prediction of precipitation is very important. regarding to the non- linear relationships and uncertainty of models, there is no superior and persuasive model among various proposed models to simulate precise precipitation and its amount. wavelet is one of the novel and very effective methods in time series and signals analyzing, that has been considered in the field of hydrology in recent year...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

the vast use of linear prediction coefficients (lpc) in speech processing systems has intensified the importance of their accurate computation. this paper is concerned with computing lpc coefficients using evolutionary algorithms: genetic algorithm (ga), particle swarm optimization (pso), dif-ferential evolution (de) and particle swarm optimization with differentially perturbed velocity (pso-dv...

The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential Evolution (DE) and Particle Swarm Optimization with Differentially perturbed Velocity (PSO-DV...

in addition to its primary role of providing financial protection for other industries the insurance industry also serves as a medium for fund mobilization. in spite of the harsh economic environment in nigeria, the insurance industry has been crucial to the consummation of business plans and wealth creation.  however, the continued downturn experienced by many countries, in the last decade, se...

this paper aims to propose an effective paroxysmal atrial fibrillation (paf) predictor which is based on the analysis of the heart rate variability (hrv) signal. predicting the onset of paf, based on non-invasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize the risks for the patients. this method consists of four st...

the net analyte signal standard addition method was used for simultaneous spectrophotometric determination of sertraline and fluoxetine in pharmaceutical preparations. the method combines the advantages of the standard addition method with the net analyte signal concept to enable the extraction of information about an analyte from the spectra of multi-component mixtures. this method uses full s...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...