in recent decades artificial neural networks (anns) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. this paper presents the application of artificial neural networks to predict drought in yazd meteorological station. in this research, different archite...

In this paper, multi step ahead prediction of monthly sunspot real time series are carried out. This series is highly chaotic in nature [7]. This paper compares performance of proposed Jordan Elman Neural Network with TLRNN (Time lag recurrent neural network), and RNN (Recurrent neural network) for multi-step ahead (1, 6, 12, 18, 24) predictions. It is seen that the proposed neural network mode...

In recent decades artificial neural networks (ANNs) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. This paper presents the application of artificial neural networks to predict drought in Yazd meteorological station. In this research, different archite...

In this chapter, we have surveyed briefly previous work in predicting noisefree piecewise chaotic time series and noisy time series with high frequency random noise. For noise-free time series, we have proposed a constrained formulation for neural-network learning that incorporates the error of each learning pattern as a constraint, a new cross-validation scheme that allows multiple validations...

In this chapter, we have briefly surveyed previous work in predicting noise-free piecewise chaotic time series and noisy time series with high frequency random noise. For noise-free time series, we have proposed a constrained formulation for neural network learning that incorporates the error of each learning pattern as a constraint, a new cross-validation scheme that allows multiple validation...

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...

We provide a new sequential predictors approach for the exponential stabilization of linear time-varying systems. Our method circumvents the problem of constructing and estimating distributed terms in the control laws, and allows arbitrarily large input delay bounds, pointwise time-varying input delays, and uncertainties. Instead of using distributed terms, our approach to handling longer delay...