Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine-Reference-Cited by-同舟云学术

Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine

Published:2013-09-20 Issue:5-6 Volume:43 Page:1303-1310
ISSN:0930-7575
Container-title:Climate Dynamics
language:en
Short-container-title:Clim Dyn

Author:

Acharya Nachiketa,Shrivastava Nitin Anand,Panigrahi B. K.,Mohanty U. C.

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

http://link.springer.com/content/pdf/10.1007/s00382-013-1942-2.pdf

Reference44 articles.

1. Acharya N, Kar SC, Kulkarni MA, Mohanty UC, Sahoo LN (2011) Multi-model ensemble schemes for predicting northeast monsoon rainfall over peninsular India. J Earth Syst Sci 120:795–805

2. Acharya N, Chattopadhyay S, Kulkarni MA, Mohanty UC (2012) A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor. Acta Geophys 60:260–279. doi: 10.2478/s11600-011-0044-y

3. Acharya N, Singh A, Mohanty UC, Nair A, Chattopadhyay S (2013) Performance of general circulation models and their ensembles for the prediction of drought indices over India during summer monsoon. Nat Hazards 66:851–871

4. Balachandran S, Asokan R, Sridharan S (2006) Global surface temperature in relation to northeast monsoon rainfall over Tamil Nadu. J Earth Syst Sci 115(3):349–362. doi: 10.1007/BF02702047

5. Chakraborty A, Krishnamurti TN (2009) Improving global model precipitation forecasts over India using downscaling and the FSU super-ensemble. Part II: seasonal climate. Mon Weather Rev 137:2736–2757

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