Rainfall Prediction Due to El Nino Factors Using Recurrent Neural Networks

Time Lag recurrent Neural Network model for Rainfall prediction using El Niño indices

Indian summer monsoon rainfall is a process which is dependent on number of environmental and geological parameter. This makes it very hard to precisely predict the monsoon rainfall. As India is agriculture based country, a long range monsoon rainfall prediction is crucial for proper planning and organization of agriculture policy. Severe hydrological events, such as droughts, may result in dec...

Rainfall Prediction Using Artificial Neural Networks

The spatial interpolation comparison 97 is concerned with predicting the daily rainfall at 367 locations based on the daily rainfall at nearby 100 locations in Switzerland. We propose a divide -and-conquer approach where the whole region is divided into four sub-areas and each is modeled with a different method. Predictions in two larger areas were made by RBF networks based on the locational i...

Using Recurrent Neural Networks in Trajectory Prediction

MIMO Channel Prediction Using Recurrent Neural Networks

Adaptive modulation is a communication technique capable of maximizing throughput while guaranteeing a fixed symbol error rate (SER). However, this technique requires instantaneous channel state information at the transmitter. This can be obtained by predicting channel states at the receiver and feeding them back to the trasnmitter. Existing algorithms used to predict single-input single-output...

The Predictability of El Nino the 1997/98 El Nino

The Southern Oscillation, a natural mode of oscillation of the coupled ocean-atmosphere system, at times appears to be self-sustaining and hence relatively easy to predict. The 1980s seem to have been such a period; El Nino of 1982183 was the start of two complete cycles of the Southern Oscillation. At other times the oscillation seems to be a damped mode that is present for a cycle at most, af...