We investigate Egypt's Taylor rule (interest rate targeting) between 1976 and 2019 by including the main economic variables in its reaction function. Using principle, we Egypt’s monetary policy optimality. To this end, conduct generalized method of moments (GMM) estimation procedure with different specifications to deal potential endogeneity among variables. Our GMM estimates reveal that partia...

A fuzzy control design method for four-wheel-steering vehicles, using fuzzy models, is presented. The design model is obtained from a vehicle model using fuzzy modeling approach. In the first step of the controller design, an optimal steering controller is proposed for each local model using LQR method. Then, the local controllers are combined using fuzzy rules to form a fuzzy controller. In th...

In this paper, we numerically investigate two distinct phenomena, coherence resonance (CR) and self-induced stochastic (SISR), in multiplex neural networks the presence of spike-timing-dependent plasticity (STDP). The high degree CR achieved one layer network turns out to be more robust than that SISR against variations topology STDP parameters. This behavior is opposite presented by Yamakou Jo...

This paper reviews applications of optimization techniques connected with reservoir simulation models to search for optimal rule curves. The literature reporting the suitable curves is discussed and examined. development searching processes are investigated by focusing on fitness function constraints. There five groups algorithms that have been applied find curves: trial error technique model, ...

We consider the problem of distributed binary hypothesis testing with independent identical sensors. It is well known that for this problem the optimal sensor rules are a likelihood ratio threshold tests and the optimal fusion rule is a K-out-of-N rule [1]. Under the Bayesian criterion, we show that for a fixed K-out-of-N fusion rule, the probability of error is a quasiconvex function of the li...

The main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. Recently there have been attempts for using artificial neural networks (ANNs) in optimizationproblems and some types of ANNs such as Hopfield network and Boltzm...

We present a novel theoretical approach to the analysis of adaptive quadratures and adaptive Simpson quadratures in particular which leads to the construction of a new algorithm for automatic integration. For a given function [Formula: see text] with [Formula: see text] and possible endpoint singularities the algorithm produces an approximation to [Formula: see text] within a given [Formula: se...

In a stochastic and fuzzy environment, two kinds of stopping models are discussed and compared. The optimal fuzzy stopping times are given under the assumptions of monotonicity and regularity for stopping rules. Also, we find that fuzzy stopping times are favored in a comparison between fuzzy and classical stopping models. Q 2000 Academic Press