International Journal of Intelligent Systems and Applications(IJISA)
ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)
Published By: MECS Press
IJISA Vol.5, No.12, Nov. 2013
Prediction of Rainfall in India using Artificial Neural Network (ANN) Models
Full Text (PDF, 1285KB), PP.1-22
In this paper, ARIMA(1,1,1) model and Artificial Neural Network (ANN) models like Multi Layer Perceptron (MLP), Functional-link Artificial Neural Network (FLANN) and Legendre Polynomial Equation ( LPE) were used to predict the time series data. MLP, FLANN and LPE gave very accurate results for complex time series model. All the Artificial Neural Network model results matched closely with the ARIMA(1,1,1) model with minimum Absolute Average Percentage Error(AAPE). Comparing the different ANN models for time series analysis, it was found that FLANN gives better prediction results as compared to ARIMA model with less Absolute Average Percentage Error (AAPE) for the measured rainfall data.
Cite This Paper
Santosh Kumar Nanda, Debi Prasad Tripathy, Simanta Kumar Nayak, Subhasis Mohapatra,"Prediction of Rainfall in India using Artificial Neural Network (ANN) Models", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.12, pp.1-22, 2013. DOI: 10.5815/ijisa.2013.12.01
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