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dc.contributor.authorShende, K.V.
dc.contributor.authorRameshKumar, M.R.
dc.contributor.authorKale, K.V.
dc.date.accessioned2020-02-04
dc.date.accessioned2020-02-04T09:38:26Z
dc.date.available2019-10-17
dc.date.available2020-02-04T09:38:26Z
dc.date.issued2020
dc.identifier.citationin: Iyer, B.; Deshpande, P.; Sharma, S.; Shiurkar, U. (Ed.), Computing in Engineering and Technology. Advances in Intelligent Systems and Computing, vol 1025, pp. 411-419
dc.identifier.urihttps://doi.org/10.1007/978-981-32-9515-5_39
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/8299
dc.description.abstractArtificial Neural Network (ANN) is contributed in many fields for forecasting or prediction like medical field, Sensex, biometric, remote sensing, pattern recognition, etc. The beauty of ANN is that it is having a capability to dealing with non-linear data. In the present situation, everyone is facing atmospheric and climate change problems. Study on an atmospheric and meteorological data is a challenging task because it gives a complex and non-linear type of data. In such a case, ANN is a better technique for dealing with non-linear atmospheric and meteorological data. In the present analysis, use an atmospheric data such as wind speed, latent heat flux, net surface heat flux and Sea Surface Temperature for the prediction of outgoing longwave radiation over the latitude 80�E:100�E and longitude 0-25�N for the Bay of Bengal. To achieve the objective, use a Feedforward Neural Network with five different training functions like Levenberg-Marquardt, conjugate gradient with Beale-Powell restarts, one step secant, Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton and gradient descent. Use various performance analysis parameters such as correlation coefficient, root mean square error and prediction accuracy to find out the performance of training function. From the analysis, it is observed that from the above five training functions, Levenberg-Marquardt gives a 95.81% accuracy which is higher than the others.
dc.languageen
dc.relation.isreferencedbyNON-SCI
dc.rightsOnly the author version of the copright reserved papers uploaded. Contact drs@nio.org for any complaints regarding copyright violations
dc.titleComparison of Neural Network Training Functions for Prediction of Outgoing Longwave Radiation over the Bay of Bengal
dc.typeBook Chapter


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