Spatial interpolation of rainfall variables using artificial neural network

Proceedings of the International Conference on Advances in Computing, Communication and Control, ICAC3'09

Volumn , Issue , 2009, Pages 547-552

  Karmakar, S ^a   Kowar, M K ^a   Guhathakurta, P ^b  

^a BHILAI INSTITUTE OF TECHNOLOGY   (India)

^b Ministry of Earth Sciences   (India)

Author keywords

Axon; Interpolation; Neuron

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AXON; CHHATTISGARH; FEED-FORWARD BACK PROPAGATION; PERCEPTRON; RAINFALL VARIABLE; SPATIAL INTERPOLATION;

BACKPROPAGATION; COMPUTER SCIENCE; INTERPOLATION; RAIN;

NEURAL NETWORKS;

EID: 70349120222     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1523103.1523212     Document Type: Conference Paper

References (5)

1. Álvaro Pimpão Silva, 2003, Neural Networks Application to Spatial Interpolation of Climate Variables, STSM on the Framework of COST 719 ZAMG, Vienna 6-10 October.
2. Bryan, B.A.; Adams, J.M., 2001Quantitative and qualitative assessment of the accuracy of neurointerpolated annual mean precipitation and temperature surfaces for China, Cartography, 30, 2, Perth, Australia.
3. Demyanov, V. et al, 1998, Neural network residual kriging application for climatic data, Journal of Geographic Information and Decision Analysis, 2, 2, 215-232.
4. Guhathakurta P, 1999, Long range forecasting Indian summer monsoon rainfall by principle component neural network model, Meteor. & Atomos. Phys., 71, 255-266.
5. Rumbelhart D., Hinton G. E., and Williams R. J., "Learning internal representation by error propagation, R J Parallel Distributed Processing: Exploration in the Microstructure of Cognition", MIT Press Cambridge, 1, 318-362, 1986.