In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (HH) in the observation w...

Modelling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network (ANN) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

simulation of groundwater fluctuations plays a crucial role in management of watersheds and water demand balancing. recently, wavelet analysis has been used widely in time series decomposition and coupling with neural networks for hydrological modeling. in this paper, the ability of the wavelet-dynamic artificial neural networks (w-ann) model was applied in forecasting one-month-ahead of ground...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

In this paper, an Artificial Neural Networks (ANN) model has been developed to design the multilayer Rectangular microstrip patch. In the design procedure, synthesis ANN model is used as feed forward network to calculate the resonant frequency. Analysis ANN model is used as the reverse side of the problem to calculate the antenna dimension. The network is trained with the data obtained from mea...

This study presents an integrated Artificial Neural Network (ANN) and time series framework to estimate and predict Signal to Interference Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. It is difficult to model uncertain behavior of SIR with only conventional ANN or time series and the integrated algorithm could be an ideal substitute for such cases. Artificial ...

Predicting Tra c flow in the busiest cities has become a popular research area in the past decades. The rapid development of intelligent tra c management system attracts the software industry to come up with e cient tools for tra c prediction over the roads. In this study, Discrete Wavelet Transformation (DWT) is employed with Artificial Neural Network (ANN) to forecast the tra c flow over the ...

This paper reports a comparative study between continuous hidden Markov model (CHMM) and artificial neural network (ANN) on text dependent, closed set speaker identification (SID) system with Thai language recording in office environment. Thai isolated digit 0-9 and their concatenation are used as speaking text. Mel frequency cepstral coefficients (MFCC) are selected as the studied features. Tw...