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Chattopadhyay, Surajit, Chattopadhyay, Goutami (2012) Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis. Pure and Applied Geophysics, 169 (10) 1891-1908 doi:10.1007/s00024-011-0437-5

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Reference TypeJournal (article/letter/editorial)
TitleModeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis
JournalPure and Applied Geophysics
AuthorsChattopadhyay, SurajitAuthor
Chattopadhyay, GoutamiAuthor
Year2012 (October)Volume169
Issue10
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s00024-011-0437-5Search in ResearchGate
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Mindat Ref. ID994536Long-form Identifiermindat:1:5:994536:8
GUID0
Full ReferenceChattopadhyay, Surajit, Chattopadhyay, Goutami (2012) Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis. Pure and Applied Geophysics, 169 (10) 1891-1908 doi:10.1007/s00024-011-0437-5
Plain TextChattopadhyay, Surajit, Chattopadhyay, Goutami (2012) Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis. Pure and Applied Geophysics, 169 (10) 1891-1908 doi:10.1007/s00024-011-0437-5
In(2012, October) Pure and Applied Geophysics Vol. 169 (10) Springer Science and Business Media LLC

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Chattopadhyay, Goutami, Chattopadhyay, Surajit, Chakraborthy, Parthasarathi (2012) Principal component analysis and neurocomputing-based models for total ozone concentration over different urban regions of India. Theoretical and Applied Climatology, 109 (1). 221-231 doi:10.1007/s00704-011-0569-7
Chattopadhyay, Goutami, Chattopadhyay, Surajit (2012) Monthly sunspot number time series analysis and its modeling through autoregressive artificial neural network. The European Physical Journal Plus, 127 (4). doi:10.1140/epjp/i2012-12043-9
Chattopadhyay, Surajit, Bandyopadhyay, Goutami (2007) Artificial neural network with backpropagation learning to predict mean monthly total ozone in Arosa, Switzerland. International Journal of Remote Sensing, 28 (20). doi:10.1080/01431160701250440
Chattopadhyay, Goutami, Chakraborthy, Parthasarathi, Chattopadhyay, Surajit (2012) Mann–Kendall trend analysis of tropospheric ozone and its modeling using ARIMA. Theoretical and Applied Climatology, 110 (3). 321-328 doi:10.1007/s00704-012-0617-y
Chattopadhyay, Goutami, Chattopadhyay, Surajit (2010) Univariate approach to the monthly total ozone time series over Kolkata, India: autoregressive integrated moving average (ARIMA) and autoregressive neural network (AR-NN) models. International Journal of Remote Sensing, 31 (3). doi:10.1080/01431160902893592
Chattopadhyay, Goutami, Chattopadhyay, Surajit (2009) Autoregressive forecast of monthly total ozone concentration: A neurocomputing approach. Computers & Geosciences, 35 (9) 1925-1932 doi:10.1016/j.cageo.2008.11.007
Chattopadhyay, Surajit, Chattopadhyay, Goutami (2008) A factor analysis and neural network‐based validation of the Varotsos–Cracknell theory on the 11‐year solar cycle. International Journal of Remote Sensing, 29 (9). doi:10.1080/01431160701767468
Chattopadhyay, Surajit, Chattopadhyay‐Bandyopadhyay, Goutami (2008) Forecasting daily total ozone concentration—a comparison between neurocomputing and statistical approaches. International Journal of Remote Sensing, 29 (7). doi:10.1080/01431160701373770
Tiampo, K. F., Mazzotti, S., James, T. S. (2012) Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis. Pure and Applied Geophysics, 169 (8) 1483-1506 doi:10.1007/s00024-011-0420-1
Kumar, Anikender, Goyal, P. (2013) Forecasting of Air Quality Index in Delhi Using Neural Network Based on Principal Component Analysis. Pure and Applied Geophysics, 170 (4) 711-722 doi:10.1007/s00024-012-0583-4
Chattopadhyay, Surajit, Chattopadhyay‐Bandyopadhyay, Goutami (2008) Forecasting daily ozone concentration—a comparison between neurocomputing and statistical approaches. International Journal of Remote Sensing, 29 (12). doi:10.1080/01431160802188325
 
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