta, Alaa ; Faris, Hossam ; Rodan, Ali ; Kovač-Andrić, Elvira ; Al-Zoubi, Ala’ M.
Izvornik
Air Quality Atmosphere and Health (1873-9318) 11
(2018);
559-569
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Neural networks ; Reservoirs ; Ozone prediction ; CRJ ; Croatia
Sažetak
Satisfying the national air quality standards represents a challenge nowadays for developing countries. Air pollution in industrial cities is one of the foremost problems that affect human health and might cause loss of human life. One of the main attributes that can cause a significant impact on people’s health is the ground-level ozone pollution. Ozone can raise the ratio of asthma attacks, permanent damage to lungs, and maybe death. Forecasting its concentration levels is essential for planning well-designed environment protection strategies. In this paper, a state-space reservoir model called cycle reservoir with jumps (CRJ) is used to predict the level of ozone concentrations in the east of Croatia utilizing some meteorological parameters including the temperature, relative humidity, wind speed, wind direction, and the pollutants PM10. CRJ is a particular type of recurrent neural networks with powerful performance when applied for complex temporal problems. Two cases from the east of Croatia are investigated in this work: the Kopaćki Rit area and the Osijek city. The proposed CRJ model shows superiority of CRJ model in forecasting ozone concentrations compared to linear regression, multilayer perceptron (MLP) and radial basis function (RBF) network.
Izvorni jezik
Engleski
POVEZANOST RADA
Ustanove:
Sveučilište u Osijeku - Odjel za kemiju
Profili:
Elvira Kovač Andrić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus