Prediction of Rainfall in India using Artificial Neural Network (ANN) Models

  • Nanda S
  • Tripathy D
  • Nayak S
  • et al.
N/ACitations
Citations of this article
77Readers
Mendeley users who have this article in their library.

Abstract

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

CITATION STYLE

APA

Nanda, S. K., Tripathy, D. P., Nayak, S. K., & Mohapatra, S. (2013). Prediction of Rainfall in India using Artificial Neural Network (ANN) Models. International Journal of Intelligent Systems and Applications, 5(12), 1–22. https://doi.org/10.5815/ijisa.2013.12.01

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free