Committee of artificial neural networks for monthly rainfall prediction using wavelet transform

The importance of long-range prediction of rainfall pattern for devising and planning agriculture strategies cannot be overemphasized. Prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. In this paper, a committee of artificial neural networks (ANNs) based model with wavelet decomposition is proposed for prediction of monthly rainfall on accounts of the preceding events of rainfall data. Wavelet transform is used for extraction of approximate and detail coefficient of the rainfall data series. These coefficients are used along with a ANN for learning and knowledge extraction processes. The model has been tested on rainfall data for different geographical region of India and also for entire country. The proposed model is capable of forecasting monthly rainfall one month in advance

[1]  D. R. Sikka,et al.  A POWER REGRESSION MODEL FOR LONG RANGE FORECAST OF SOUTHWEST MONSOON RAINFALL OVER INDIA , 2021, MAUSAM.

[2]  N. Null Artificial Neural Networks in Hydrology. I: Preliminary Concepts , 2000 .

[3]  R Govindaraju,et al.  ARTIFICIAL NEURAL NETWORKS IN HYDROLOGY: II, HYDROLOGIC APPLICATIONS , 2000 .

[4]  M. Rajeevan,et al.  New Models for Long Range Forecasts of Summer Monsoon Rainfall over North West and Peninsular India , 2000 .

[5]  Stéphane Canu,et al.  The long-term memory prediction by multiscale decomposition , 2000, Signal Process..

[6]  Mato Baotic,et al.  Model structure selection for nonlinear system identification using feedforward neural networks , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[7]  H Schmidli,et al.  Advantages of Artificial Neural Networks (ANNs) as alternative modelling technique for data sets showing non-linear relationships using data from a galenical study on a solid dosage form. , 1998, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[8]  V. Thapliyal,et al.  Recent models for long range forecasting of Southwest monsoon rainfall in India , 2021, MAUSAM.

[9]  K. K. Kumar,et al.  Seasonal forecasting of Indian summer monsoon rainfall: A review , 1995 .

[10]  Ashish Sharma,et al.  A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting , 2000 .

[11]  P. Swain,et al.  Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing Data , 1990 .

[12]  C. Chui Wavelet Analysis and Its Applications , 1992 .

[13]  null null,et al.  Artificial Neural Networks in Hydrology. II: Hydrologic Applications , 2000 .

[14]  Sunyoung Lee Rainfall Prediction Using Artificial Neural Networks , 1998 .

[15]  Todd R. Ogden,et al.  Wavelet Methods for Time Series Analysis , 2002 .

[16]  H A Ceccatto,et al.  Predicting Indian monsoon rainfall: a neural network approach , 1994 .

[17]  A. Lapedes,et al.  Nonlinear Signal Processing Using Neural Networks , 1987 .

[18]  Ashish Sharma,et al.  An application of artificial neural networks for rainfall forecasting , 2001 .

[19]  Rufin VanRullen,et al.  The power of the feed-forward sweep , 2008, Advances in cognitive psychology.