CLIMATE PREDICTION USING DETERMINISTIC ANN MODEL.
- A. P. S. University, Rewa, Madhya Pradesh (India)
- Bhilai Institute of Technology (BIT), Bhilai House, Durg, CG (India)
- Govt New Science College, Rewa (M.P.)
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The ANN based models are most imperative and demanding for climate prediction. Back-Propagation Neural Network is an appropriate methodology in identification of parameters for long-term rainfall data. Presented BPN model is best to identify climatic parameter for prediction as well as forecast rainfall. Forecasting of rainfall over vindhya region has been analyzed through developed BPN model. The observed long period average (LPA) is 956.74 for 45 years data time series of vindhya region. It is observed that the MAD (6.09) is less than the SD (14.37) during the testing period. Correlation coefficient of training period is 0.89 and for testing period is 0.95. The performance of the model is accurately observed.
[Shailendra Singh, Navita Shrivastava, Sanjeev Karmakar and R.K. Tiwari. (2016); CLIMATE PREDICTION USING DETERMINISTIC ANN MODEL. Int. J. of Adv. Res. 4 (May). 34-38] (ISSN 2320-5407). www.journalijar.com
