This paper compares the accuracy of three hybrid intelligent systems in forecasting ten international stock market indices; namely the CAC40, DAX, FTSE, Hang Seng, KOSPI, NASDAQ, NIKKEI, S&P500, Taiwan stock market price index, and the Canadian TSE. In particular, genetic algorithms (GA) are used to optimize the topology and parameters of the adaptive time delay neural networks (ATNN) and the t...

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

This paper focuses on the non-fragile guaranteed cost control problem for a class of TakagiSugeno (T-S) fuzzy time-varying delay systems with local bilinear models and different state and input delays. A non-fragile guaranteed cost state-feedback controller is designed such that the closed-loop T-S fuzzy local bilinear control system is delay-dependent asymptotically stable, and the closed-loop...

This paper presents a neuro-fuzzy control strategy with online estimation of Round Trip Time delay for nonlinear Networked Control Systems, first a fuzzy model is identified offline through inputs-states data with delay measurement, therefore, parameters for the estimation of Round Trip Time delay are obtained. The fuzzy control is designed by Linear Quadratic Regulation and a stability analysi...

In a series of papers and a book, M. Margaliot and G. Langholz proposed a hyperbolic approach to fuzzy control, in which they apply a certain hyperbolic non-linear transformation to the original variables. In this paper, we consider all possible non-linear transformations of this type and show that this hyperbolic transformation is indeed optimal.

This paper deals with the problems of stability analysis and control designs for a class of delay-dependent nonlinear systems with input constraint when using T-S fuzzy model in consideration of the uncertainties in the system. As a result, it arrives at two kinds of feedback controllers in terms of linear matrix inequalities (LMIs), in which the latter tries to use less information about the d...

In this paper, we study the existence of extremal solutions forimpulsive delay fuzzy integrodifferential equations in$n$-dimensional fuzzy vector space, by using monotone method. Weshow that obtained result is an extension of the result ofRodr'{i}guez-L'{o}pez cite{rod2} to impulsive delay fuzzyintegrodifferential equations in $n$-dimensional fuzzy vector space.

introduction: the adaptive neuro-fuzzy inference system (anfis) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. in this study we used this model in breast cancer detection. methodology: a set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  first, the risk fact...

Previously, we (McKerchar et al., 2009) showed that two-parameter hyperboloid models (Green and Myerson, 2004; Rachlin, 2006) provide significantly better fits to delay discounting data than simple, one-parameter hyperbolic and exponential models. Here, we extend this effort by comparing fits of the two-parameter hyperboloid models to data from a larger sample of participants (N=171) who discou...