background: one issue of concern in water supply is the quality of water. measuring the qualitative parameters of water is time-consuming and costly. predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. methods: the present study used an artificial neural network (ann...

objective: social anxiety disorder (sad) is defined as a constant fear of being embarrassed or negatively evaluated in social situations or while doing activities in the presence of others. several studies have examined the role of certain variables that might predict response to treatment and may affect treatment outcome. the purpose of this study was to identify predictive variables of change...

ABSTRACT The contribution is aimed at predictive control of nonlinear processes with the help of artificial neural networks as the predictor. Since this methodology is relatively wide, paper only concentrates on the prediction via artificial neural networks. Special attention is paid to the usage of offline-learnt predictor based on multilayer feed forward neural network. The proposed method is...

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is sho...

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...

this paper proposes a hybrid control scheme for the synchronization of two chaotic duffing oscillator system, subject to uncertainties and external disturbances. the novelty of this scheme is that the linear quadratic regulation (lqr) control, sliding mode (sm) control and gaussian radial basis function neural network (grbfnn) control are combined to chaos synchronization with respect to extern...