Email this article 
Open Access
Subscription or Fee Access
On the Predictability of Rainfall in Western Maharashtra - An Application of RBF Neural Network
Abstract
A time series is a sequence of data points, measured typically at successive times, spaced at (often uniform) time intervals. Time series forecasting is the use of a model to forecast future events based on known past events: to forecast future data points before they are measured. Rain fall may the oldest time series and human being always keep analyzing the rainfall time series by various means.Neural networks are applicable in virtually every situation in which a relationship between the predictor variables and predicted variables exists, even when that relationship is very complex and not easy to articulate in the usual terms of correlations or differences between groups. This work is an attempt to determine the best learning rule and activation function for the rainfall forecasting using radial basis function (RBF).
Keywords
References
Forecast For Monsoon rainfall (June-September 1999) (Issued on the 25 May) Indian Meteorological Department Report W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123–135.
V. Gowariker, V. Thapliyal, S. M. Kulshrestha, G. S. Mandal, N. Sen Roy, and D. R. Sikka, “A power regression model for long range forecast of southwest monsoon rainfall over India” Mausam, 42(2):125–30, 1991.
A. Abraham, N. S. Philip and D. Steinberg, “Rainfall forecasting using soft computing models and multivariate adaptive regression splines”,IEEE Transactions: Special Issue on Fusion of Soft Computing and Hard Computing in Industrial Applications, February 2001.
T. Moriyama and H. Muneo, “Quantitative precipitation forecasting using neural networks”, 3rd International Symposium on Weather Radars, São Paulo, Brazil, August 1995.
Ninan Sajeeth Philip and K. Babu Joseph, “On the predictability of Rainfall in Kerala - An Application of RBF Neural Network”, Lecture Notes in Computer Science(LNCS 2074), Springer Verlag, Germany, pp 400-408, 2001.
B. Parthasarathy, A. A. Munot, and D. R. Kothwale, “Monthly and seasonal rainfall series for all-India homogeneous regions and meteorological subdivisions: 1871 1994”, Contributions from Indian Institute of Tropical Meteorology, Pune-411 008, INDIA. 1995.
Philip N S and Joseph K B, On the Predictability of Rainfall in Kerala: An Application of ABF Neural Network, In Proceedings of Workshop on Intelligent Systems Design and Applications (ISDA 2001), In Conjunction with International Conference on Computational Sciences, ICCS 2001, San Francisco, May 2001.
Abraham A and Nath B, Designing Optimal Neuro -Fuzzy Systems for Intelligent Control, The Sixth International Conference on Control, Automation, Robotics and Vision, (ICARCV 2000), December 2000.
A. Abraham, N. S. Philip and B. Joseph, “Will we have a wet summer? Soft computing models for long-term rainfall forecasting”, Publication of the Society for Computer Simulation International, Prague, Czech Republic, Kerckhoffs E.J.H. and Snorek M. (Eds.), ISBN 1565552253, pp. 1044 1048, 2001.
Kin C. Luk, J. E. Ball And A. Sharma, “An application of artificial neural networks for rainfall forecasting”, Mathematical and Computer Modelling, 33, pp 683-693, 2001.
G. T. Walker, “Correlation in seasonal variation of climate (Introduction)”, Mem. India Meteorol. Dept., (IMD Mem.), 20, 117−124, 1908.
C. Chatfeld, “The analysis of time series-an introduction” Chapman Hall, London, 5th ed., 1996.
C. Chatfeld, “Time-series forecasting”, Chapman & Hall/CRC, Boca Raton, Florida, 2001.
G. E. P. Box, G.M. Jenkins, “Time Series Analysis: Forecasting and Control”, 2nd ed. (Holden-Day, San Francisco, 1976.
S. Haykin, “Neural Networks: A Comprehensive Foundation”, Prentice Hall, NJ, 2nd ed., 2003.
M. J. D. Powell, “Radial basis functions for multivariable interpolation: a review”, Algorithms for Approximation, Oxford: Clarendon Press, pp. 143- 167, 1987.
Zurada J M, Introduction to Artificial Neural Systems, PWS Pub Co, 1992.
C.Y. Patil, Dr. A.A. Ghatol, Average Rainfall Forecasting Using Multilayer Perceptron Network, National Conference on Signal Processing, & Automation, DYPIET, Pune, Sept, 6-8, 2007.
C. Y. Patil, Mrs. R. P. Mudhalwadkar, Dr. A.A. Ghatol, “Average Rainfall Prediction A Neural Network Approach”, International Conference on WCETE 2006, Brazil.
Muhammad Muslehuddin, Hazrat Mir, and Nadeem Faisal, “Sindh summer (June-September) monsoon rainfall prediction”, Pakistan Journal of Meteorology, Vol 2, Issue 4, Nov 2005.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.