Autoregressive forecast of monthly total ozone concentration: A neurocomputing approach

Author:

Chattopadhyay Goutami,Chattopadhyay Surajit

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Information Systems

Reference56 articles.

1. Sensible heat flux estimation over the FIFE site by neural networks;Abareshi;Journal of the Atmospheric Sciences,1998

2. Quasi-biennial variations in temperature, total ozone, and tropopause height;Angell;Journal of the Atmospheric Sciences,1964

3. Baldwin, M., Dameris, M., Austin, J., Bekki, S., Bregman, B., Butchart, N., Cordero, E., Gillett, N., Graf, H.F., Granier, C., Kinnison, D., Lal, S., Peter, T., Randel, W., Scinocca, J., Shindell, D., Struthers, H., Takahashi, M., Thompsonv, D., 2006. Chapter 5, Scientific assessment of ozone depletion, global ozone research and monitoring project—Report No. 50, World Meteorological Organization, Geneva, Switzerland. 〈http://www.wmo.ch/pages/prog/arep/gaw/ozone_2006/ozone_asst_report.html〉, [accessed on 09 April, 2009].

4. A new fast stratospheric ozone chemistry scheme in an intermediate general-circulation model II: application to effects of future increases in greenhouse gases;Bourqui;Quarterly Journal of Royal Meteorological Society,2005

5. Time Series Analysis: Forecasting and Control;Box,2007

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