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...

background and objectives: survival models are statistical technique to estimate or predict the overall time up to specific events. prediction is important in medical science and the accuracy of prediction is determined by a measurement, generally based on loss functions, called prediction error. the aim of this study is using parametric models to determine the factors influencing predicted sur...

the quality of wastewater generated in any process industry is generally indicated by performance indices namely bod, cod and toc, expressed in mg/l. the use of toc as an analytica parameter has become more common in recent years especially for the treatment of industrial wastewater. in this study, several empirical relationships were established between bod and cod with toc using regression an...

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 current study aims to investigate the relationship between stock liquidity risk and financial information quality criteria (i.e. the timely dividends announcement, accruals quality and the percentage of profitability prediction error) of companies listed on the tehran stock exchange. for this purpose, 148 cases of data from listed companies, collected from 2007 to 2012, were employed in ord...

This paper reports a preliminary attempt on data-driven modeling of segmental (phoneme) duration for two Indian languages Hindi and Telugu. Classification and Regression Tree (CART) based data-driven duration modeling for segmental duration prediction is presented. A number of features are proposed and their usefulness and relative contribution in segmental duration prediction is assessed. Obje...

This paper reports preliminary results of data-driven modeling of segmental (phoneme) duration for Hindi. Classification and Regression Tree (CART) based datadriven duration modeling for segmental duration prediction is presented. A number of features are considered and their usefulness and relative contribution for segmental duration prediction is assessed. Objective evaluation of the duration...